Sensor array calibration via tracking with the extended Kalman filter. - Volkan Cevher; James H. McClellan (ICASSP, 2001)

Fast initialization of particle filters using a modified metropolis-Hastings algorithm: mode-hungry approach. - Volkan Cevher; James H. McClellan (ICASSP (2), 2004)

Proposal strategies for joint state-space tracking with particle filters. - Volkan Cevher; James H. McClellan (ICASSP (2), 2005)

General direction-of-arrival tracking with acoustic nodes. - Volkan Cevher; James H. McClellan (IEEE Trans. Signal Process., 2005)

A Bayesian Framework for Target Tracking using Acoustic and Image Measurements. - Volkan Cevher (2005)

A joint radar-acoustic particle filter tracker with acoustic propagation delay compensation. - Volkan Cevher; Milind Borkar; James H. McClellan (EUSIPCO, 2006)

On low-power analog implementation of particle filters for target tracking. - Rajbabu Velmurugan; Shyam Subramanian; Volkan Cevher; David Abramson 002; Kofi M. Odame; Jordan D. Gray; Haw-Jing Lo; James H. McClellan; David V. Anderson (EUSIPCO, 2006)

Optimal Experiments With Seismic Sensors. - Mubashir Alam; Volkan Cevher; James H. McClellan (ICASSP (4), 2006)

A Monte-Carlo Method for Initializing Distributed Tracking Algorithms. - Milind Borkar; Volkan Cevher; James H. McClellan (ICASSP (4), 2006)

A Range-Only Multiple Target Particle Filter Tracker. - Volkan Cevher; Rajbabu Velmurugan; James H. McClellan (ICASSP (4), 2006)

Joint Acoustic-Video Fingerprinting of Vehicles, Part I. - Volkan Cevher; Rama Chellappa; James H. McClellan (ICASSP (2), 2007)

Joint Acoustic-Video Fingerprinting of Vehicles, Part II. - Volkan Cevher; Feng Guo 006; Aswin C. Sankaranarayanan; Rama Chellappa (ICASSP (2), 2007)

Low computation and low latency algorithms for distributed sensor network initialization. - Milind Borkar; Volkan Cevher; James H. McClellan (Signal Image Video Process., 2007)

Optimal Maneuvering of Seismic Sensors for Localization of Subsurface Targets. - Mubashir Alam; Volkan Cevher; James H. McClellan; Greg D. Larson; Waymond R. Scott (IEEE Trans. Geosci. Remote. Sens., 2007)

Target Tracking Using a Joint Acoustic Video System. - Volkan Cevher; Aswin C. Sankaranarayanan; James H. McClellan; Rama Chellappa (IEEE Trans. Multim., 2007)

Acoustic Multitarget Tracking Using Direction-of-Arrival Batches. - Volkan Cevher; Rajbabu Velmurugan; James H. McClellan (IEEE Trans. Signal Process., 2007)

Decentralized State Initialization with Delay Compensation for Multi-modal Sensor Networks. - Milind Borkar; Volkan Cevher; James H. McClellan (J. VLSI Signal Process., 2007)

Compressive Sensing for Background Subtraction. - Volkan Cevher; Aswin C. Sankaranarayanan; Marco F. Duarte; Dikpal Reddy; Richard G. Baraniuk; Rama Chellappa (ECCV (2), 2008)

Distributed target localization via spatial sparsity. - Volkan Cevher; Marco F. Duarte; Richard G. Baraniuk (EUSIPCO, 2008)

Compressive wireless arrays for bearing estimation. - Volkan Cevher; Ali Cafer Gürbüz; James H. McClellan; Rama Chellappa (ICASSP, 2008)

Factorized variational approximations for acoustic multi source localization. - Volkan Cevher; Aswin C. Sankaranarayanan; Rama Chellappa (ICASSP, 2008)

A compressive beamforming method. - Ali Cafer Gürbüz; James H. McClellan; Volkan Cevher (ICASSP, 2008)

Compressed sensing for multi-view tracking and 3-D voxel reconstruction. - Dikpal Reddy; Aswin C. Sankaranarayanan; Volkan Cevher; Rama Chellappa (ICIP, 2008)

Pareto Frontiers of Sensor Networks for Localization. - Volkan Cevher; Lance M. Kaplan (IPSN, 2008)

Sparse Signal Recovery Using Markov Random Fields. - Volkan Cevher; Marco F. Duarte; Chinmay Hegde; Richard G. Baraniuk (NIPS, 2008)

Model-based compressive sensing for signal ensembles. - Marco F. Duarte; Volkan Cevher; Richard G. Baraniuk (Allerton, 2009)

Recovery of compressible signals in unions of subspaces. - Marco F. Duarte; Chinmay Hegde; Volkan Cevher; Richard G. Baraniuk (CISS, 2009)

Near-optimal Bayesian localization via incoherence and sparsity. - Volkan Cevher; Petros Boufounos; Richard G. Baraniuk; Anna C. Gilbert; Martin J. Strauss (IPSN, 2009)

Learning with Compressible Priors. - Volkan Cevher (NIPS, 2009)

Acoustic sensor network design for position estimation. - Volkan Cevher; Lance M. Kaplan (ACM Trans. Sens. Networks, 2009)

Vehicle Speed Estimation Using Acoustic Wave Patterns. - Volkan Cevher; Rama Chellappa; James H. McClellan (IEEE Trans. Signal Process., 2009)

Distributed bearing estimation via matrix completion. - Andrew E. Waters; Volkan Cevher (ICASSP, 2010)

Submodular Dictionary Selection for Sparse Representation. - Andreas Krause 001; Volkan Cevher (ICML, 2010)

Low-Dimensional Models for Dimensionality Reduction and Signal Recovery: A Geometric Perspective. - Richard G. Baraniuk; Volkan Cevher; Michael B. Wakin (Proc. IEEE, 2010)

Sparse Signal Recovery and Acquisition with Graphical Models. - Volkan Cevher; Piotr Indyk; Lawrence Carin; Richard G. Baraniuk (IEEE Signal Process. Mag., 2010)

Model-based compressive sensing. - Richard G. Baraniuk; Volkan Cevher; Marco F. Duarte; Chinmay Hegde (IEEE Trans. Inf. Theory, 2010)

Compressive sensing under matrix uncertainties: An Approximate Message Passing approach. - Jason T. Parker; Volkan Cevher; Philip Schniter (ACSCC, 2011)

Recipes on hard thresholding methods. - Anastasios Kyrillidis; Volkan Cevher (CAMSAP, 2011)

Model-based compressive sensing for multi-party distant speech recognition. - Afsaneh Asaei; Hervé Bourlard; Volkan Cevher (ICASSP, 2011)

An ALPS view of sparse recovery. - Volkan Cevher (ICASSP, 2011)

Online performance guarantees for sparse recovery. - Raja Giryes; Volkan Cevher (ICASSP, 2011)

Compressive sensing meets game theory. - Sina Jafarpour; Robert E. Schapire; Volkan Cevher (ICASSP, 2011)

Multi-Party Speech Recovery Exploiting Structured Sparsity Models. - Afsaneh Asaei; Mohammad Javad Taghizadeh; Hervé Bourlard; Volkan Cevher (INTERSPEECH, 2011)

A game theoretic approach to expander-based compressive sensing. - Sina Jafarpour; Volkan Cevher; Robert E. Schapire (ISIT, 2011)

Greedy Dictionary Selection for Sparse Representation. - Volkan Cevher; Andreas Krause 001 (IEEE J. Sel. Top. Signal Process., 2011)

Learning Low-Dimensional Signal Models. - Lawrence Carin; Richard G. Baraniuk; Volkan Cevher; David B. Dunson; Michael I. Jordan; Guillermo Sapiro; Michael B. Wakin (IEEE Signal Process. Mag., 2011)

Computational methods for structured sparse component analysis of convolutive speech mixtures. - Afsaneh Asaei; Michael E. Davies 001; Hervé Bourlard; Volkan Cevher (ICASSP, 2012)

Filtered Variation method for denoising and sparse signal processing. - Kivanç Köse; Volkan Cevher; A. Enis Çetin (ICASSP, 2012)

Hard thresholding with norm constraints. - Anastasios Kyrillidis; Gilles Puy; Volkan Cevher (ICASSP, 2012)

Learning ridge functions with randomized sampling in high dimensions. - Hemant Tyagi; Volkan Cevher (ICASSP, 2012)

Structured sparse coding for microphone array location calibration. - Afsaneh Asaei; Bhiksha Raj; Hervé Bourlard; Volkan Cevher (SAPA@INTERSPEECH, 2012)

Combinatorial selection and least absolute shrinkage via the Clash algorithm. - Anastasios Kyrillidis; Volkan Cevher (ISIT, 2012)

Active Learning of Multi-Index Function Models. - Hemant Tyagi; Volkan Cevher (NIPS, 2012)

Equivalence of synthesis and atomic formulations of sparse recovery. - Mitra Fatemi; Shayan Dashmiz; Mohammad Hossein Shafinia; Volkan Cevher (SSP, 2012)

MATRIX ALPS: Accelerated low rank and sparse matrix reconstruction. - Anastasios Kyrillidis; Volkan Cevher (SSP, 2012)

Sparse projections onto the simplex - Anastasios Kyrillidis; Stephen Becker; Volkan Cevher (CoRR, 2012)

Structured Sparsity Models for Multiparty Speech Recovery from Reverberant Recordings - Afsaneh Asaei; Mohammad Golbabaee; Hervé Bourlard; Volkan Cevher (CoRR, 2012)

Bearing Estimation via Spatial Sparsity using Compressive Sensing. - Ali Cafer Gürbüz; Volkan Cevher; James H. McClellan (IEEE Trans. Aerosp. Electron. Syst., 2012)

Compressible Distributions for High-Dimensional Statistics. - Rémi Gribonval; Volkan Cevher; Mike E. Davies 001 (IEEE Trans. Inf. Theory, 2012)

Manifold sparse beamforming. - Baran Gozcu; Afsaneh Asaei; Volkan Cevher (CAMSAP, 2013)

To convexify or not? Regression with clustering penalties on graphs. - Marwa El Halabi; Luca Baldassarre; Volkan Cevher (CAMSAP, 2013)

Tractability of interpretability via selection of group-sparse models. - Nirav Bhan; Luca Baldassarre; Volkan Cevher (GlobalSIP, 2013)

Sparse simplex projections for portfolio optimization. - Anastasios Kyrillidis; Stephen Becker; Volkan Cevher; Christoph Koch 001 (GlobalSIP, 2013)

Fast proximal algorithms for Self-concordant function minimization with application to sparse graph selection. - Anastasios Kyrillidis; Volkan Cevher (ICASSP, 2013)

Sparse projections onto the simplex. - Anastasios Kyrillidis; Stephen Becker; Volkan Cevher; Christoph Koch 001 (ICML (2), 2013)

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions. - Quoc Tran-Dinh; Anastasios Kyrillidis; Volkan Cevher (ICML (2), 2013)

High-Dimensional Gaussian Process Bandits. - Josip Djolonga; Andreas Krause 001; Volkan Cevher (NIPS, 2013)

Energy-aware adaptive bi-Lipschitz embeddings. - Bubacarr Bah; Ali Sadeghian; Volkan Cevher (CoRR, 2013)

Bilinear Generalized Approximate Message Passing. - Jason T. Parker; Philip Schniter; Volkan Cevher (CoRR, 2013)

Randomized Low-Memory Singular Value Projection - Stephen Becker; Volkan Cevher; Anastasios Kyrillidis (CoRR, 2013)

Group-Sparse Model Selection: Hardness and Relaxations - Luca Baldassarre; Nirav Bhan; Volkan Cevher; Anastasios Kyrillidis (CoRR, 2013)

Scalable Sparse Covariance Estimation via Self-Concordance. - Anastasios Kyrillidis; Rabeeh Karimi Mahabadi; Quoc Tran-Dinh; Volkan Cevher (AAAI, 2014)

Model-based sparse component analysis for reverberant speech localization. - Afsaneh Asaei; Hervé Bourlard; Mohammad Javad Taghizadeh; Volkan Cevher (ICASSP, 2014)

Metric learning with rank and sparsity constraints. - Bubacarr Bah; Stephen Becker; Volkan Cevher; Baran Gozcu (ICASSP, 2014)

Barrier smoothing for nonsmooth convex minimization. - Quoc Tran-Dinh; Yen-Huan Li; Volkan Cevher (ICASSP, 2014)

Map estimation for Bayesian mixture models with submodular priors. - Marwa El Halabi; Luca Baldassarre; Volkan Cevher (MLSP, 2014)

Time-Data Tradeoffs by Aggressive Smoothing. - John J. Bruer; Joel A. Tropp; Volkan Cevher; Stephen Becker (NIPS, 2014)

Constrained convex minimization via model-based excessive gap. - Quoc Tran-Dinh; Volkan Cevher (NIPS, 2014)

Model-based Sketching and Recovery with Expanders. - Bubacarr Bah; Luca Baldassarre; Volkan Cevher (SODA, 2014)

A variational approach to stable principal component pursuit. - Aleksandr Y. Aravkin; Stephen Becker; Volkan Cevher; Peder A. Olsen (UAI, 2014)

Convex Optimization for Big Data. - Volkan Cevher; Stephen Becker; Mark Schmidt 001 (CoRR, 2014)

Matrix Recipes for Hard Thresholding Methods. - Anastasios Kyrillidis; Volkan Cevher (J. Math. Imaging Vis., 2014)

An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization. - Quoc Tran-Dinh; Anastasios Kyrillidis; Volkan Cevher (SIAM J. Optim., 2014)

Convex Optimization for Big Data: Scalable, randomized, and parallel algorithms for big data analytics. - Volkan Cevher; Stephen Becker; Mark Schmidt 001 (IEEE Signal Process. Mag., 2014)

Convexity in Source Separation : Models, geometry, and algorithms. - Michael B. McCoy; Volkan Cevher; Quoc Tran-Dinh; Afsaneh Asaei; Luca Baldassarre (IEEE Signal Process. Mag., 2014)

Structured Sparsity Models for Reverberant Speech Separation. - Afsaneh Asaei; Mohammad Golbabaee; Hervé Bourlard; Volkan Cevher (IEEE ACM Trans. Audio Speech Lang. Process., 2014)

Bilinear Generalized Approximate Message Passing - Part I: Derivation. - Jason T. Parker; Philip Schniter; Volkan Cevher (IEEE Trans. Signal Process., 2014)

Bilinear Generalized Approximate Message Passing - Part II: Applications. - Jason T. Parker; Philip Schniter; Volkan Cevher (IEEE Trans. Signal Process., 2014)

Stochastic Spectral Descent for Restricted Boltzmann Machines. - David E. Carlson; Volkan Cevher; Lawrence Carin (AISTATS, 2015)

A totally unimodular view of structured sparsity. - Marwa El Halabi; Volkan Cevher (AISTATS, 2015)

Sparsistency of 1-Regularized M-Estimators. - Yen-Huan Li; Jonathan Scarlett; Pradeep Ravikumar; Volkan Cevher (AISTATS, 2015)

WASP: Scalable Bayes via barycenters of subset posteriors. - Sanvesh Srivastava; Volkan Cevher; Quoc Tran-Dinh; David B. Dunson (AISTATS, 2015)

Structured sampling and recovery of iEEG signals. - Luca Baldassarre; Cosimo Aprile; Mahsa Shoaran; Yusuf Leblebici; Volkan Cevher (CAMSAP, 2015)

Scalable convex methods for phase retrieval. - Alp Yurtsever; Ya-Ping Hsieh; Volkan Cevher (CAMSAP, 2015)

A primal-dual framework for mixtures of regularizers. - Baran Gozcu; Luca Baldassarre; Quoc Tran-Dinh; Cosimo Aprile; Volkan Cevher (EUSIPCO, 2015)

Active learning of self-concordant like multi-index functions. - Ilija Bogunovic; Volkan Cevher; Jarvis D. Haupt; Jonathan Scarlett (ICASSP, 2015)

Consistency of ℓ1-regularized maximum-likelihood for compressive Poisson regression. - Yen-Huan Li; Volkan Cevher (ICASSP, 2015)

Dynamic sparse state estimation using ℓ1-ℓ1 minimization: Adaptive-rate measurement bounds, algorithms and applications. - João F. C. Mota; Nikos Deligiannis; Aswin C. Sankaranarayanan; Volkan Cevher; Miguel R. D. Rodrigues (ICASSP, 2015)

Sparse group covers and greedy tree approximations. - Siddhartha Satpathi; Luca Baldassarre; Volkan Cevher (ISIT, 2015)

A concentration-of-measure inequality for multiple-measurement models. - Liming Wang 004; Jiaji Huang; Xin Yuan 002; Volkan Cevher; Miguel R. D. Rodrigues; A. Robert Calderbank; Lawrence Carin (ISIT, 2015)

Composite Convex Minimization Involving Self-concordant-Like Cost Functions. - Quoc Tran-Dinh; Yen-Huan Li; Volkan Cevher (MCO (1), 2015)

Preconditioned Spectral Descent for Deep Learning. - David E. Carlson; Edo Collins; Ya-Ping Hsieh; Lawrence Carin; Volkan Cevher (NIPS, 2015)

A Universal Primal-Dual Convex Optimization Framework. - Alp Yurtsever; Quoc Tran-Dinh; Volkan Cevher (NIPS, 2015)

A 5.9mW/Gb/s 7Gb/s/pin 8-lane single-ended RX with crosstalk cancellation scheme using a XCTLE and 56-tap XDFE in 32nm SOI CMOS. - Alessandro Cevrero; Cosimo Aprile; Pier Andrea Francese; Urs Bapst; Christian Menolfi; Matthias Braendli; Marcel A. Kossel; Thomas Morf; Lukas Kull; Hazar Yueksel; Ilter Oezkaya; Yusuf Leblebici; et al. (VLSIC, 2015)

What's the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid. - Petros Boufounos; Volkan Cevher; Anna C. Gilbert; Yi Li 002; Martin J. Strauss (Algorithmica, 2015)

Linear Inverse Problems with Norm and Sparsity Constraints. - Volkan Cevher; Sina Jafarpour; Anastasios Kyrillidis (CoRR, 2015)

Structured Sparsity: Discrete and Convex approaches. - Anastasios Kyrillidis; Luca Baldassarre; Marwa El Halabi; Quoc Tran-Dinh; Volkan Cevher (CoRR, 2015)

Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Background Subtraction. - João F. C. Mota; Nikos Deligiannis; Aswin C. Sankaranarayanan; Volkan Cevher; Miguel R. D. Rodrigues (CoRR, 2015)

Limits on Support Recovery with Probabilistic Models: An Information-Spectrum Approach. - Jonathan Scarlett; Volkan Cevher (CoRR, 2015)

Composite self-concordant minimization. - Quoc Tran-Dinh; Anastasios Kyrillidis; Volkan Cevher (J. Mach. Learn. Res., 2015)

Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost. - John J. Bruer; Joel A. Tropp; Volkan Cevher; Stephen Becker (IEEE J. Sel. Top. Signal Process., 2015)

Introduction to the issue on signal processing for big data. - Georgios B. Giannakis; Raphael Cendrillon; Volkan Cevher; Ananthram Swami; Zhi Tian (IEEE J. Sel. Top. Signal Process., 2015)

Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements. - Liming Wang 004; Jiaji Huang; Xin Yuan 002; Kalyani Krishnamurthy; Joel A. Greenberg; Volkan Cevher; Miguel R. D. Rodrigues; David J. Brady; A. Robert Calderbank; Lawrence Carin (SIAM J. Imaging Sci., 2015)

Time-Varying Gaussian Process Bandit Optimization. - Ilija Bogunovic; Jonathan Scarlett; Volkan Cevher (AISTATS, 2016)

Convex Block-sparse Linear Regression with Expanders - Provably. - Anastasios Kyrillidis; Bubacarr Bah; Rouzbeh Hasheminezhad; Quoc Tran-Dinh; Luca Baldassarre; Volkan Cevher (AISTATS, 2016)

Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices. - Jonathan Scarlett; Volkan Cevher (AISTATS, 2016)

Estimation error of the constrained lasso. - Nissim Zerbib; Yen-Huan Li; Ya-Ping Hsieh; Volkan Cevher (Allerton, 2016)

Learning-Based Near-Optimal Area-Power Trade-offs in Hardware Design for Neural Signal Acquisition. - Cosimo Aprile; Luca Baldassarre; Vipul Gupta; Juhwan Yoo; Mahsa Shoaran; Yusuf Leblebici; Volkan Cevher (ACM Great Lakes Symposium on VLSI, 2016)

Learning data triage: Linear decoding works for compressive MRI. - Yen-Huan Li; Volkan Cevher (ICASSP, 2016)

Frank-Wolfe works for non-Lipschitz continuous gradient objectives: Scalable poisson phase retrieval. - Gergely Ódor; Yen-Huan Li; Alp Yurtsever; Ya-Ping Hsieh; Quoc Tran-Dinh; Marwa El Halabi; Volkan Cevher (ICASSP, 2016)

Partial recovery bounds for the sparse stochastic block model. - Jonathan Scarlett; Volkan Cevher (ISIT, 2016)

Converse bounds for noisy group testing with arbitrary measurement matrices. - Jonathan Scarlett; Volkan Cevher (ISIT, 2016)

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation. - Ilija Bogunovic; Jonathan Scarlett; Andreas Krause 001; Volkan Cevher (NIPS, 2016)

An Efficient Streaming Algorithm for the Submodular Cover Problem. - Ashkan Norouzi-Fard; Abbas Bazzi; Ilija Bogunovic; Marwa El Halabi; Ya-Ping Hsieh; Volkan Cevher (NIPS, 2016)

Stochastic Three-Composite Convex Minimization. - Alp Yurtsever; Bang Công Vu; Volkan Cevher (NIPS, 2016)

Phase Transitions in Group Testing. - Jonathan Scarlett; Volkan Cevher (SODA, 2016)

Randomized single-view algorithms for low-rank matrix approximation. - Joel A. Tropp; Alp Yurtsever; Madeleine Udell; Volkan Cevher (CoRR, 2016)

Learning-Based Compressive Subsampling. - Luca Baldassarre; Yen-Huan Li; Jonathan Scarlett; Baran Gozcu; Ilija Bogunovic; Volkan Cevher (IEEE J. Sel. Top. Signal Process., 2016)

Stochastic Spectral Descent for Discrete Graphical Models. - David E. Carlson; Ya-Ping Hsieh; Edo Collins; Lawrence Carin; Volkan Cevher (IEEE J. Sel. Top. Signal Process., 2016)

Computational methods for underdetermined convolutive speech localization and separation via model-based sparse component analysis. - Afsaneh Asaei; Hervé Bourlard; Mohammad Javad Taghizadeh; Volkan Cevher (Speech Commun., 2016)

Group-Sparse Model Selection: Hardness and Relaxations. - Luca Baldassarre; Nirav Bhan; Volkan Cevher; Anastasios Kyrillidis; Siddhartha Satpathi (IEEE Trans. Inf. Theory, 2016)

Fixed Points of Generalized Approximate Message Passing With Arbitrary Matrices. - Sundeep Rangan; Philip Schniter; Erwin Riegler; Alyson K. Fletcher; Volkan Cevher (IEEE Trans. Inf. Theory, 2016)

On the Difficulty of Selecting Ising Models With Approximate Recovery. - Jonathan Scarlett; Volkan Cevher (IEEE Trans. Signal Inf. Process. over Networks, 2016)

Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization. - Afsaneh Asaei; Mohammad Javad Taghizadeh; Saeid Haghighatshoar; Bhiksha Raj; Hervé Bourlard; Volkan Cevher (IEEE Trans. Signal Process., 2016)

Adaptive-Rate Reconstruction of Time-Varying Signals With Application in Compressive Foreground Extraction. - João F. C. Mota; Nikos Deligiannis; Aswin C. Sankaranarayanan; Volkan Cevher; Miguel R. D. Rodrigues (IEEE Trans. Signal Process., 2016)

Faster Coordinate Descent via Adaptive Importance Sampling. - Dmytro Perekrestenko; Volkan Cevher; Martin Jaggi (AISTATS, 2017)

Lower Bounds on Active Learning for Graphical Model Selection. - Jonathan Scarlett; Volkan Cevher (AISTATS, 2017)

Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage. - Alp Yurtsever; Madeleine Udell; Joel A. Tropp; Volkan Cevher (AISTATS, 2017)

A distributed algorithm for partitioned robust submodular maximization. - Ilija Bogunovic; Slobodan Mitrovic; Jonathan Scarlett; Volkan Cevher (CAMSAP, 2017)

DCT Learning-Based Hardware Design for Neural Signal Acquisition Systems. - Cosimo Aprile; Johannes Wüthrich; Luca Baldassarre; Yusuf Leblebici; Volkan Cevher (Conf. Computing Frontiers, 2017)

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization. - Jonathan Scarlett; Ilija Bogunovic; Volkan Cevher (COLT, 2017)

How little does non-exact recovery help in group testing? - Jonathan Scarlett; Volkan Cevher (ICASSP, 2017)

Robust Submodular Maximization: A Non-Uniform Partitioning Approach. - Ilija Bogunovic; Slobodan Mitrovic; Jonathan Scarlett; Volkan Cevher (ICML, 2017)

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization. - Ahmet Alacaoglu; Quoc Tran-Dinh; Olivier Fercoq; Volkan Cevher (NIPS, 2017)

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach. - Slobodan Mitrovic; Ilija Bogunovic; Ashkan Norouzi-Fard; Jakub Tarnawski; Volkan Cevher (NIPS, 2017)

Phase Transitions in the Pooled Data Problem. - Jonathan Scarlett; Volkan Cevher (NIPS, 2017)

Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data. - Joel A. Tropp; Alp Yurtsever; Madeleine Udell; Volkan Cevher (NIPS, 2017)

An adaptive sublinear-time block sparse fourier transform. - Volkan Cevher; Michael Kapralov; Jonathan Scarlett; Amir Zandieh (STOC, 2017)

Efficient and Near-Optimal Noisy Group Testing: An Information-Theoretic Framework. - Jonathan Scarlett; Volkan Cevher (CoRR, 2017)

Practical Sketching Algorithms for Low-Rank Matrix Approximation. - Joel A. Tropp; Alp Yurtsever; Madeleine Udell; Volkan Cevher (SIAM J. Matrix Anal. Appl., 2017)

Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework. - Jonathan Scarlett; Volkan Cevher (IEEE Trans. Inf. Theory, 2017)

Robust Maximization of Non-Submodular Objectives. - Ilija Bogunovic; Junyao Zhao 001; Volkan Cevher (AISTATS, 2018)

Combinatorial Penalties: Which structures are preserved by convex relaxations? - Marwa El Halabi; Francis R. Bach; Volkan Cevher (AISTATS, 2018)

High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups. - Paul Rolland; Jonathan Scarlett; Ilija Bogunovic; Volkan Cevher (AISTATS, 2018)

Stochastic Three-Composite Convex Minimization with a Linear Operator. - Renbo Zhao; Volkan Cevher (AISTATS, 2018)

Dimension-free Information Concentration via Exp-Concavity. - Ya-Ping Hsieh; Volkan Cevher (ALT, 2018)

An area and power efficient on-the-fly LBCS transformation for implantable neuronal signal acquisition systems. - Cosimo Aprile; Johannes Wüthrich; Luca Baldassarre; Yusuf Leblebici; Volkan Cevher (CF, 2018)

Real-Time DCT Learning-based Reconstruction of Neural Signals. - Rabeeh Karimi Mahabadi; Cosimo Aprile; Volkan Cevher (EUSIPCO, 2018)

Let's be Honest: An Optimal No-Regret Framework for Zero-Sum Games. - Ehsan Asadi Kangarshahi; Ya-Ping Hsieh; Mehmet Fatih Sahin; Volkan Cevher (ICML, 2018)

Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods. - Junhong Lin; Volkan Cevher (ICML, 2018)

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces. - Junhong Lin; Volkan Cevher (ICML, 2018)

A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming. - Alp Yurtsever; Olivier Fercoq; Francesco Locatello; Volkan Cevher (ICML, 2018)

Adversarially Robust Optimization with Gaussian Processes. - Ilija Bogunovic; Jonathan Scarlett; Stefanie Jegelka; Volkan Cevher (NeurIPS, 2018)

Mirrored Langevin Dynamics. - Ya-Ping Hsieh; Ali Kavis; Paul Rolland; Volkan Cevher (NeurIPS, 2018)

Online Adaptive Methods, Universality and Acceleration. - Kfir Yehuda Levy; Alp Yurtsever; Volkan Cevher (NeurIPS, 2018)

Optimal Rates for Spectral-regularized Algorithms with Least-Squares Regression over Hilbert Spaces. - Junhong Lin; Volkan Cevher (CoRR, 2018)

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral-Regularization Algorithms. - Junhong Lin; Volkan Cevher (CoRR, 2018)

Mirrored Langevin Dynamics. - Ya-Ping Hsieh; Volkan Cevher (CoRR, 2018)

Kernel Conjugate Gradient Methods with Random Projections. - Junhong Lin; Volkan Cevher (CoRR, 2018)

Efficient learning of smooth probability functions from Bernoulli tests with guarantees. - Paul Rolland; Ali Kavis; Adish Singla; Volkan Cevher (CoRR, 2018)

An Eight-Lane 7-Gb/s/pin Source Synchronous Single-Ended RX With Equalization and Far-End Crosstalk Cancellation for Backplane Channels. - Cosimo Aprile; Alessandro Cevrero; Pier Andrea Francese; Christian Menolfi; Matthias Braendli; Marcel A. Kossel; Thomas Morf; Lukas Kull; Ilter Oezkaya; Yusuf Leblebici; Volkan Cevher; Thomas Toifl (IEEE J. Solid State Circuits, 2018)

Near-Optimal Noisy Group Testing via Separate Decoding of Items. - Jonathan Scarlett; Volkan Cevher (IEEE J. Sel. Top. Signal Process., 2018)

A Single-Phase, Proximal Path-Following Framework. - Quoc Tran-Dinh; Anastasios Kyrillidis; Volkan Cevher (Math. Oper. Res., 2018)

A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization. - Quoc Tran-Dinh; Olivier Fercoq; Volkan Cevher (SIAM J. Optim., 2018)

Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants. - Cosimo Aprile; Kerim Türe; Luca Baldassarre; Mahsa Shoaran; Gürkan Yilmaz; Franco Maloberti; Catherine Dehollain; Yusuf Leblebici; Volkan Cevher (IEEE Trans. Circuits Syst. I Regul. Pap., 2018)

Learning-Based Compressive MRI. - Baran Gozcu; Rabeeh Karimi Mahabadi; Yen-Huan Li; Efe Ilicak; Tolga Çukur; Jonathan Scarlett; Volkan Cevher (IEEE Trans. Medical Imaging, 2018)

A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization. - Ya-Ping Hsieh; Yu-Chun Kao; Rabeeh Karimi Mahabadi; Alp Yurtsever; Anastasios Kyrillidis; Volkan Cevher (IEEE Trans. Signal Process., 2018)

Iterative Classroom Teaching. - Teresa Yeo; Parameswaran Kamalaruban; Adish Singla; Arpit Merchant; Thibault Asselborn; Louis Faucon; Pierre Dillenbourg; Volkan Cevher (AAAI, 2019)

Rethinking Sampling in Parallel MRI: A Data-Driven Approach. - Baran Gözcü; Thomas Sanchez; Volkan Cevher (EUSIPCO, 2019)

Almost surely constrained convex optimization. - Olivier Fercoq; Ahmet Alacaoglu; Ion Necoara; Volkan Cevher (ICML, 2019)

Finding Mixed Nash Equilibria of Generative Adversarial Networks. - Ya-Ping Hsieh; Chen Liu 027; Volkan Cevher (ICML, 2019)

On Certifying Non-Uniform Bounds against Adversarial Attacks. - Chen Liu 027; Ryota Tomioka; Volkan Cevher (ICML, 2019)

Efficient learning of smooth probability functions from Bernoulli tests with guarantees. - Paul Rolland; Ali Kavis; Alexander Immer; Adish Singla; Volkan Cevher (ICML, 2019)

A Conditional-Gradient-Based Augmented Lagrangian Framework. - Alp Yurtsever; Olivier Fercoq; Volkan Cevher (ICML, 2019)

Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator. - Alp Yurtsever; Suvrit Sra; Volkan Cevher (ICML, 2019)

Interactive Teaching Algorithms for Inverse Reinforcement Learning. - Parameswaran Kamalaruban; Rati Devidze; Volkan Cevher; Adish Singla (IJCAI, 2019)

Overlapping Multi-Bandit Best Arm Identification. - Jonathan Scarlett; Ilija Bogunovic; Volkan Cevher (ISIT, 2019)

Fast and Provable ADMM for Learning with Generative Priors. - Fabian Latorre; Armin Eftekhari; Volkan Cevher (NeurIPS, 2019)

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization. - Ali Kavis; Kfir Y. Levy; Francis R. Bach; Volkan Cevher (NeurIPS, 2019)

Stochastic Frank-Wolfe for Composite Convex Minimization. - Francesco Locatello; Alp Yurtsever; Olivier Fercoq; Volkan Cevher (NeurIPS, 2019)

An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints. - Mehmet Fatih Sahin; Armin Eftekhari; Ahmet Alacaoglu; Fabian Latorre; Volkan Cevher (NeurIPS, 2019)

An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation. - Jonathan Scarlett; Volkan Cevher (CoRR, 2019)

Stochastic Conditional Gradient Method for Composite Convex Minimization. - Francesco Locatello; Alp Yurtsever; Olivier Fercoq; Volkan Cevher (CoRR, 2019)

Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI. - Thomas Sanchez; Baran Gözcü; Ruud B. van Heeswijk; Efe Ilicak; Tolga Çukur; Volkan Cevher (CoRR, 2019)

On Certifying Non-uniform Bound against Adversarial Attacks. - Chen Liu 027; Ryota Tomioka; Volkan Cevher (CoRR, 2019)

Fast and Provable ADMM for Learning with Generative Priors. - Fabian Latorre Gómez; Armin Eftekhari; Volkan Cevher (CoRR, 2019)

Convergence of the Exponentiated Gradient Method with Armijo Line Search. - Yen-Huan Li; Volkan Cevher (J. Optim. Theory Appl., 2019)

On the linear convergence of the stochastic gradient method with constant step-size. - Volkan Cevher; Bang Công Vu (Optim. Lett., 2019)

Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation. - Joel A. Tropp; Alp Yurtsever; Madeleine Udell; Volkan Cevher (SIAM J. Sci. Comput., 2019)

A Learning-Based Framework for Quantized Compressed Sensing. - Rabeeh Karimi Mahabadi; Junhong Lin; Volkan Cevher (IEEE Signal Process. Lett., 2019)

Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI. - Thomas Sanchez; Baran Gözcü; Ruud B. van Heeswijk; Armin Eftekhari; Efe Ilicak; Tolga Çukur; Volkan Cevher (ICASSP, 2020)

Lipschitz constant estimation of Neural Networks via sparse polynomial optimization. - Fabian Latorre; Paul Rolland; Volkan Cevher (ICLR, 2020)

Random extrapolation for primal-dual coordinate descent. - Ahmet Alacaoglu; Olivier Fercoq; Volkan Cevher (ICML, 2020)

A new regret analysis for Adam-type algorithms. - Ahmet Alacaoglu; Yura Malitsky; Panayotis Mertikopoulos; Volkan Cevher (ICML, 2020)

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks. - Fabian Latorre; Paul Rolland; Nadav Hallak; Volkan Cevher (ICML, 2020)

Double-Loop Unadjusted Langevin Algorithm. - Paul Rolland; Armin Eftekhari; Ali Kavis; Volkan Cevher (ICML, 2020)

Conditional gradient methods for stochastically constrained convex minimization. - Maria-Luiza Vladarean; Ahmet Alacaoglu; Ya-Ping Hsieh; Volkan Cevher (ICML, 2020)

Robust Reinforcement Learning via Adversarial training with Langevin Dynamics. - Parameswaran Kamalaruban; Yu-Ting Huang 003; Ya-Ping Hsieh; Paul Rolland; Cheng Shi; Volkan Cevher (NeurIPS, 2020)

On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems. - Panayotis Mertikopoulos; Nadav Hallak; Ali Kavis; Volkan Cevher (NeurIPS, 2020)

Convergence of adaptive algorithms for weakly convex constrained optimization. - Ahmet Alacaoglu; Yura Malitsky; Volkan Cevher (CoRR, 2020)

Environment Shaping in Reinforcement Learning using State Abstraction. - Parameswaran Kamalaruban; Rati Devidze; Volkan Cevher; Adish Singla (CoRR, 2020)

Interaction-limited Inverse Reinforcement Learning. - Martin Troussard; Emmanuel Pignat; Parameswaran Kamalaruban; Sylvain Calinon; Volkan Cevher (CoRR, 2020)

Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections. - Junhong Lin; Volkan Cevher (J. Mach. Learn. Res., 2020)

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms. - Junhong Lin; Volkan Cevher (J. Mach. Learn. Res., 2020)

An adaptive primal-dual framework for nonsmooth convex minimization. - Quoc Tran-Dinh; Ahmet Alacaoglu; Olivier Fercoq; Volkan Cevher (Math. Program. Comput., 2020)

Machine Learning From Distributed, Streaming Data [From the Guest Editors]. - Waheed U. Bajwa; Volkan Cevher; Dimitris S. Papailiopoulos; Anna Scaglione (IEEE Signal Process. Mag., 2020)

Optimization for Reinforcement Learning: From a single agent to cooperative agents. - Donghwan Lee 002; Niao He; Parameswaran Kamalaruban; Volkan Cevher (IEEE Signal Process. Mag., 2020)

A 16-Channel Wireless Neural Recording System-on-Chip with CHT Feature Extraction Processor in 65nm CMOS. - Arda Uran; Kerim Türe; Cosimo Aprile; Alix Trouillet; Florian Fallegger; Azita Emami; Stéphanie P. Lacour; Catherine Dehollain; Yusuf Leblebici; Volkan Cevher (CICC, 2021)

A Plug-and-Play Deep Image Prior. - Zhaodong Sun; Fabian Latorre; Thomas Sanchez; Volkan Cevher (ICASSP, 2021)

Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach. - Nadav Hallak; Panayotis Mertikopoulos; Volkan Cevher (ICML, 2021)

The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets. - Ya-Ping Hsieh; Panayotis Mertikopoulos; Volkan Cevher (ICML, 2021)

Convergence of adaptive algorithms for constrained weakly convex optimization. - Ahmet Alacaoglu; Yura Malitsky; Volkan Cevher (NeurIPS, 2021)

Sifting through the noise: Universal first-order methods for stochastic variational inequalities. - Kimon Antonakopoulos; Thomas Pethick; Ali Kavis; Panayotis Mertikopoulos; Volkan Cevher (NeurIPS, 2021)

The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers. - Fabian Latorre; Leello Tadesse Dadi; Paul Rolland; Volkan Cevher (NeurIPS, 2021)

STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization. - Kfir Y. Levy; Ali Kavis; Volkan Cevher (NeurIPS, 2021)

Subquadratic Overparameterization for Shallow Neural Networks. - Chaehwan Song; Ali Ramezani-Kebrya; Thomas Pethick; Armin Eftekhari; Volkan Cevher (NeurIPS, 2021)

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch. - Luca Viano; Yu-Ting Huang 003; Parameswaran Kamalaruban; Adrian Weller; Volkan Cevher (NeurIPS, 2021)

A first-order primal-dual method with adaptivity to local smoothness. - Maria-Luiza Vladarean; Yura Malitsky; Volkan Cevher (NeurIPS, 2021)

Forward-reflected-backward method with variance reduction. - Ahmet Alacaoglu; Yura Malitsky; Volkan Cevher (Comput. Optim. Appl., 2021)

Self-Supervised Neural Architecture Search for Imbalanced Datasets. - Aleksandr Timofeev; Grigorios G. Chrysos; Volkan Cevher (CoRR, 2021)

STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization. - Kfir Y. Levy; Ali Kavis; Volkan Cevher (CoRR, 2021)

An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity. - Lijun Ding; Alp Yurtsever; Volkan Cevher; Joel A. Tropp; Madeleine Udell (SIAM J. Optim., 2021)

Scalable Semidefinite Programming. - Alp Yurtsever; Joel A. Tropp; Olivier Fercoq; Madeleine Udell; Volkan Cevher (SIAM J. Math. Data Sci., 2021)

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization. - Gideon Dresdner; Maria-Luiza Vladarean; Gunnar Rätsch; Francesco Locatello; Volkan Cevher; Alp Yurtsever (AISTATS, 2022)

The Spectral Bias of Polynomial Neural Networks. - Moulik Choraria; Leello Tadesse Dadi; Grigorios Chrysos 002; Julien Mairal; Volkan Cevher (ICLR, 2022)

High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize. - Ali Kavis; Kfir Yehuda Levy; Volkan Cevher (ICLR, 2022)

Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems. - Thomas Pethick; Puya Latafat; Panos Patrinos; Olivier Fercoq; Volkan Cevher (ICLR, 2022)

Controlling the Complexity and Lipschitz Constant improves Polynomial Nets. - Zhenyu Zhu; Fabian Latorre; Grigorios Chrysos 002; Volkan Cevher (ICLR, 2022)

A Natural Actor-Critic Framework for Zero-Sum Markov Games. - Ahmet Alacaoglu; Luca Viano; Niao He; Volkan Cevher (ICML, 2022)

UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees. - Kimon Antonakopoulos; Dong Quan Vu; Volkan Cevher; Kfir Y. Levy; Panayotis Mertikopoulos (ICML, 2022)

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models. - Paul Rolland; Volkan Cevher; Matthäus Kleindessner; Chris Russell 001; Dominik Janzing; Bernhard Schölkopf; Francesco Locatello (ICML, 2022)

On the Double Descent of Random Features Models Trained with SGD. - Fanghui Liu 001; Johan A. K. Suykens; Volkan Cevher (NeurIPS, 2022)

Understanding Deep Neural Function Approximation in Reinforcement Learning via $ epsilon$-Greedy Exploration. - Fanghui Liu 001; Luca Viano; Volkan Cevher (NeurIPS, 2022)

Sound and Complete Verification of Polynomial Networks. - Elías Abad-Rocamora; Mehmet Fatih Sahin; Fanghui Liu 001; Grigorios Chrysos 002; Volkan Cevher (NeurIPS, 2022)

Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods. - Kimon Antonakopoulos; Ali Kavis; Volkan Cevher (NeurIPS, 2022)

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation. - Yu-Guan Hsieh; Kimon Antonakopoulos; Volkan Cevher; Panayotis Mertikopoulos (NeurIPS, 2022)

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization. - Ali Kavis; Stratis Skoulakis; Kimon Antonakopoulos; Leello Tadesse Dadi; Volkan Cevher (NeurIPS, 2022)

Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning. - Paul Rolland; Luca Viano; Norman Schürhoff; Boris Nikolov; Volkan Cevher (NeurIPS, 2022)

Proximal Point Imitation Learning. - Luca Viano; Angeliki Kamoutsi; Gergely Neu; Igor Krawczuk; Volkan Cevher (NeurIPS, 2022)

Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study. - Yongtao Wu; Zhenyu Zhu; Fanghui Liu 001; Grigorios Chrysos 002; Volkan Cevher (NeurIPS, 2022)

Generalization Properties of NAS under Activation and Skip Connection Search. - Zhenyu Zhu; Fanghui Liu 001; Grigorios Chrysos 002; Volkan Cevher (NeurIPS, 2022)

Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization). - Zhenyu Zhu; Fanghui Liu 001; Grigorios Chrysos 002; Volkan Cevher (NeurIPS, 2022)

On the Complexity of a Practical Primal-Dual Coordinate Method. - Ahmet Alacaoglu; Volkan Cevher; Stephen J. Wright 001 (CoRR, 2022)

Learning in games from a stochastic approximation viewpoint. - Panayotis Mertikopoulos; Ya-Ping Hsieh; Volkan Cevher (CoRR, 2022)

Adversarial Audio Synthesis with Complex-valued Polynomial Networks. - Yongtao Wu; Grigorios G. Chrysos; Volkan Cevher (CoRR, 2022)

Understanding Deep Neural Function Approximation in Reinforcement Learning via ε-Greedy Exploration. - Fanghui Liu 001; Luca Viano; Volkan Cevher (CoRR, 2022)

A Newton Frank-Wolfe method for constrained self-concordant minimization. - Deyi Liu; Volkan Cevher; Quoc Tran-Dinh (J. Glob. Optim., 2022)

A 16-Channel Neural Recording System-on-Chip With CHT Feature Extraction Processor in 65-nm CMOS. - Arda Uran; Kerim Türe; Cosimo Aprile; Alix Trouillet; Florian Fallegger; Emilie C. M. Revol; Azita Emami; Stéphanie P. Lacour; Catherine Dehollain; Yusuf Leblebici; Volkan Cevher (IEEE J. Solid State Circuits, 2022)

On the Convergence of Stochastic Primal-Dual Hybrid Gradient. - Ahmet Alacaoglu; Olivier Fercoq; Volkan Cevher (SIAM J. Optim., 2022)

Evaluating the Fairness of Discriminative Foundation Models in Computer Vision. - Junaid Ali 001; Matthäus Kleindessner; Florian Wenzel; Kailash Budhathoki; Volkan Cevher; Chris Russell 001 (AIES, 2023)

Regularization of polynomial networks for image recognition. - Grigorios G. Chrysos; Bohan Wang; Jiankang Deng; Volkan Cevher (CVPR, 2023)

Finding Actual Descent Directions for Adversarial Training. - Fabian Latorre; Igor Krawczuk; Leello Tadesse Dadi; Thomas Pethick; Volkan Cevher (ICLR, 2023)

Solving stochastic weak Minty variational inequalities without increasing batch size. - Thomas Pethick; Olivier Fercoq; Puya Latafat; Panagiotis Patrinos; Volkan Cevher (ICLR, 2023)

Distributed Extra-gradient with Optimal Complexity and Communication Guarantees. - Ali Ramezani-Kebrya; Kimon Antonakopoulos; Igor Krawczuk; Justin Deschenaux; Volkan Cevher (ICLR, 2023)

DiGress: Discrete Denoising diffusion for graph generation. - Clément Vignac; Igor Krawczuk; Antoine Siraudin; Bohan Wang; Volkan Cevher; Pascal Frossard (ICLR, 2023)

What can online reinforcement learning with function approximation benefit from general coverage conditions? - Fanghui Liu 001; Luca Viano; Volkan Cevher (ICML, 2023)

Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees. - Ioannis Panageas; Stratis Skoulakis; Luca Viano; Xiao Wang 036; Volkan Cevher (ICML, 2023)

When do Minimax-fair Learning and Empirical Risk Minimization Coincide? - Harvineet Singh; Matthäus Kleindessner; Volkan Cevher; Rumi Chunara; Chris Russell 001 (ICML, 2023)

Benign Overfitting in Deep Neural Networks under Lazy Training. - Zhenyu Zhu; Fanghui Liu 001; Grigorios Chrysos 002; Francesco Locatello; Volkan Cevher (ICML, 2023)

Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks. - Jiayuan Ye 001; Zhenyu Zhu; Fanghui Liu 001; Reza Shokri; Volkan Cevher (NeurIPS, 2023)

Maximum Independent Set: Self-Training through Dynamic Programming. - Lorenzo Brusca; Lars C. P. M. Quaedvlieg; Stratis Skoulakis; Grigorios Chrysos 002; Volkan Cevher (NeurIPS, 2023)

Alternation makes the adversary weaker in two-player games. - Volkan Cevher; Ashok Cutkosky; Ali Kavis; Georgios Piliouras; Stratis Skoulakis; Luca Viano (NeurIPS, 2023)

Efficient Online Clustering with Moving Costs. - Dimitris Christou; Stratis Skoulakis; Volkan Cevher (NeurIPS, 2023)

Exponential Lower Bounds for Fictitious Play in Potential Games. - Ioannis Panageas; Nikolas Patris; Stratis Skoulakis; Volkan Cevher (NeurIPS, 2023)

Stable Nonconvex-Nonconcave Training via Linear Interpolation. - Thomas Pethick; Wanyun Xie; Volkan Cevher (NeurIPS, 2023)

On the Convergence of Encoder-only Shallow Transformers. - Yongtao Wu; Fanghui Liu 001; Grigorios Chrysos 002; Volkan Cevher (NeurIPS, 2023)

Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling. - Zhenyu Zhu; Francesco Locatello; Volkan Cevher (NeurIPS, 2023)

Min-Max Optimization Made Simple: Approximating the Proximal Point Method via Contraction Maps. - Volkan Cevher; Georgios Piliouras; Ryann Sim; Stratis Skoulakis (SOSA, 2023)

Provable benefits of general coverage conditions in efficient online RL with function approximation. - Fanghui Liu 001; Luca Viano; Volkan Cevher (CoRR, 2023)

Revisiting adversarial training for the worst-performing class. - Thomas Pethick; Grigorios Chrysos 002; Volkan Cevher (Trans. Mach. Learn. Res., 2023)

Federated Learning under Covariate Shifts with Generalization Guarantees. - Ali Ramezani-Kebrya; Fanghui Liu 001; Thomas Pethick; Grigorios Chrysos 002; Volkan Cevher (Trans. Mach. Learn. Res., 2023)

Extreme Miscalibration and the Illusion of Adversarial Robustness. - Vyas Raina; Samson Tan; Volkan Cevher; Aditya Rawal; Sheng Zha; George Karypis (ACL (1), 2024)

Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate. - Ruichen Jiang; Parameswaran Raman; Shoham Sabach; Aryan Mokhtari; Mingyi Hong 001; Volkan Cevher (AISTATS, 2024)

Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning. - Soumajyoti Sarkar; Leonard Lausen; Volkan Cevher; Thomas Brox; Sheng Zha; George Karypis (ENLSP, 2024)

Efficient local linearity regularization to overcome catastrophic overfitting. - Elías Abad-Rocamora; Fanghui Liu 001; Grigorios Chrysos 002; Pablo M. Olmos; Volkan Cevher (ICLR, 2024)

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness. - Artem Agafonov; Dmitry Kamzolov; Alexander V. Gasnikov; Ali Kavis; Kimon Antonakopoulos; Volkan Cevher; Martin Takác 001 (ICLR, 2024)

Generalization of Scaled Deep ResNets in the Mean-Field Regime. - Yihang Chen; Fanghui Liu 001; Yiping Lu; Grigorios Chrysos 002; Volkan Cevher (ICLR, 2024)

Multilinear Operator Networks. - Yixin Cheng; Grigorios Chrysos 002; Markos Georgopoulos; Volkan Cevher (ICLR, 2024)

Efficient Continual Finite-Sum Minimization. - Ioannis Mavrothalassitis; Stratis Skoulakis; Leello Tadesse Dadi; Volkan Cevher (ICLR, 2024)

Adversarial Training Should Be Cast as a Non-Zero-Sum Game. - Alexander Robey; Fabian Latorre; George J. Pappas; Hamed Hassani; Volkan Cevher (ICLR, 2024)

Robust NAS under adversarial training: benchmark, theory, and beyond. - Yongtao Wu; Fanghui Liu 001; Carl-Johann Simon-Gabriel; Grigorios Chrysos 002; Volkan Cevher (ICLR, 2024)

Revisiting Character-level Adversarial Attacks for Language Models. - Elías Abad-Rocamora; Yongtao Wu; Fanghui Liu 001; Grigorios Chrysos 002; Volkan Cevher (ICML, 2024)

REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates. - Arshia Afzal; Grigorios Chrysos 002; Volkan Cevher; Mahsa Shoaran (ICML, 2024)

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization. - Yihang Chen; Fanghui Liu 001; Taiji Suzuki; Volkan Cevher (ICML, 2024)

Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations. - Justin Deschenaux; Igor Krawczuk; Grigorios Chrysos 002; Volkan Cevher (ICML, 2024)

Truly No-Regret Learning in Constrained MDPs. - Adrian Müller 002; Pragnya Alatur; Volkan Cevher; Giorgia Ramponi; Niao He (ICML, 2024)

MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent. - Kaan Ozkara; Can Karakus; Parameswaran Raman; Mingyi Hong 001; Shoham Sabach; Branislav Kveton; Volkan Cevher (ICML, 2024)

Learning to Remove Cuts in Integer Linear Programming. - Pol Puigdemont; Stratis Skoulakis; Grigorios Chrysos 002; Volkan Cevher (ICML, 2024)

Universal Gradient Methods for Stochastic Convex Optimization. - Anton Rodomanov; Ali Kavis; Yongtao Wu; Kimon Antonakopoulos; Volkan Cevher (ICML, 2024)

Imitation Learning in Discounted Linear MDPs without exploration assumptions. - Luca Viano; Stratis Skoulakis; Volkan Cevher (ICML, 2024)

Improving SAM Requires Rethinking its Optimization Formulation. - Wanyun Xie; Fabian Latorre; Kimon Antonakopoulos; Thomas Pethick; Volkan Cevher (ICML, 2024)

Inference Optimization of Foundation Models on AI Accelerators. - Youngsuk Park; Kailash Budhathoki; Liangfu Chen; Jonas M. Kübler; Jiaji Huang; Matthäus Kleindessner; Jun Huan; Volkan Cevher; Yida Wang 003; George Karypis (KDD, 2024)

μP2: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling. - Moritz Haas; Jin Xu; Volkan Cevher; Leena Chennuru Vankadara (NeurIPS, 2024)

Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces. - Angeliki Kamoutsi; Peter Schmitt-Förster; Tobias Sutter; Volkan Cevher; John Lygeros (NeurIPS, 2024)

Membership Inference Attacks against Large Vision-Language Models. - Zhan Li; Yongtao Wu; Yihang Chen; Francesco Tonin; Elías Abad-Rocamora; Volkan Cevher (NeurIPS, 2024)

On Feature Learning in Structured State Space Models. - Leena Chennuru Vankadara; Jin Xu; Moritz Haas; Volkan Cevher (NeurIPS, 2024)

SAMPa: Sharpness-aware Minimization Parallelized. - Wanyun Xie; Thomas Pethick; Volkan Cevher (NeurIPS, 2024)

Polynomial Convergence of Bandit No-Regret Dynamics in Congestion Games. - Leello Tadesse Dadi; Ioannis Panageas; Stratis Skoulakis; Luca Viano; Volkan Cevher (CoRR, 2024)

Leveraging the Context through Multi-Round Interactions for Jailbreaking Attacks. - Yixin Cheng; Markos Georgopoulos; Volkan Cevher; Grigorios G. Chrysos (CoRR, 2024)

Revisiting character-level adversarial attacks. - Elías Abad-Rocamora; Yongtao Wu; Fanghui Liu 001; Grigorios G. Chrysos; Volkan Cevher (CoRR, 2024)

HeNCler: Node Clustering in Heterophilous Graphs through Learned Asymmetric Similarity. - Sonny Achten; Francesco Tonin; Volkan Cevher; Johan A. K. Suykens (CoRR, 2024)

Going beyond compositional generalization, DDPMs can produce zero-shot interpolation. - Justin Deschenaux; Igor Krawczuk; Grigorios Chrysos 002; Volkan Cevher (CoRR, 2024)

Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants. - Beatriz Borges; Negar Foroutan; Deniz Bayazit; Anna Sotnikova; Syrielle Montariol; Tanya Nazaretzky; Mohammadreza Banaei; Alireza Sakhaeirad; Philippe Servant; Seyed Parsa Neshaei; Jibril Frej; Angelika Romanou; et al. (CoRR, 2024)

μ P2: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling. - Moritz Haas; Jin Xu; Volkan Cevher; Leena Chennuru Vankadara (CoRR, 2024)

The Last Mile to Supervised Performance: Semi-Supervised Domain Adaptation for Semantic Segmentation. - Daniel Morales-Brotons; Grigorios Chrysos 002; Stratis Tzoumas; Volkan Cevher (CoRR, 2024)

Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks. - Fanghui Liu 001; Leello Tadesse Dadi; Volkan Cevher (J. Mach. Learn. Res., 2024)

On the Generalization of Stochastic Gradient Descent with Momentum. - Ali Ramezani-Kebrya; Kimon Antonakopoulos; Volkan Cevher; Ashish Khisti; Ben Liang 001 (J. Mach. Learn. Res., 2024)

Mixed Nash for Robust Federated Learning. - Wanyun Xie; Thomas Pethick; Ali Ramezani-Kebrya; Volkan Cevher (Trans. Mach. Learn. Res., 2024)

A unified stochastic approximation framework for learning in games. - Panayotis Mertikopoulos; Ya-Ping Hsieh; Volkan Cevher (Math. Program., 2024)

Certified Robustness Under Bounded Levenshtein Distance. - Elías Abad-Rocamora; Grigorios Chrysos 002; Volkan Cevher (ICLR, 2025)

Adversarial Training for Defense Against Label Poisoning Attacks. - Melis Ilayda Bal; Volkan Cevher; Michael Muehlebach (ICLR, 2025)

Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling. - Aram Davtyan; Leello Tadesse Dadi; Volkan Cevher; Paolo Favaro (ICLR, 2025)

Quantum-PEFT: Ultra parameter-efficient fine-tuning. - Toshiaki Koike-Akino; Francesco Tonin; Yongtao Wu; Frank Zhengqing Wu; Leyla Naz Candogan; Volkan Cevher (ICLR, 2025)

Efficient Interpolation between Extragradient and Proximal Methods for Weak MVIs. - Thomas Pethick; Ioannis Mavrothalassitis; Volkan Cevher (ICLR, 2025)

Addressing Label Shift in Distributed Learning via Entropy Regularization​. - Zhiyuan Wu; Changkyu Choi; Xiangcheng Cao; Volkan Cevher; Ali Ramezani-Kebrya (ICLR, 2025)

How Gradient descent balances features: A dynamical analysis for two-layer neural networks. - Zhenyu Zhu; Fanghui Liu 001; Volkan Cevher (ICLR, 2025)

Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate. - Xiaomeng Jin; Zhiqi Bu; Bhanukiran Vinzamuri; Anil Ramakrishna; Kai-Wei Chang; Volkan Cevher; Mingyi Hong 001 (NAACL (Long Papers), 2025)

Single-pass Detection of Jailbreaking Input in Large Language Models. - Leyla Naz Candogan; Yongtao Wu; Elías Abad-Rocamora; Grigorios Chrysos 002; Volkan Cevher (Trans. Mach. Learn. Res., 2025)

A Proximal Operator for Inducing 2:4-Sparsity. - Jonas M. Kübler; Yu-Xiang Wang 003; Shoham Sabach; Navid Ansari; Matthäus Kleindessner; Kailash Budhathoki; Volkan Cevher; George Karypis (Trans. Mach. Learn. Res., 2025)

νSAM: Memory-Efficient Sharpness-Aware Minimization via Nuclear Norm Constraints. - Thomas Pethick; Parameswaran Raman; Lenon Minorics; Mingyi Hong 001; Shoham Sabach; Volkan Cevher (Trans. Mach. Learn. Res., 2025)

Training Deep Learning Models with Norm-Constrained LMOs. - Thomas Pethick; Wanyun Xie; Kimon Antonakopoulos; Zhenyu Zhu; Antonio Silveti-Falls; Volkan Cevher (CoRR, 2025)

Best of Both Worlds: Regret Minimization versus Minimax Play. - Adrian Müller 002; Jon Schneider; Stratis Skoulakis; Luca Viano; Volkan Cevher (CoRR, 2025)

Multi-Step Alignment as Markov Games: An Optimistic Online Gradient Descent Approach with Convergence Guarantees. - Yongtao Wu; Luca Viano; Yihang Chen; Zhenyu Zhu; Kimon Antonakopoulos; Quanquan Gu; Volkan Cevher (CoRR, 2025)

LUME: LLM Unlearning with Multitask Evaluations. - Anil Ramakrishna; Yixin Wan; Xiaomeng Jin; Kai-Wei Chang; Zhiqi Bu; Bhanukiran Vinzamuri; Volkan Cevher; Mingyi Hong 001; Rahul Gupta 001 (CoRR, 2025)

Linear Attention for Efficient Bidirectional Sequence Modeling. - Arshia Afzal; Elías Abad-Rocamora; Leyla Naz Candogan; Pol Puigdemont; Francesco Tonin; Yongtao Wu; Mahsa Shoaran; Volkan Cevher (CoRR, 2025)

IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic. - Stefano Viel; Luca Viano; Volkan Cevher (CoRR, 2025)

MT-NAM: An Efficient and Adaptive Model for Epileptic Seizure Detection. - Arshia Afzal; Volkan Cevher; Mahsa Shoaran (CoRR, 2025)

SemEval-2025 Task 4: Unlearning sensitive content from Large Language Models. - Anil Ramakrishna; Yixin Wan; Xiaomeng Jin; Kai-Wei Chang; Zhiqi Bu; Bhanukiran Vinzamuri; Volkan Cevher; Mingyi Hong 001; Rahul Gupta 001 (CoRR, 2025)

Layer-wise Quantization for Quantized Optimistic Dual Averaging. - Anh Duc Nguyen; Ilia Markov; Frank Zhengqing Wu; Ali Ramezani-Kebrya; Kimon Antonakopoulos; Dan Alistarh; Volkan Cevher (CoRR, 2025)

Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning. - Till Freihaut; Luca Viano; Volkan Cevher; Matthieu Geist; Giorgia Ramponi (CoRR, 2025)

Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games. - Yi Feng; Kaito Fujii; Stratis Skoulakis; Xiao Wang 036; Volkan Cevher (CoRR, 2025)

ESLM: Risk-Averse Selective Language Modeling for Efficient Pretraining. - Melis Ilayda Bal; Volkan Cevher; Michael Muehlebach (CoRR, 2025)

Efficient Large Language Model Inference with Neural Block Linearization. - Mete Erdogan; Francesco Tonin; Volkan Cevher (CoRR, 2025)

Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning. - Wanyun Xie; Francesco Tonin; Volkan Cevher (CoRR, 2025)

Not Every Token Needs Forgetting: Selective Unlearning to Limit Change in Utility in Large Language Model Unlearning. - Yixin Wan; Anil Ramakrishna; Kai-Wei Chang; Volkan Cevher; Rahul Gupta 001 (CoRR, 2025)

Generalized Gradient Norm Clipping & Non-Euclidean (L0,L1)-Smoothness. - Thomas Pethick; Wanyun Xie; Mete Erdogan; Kimon Antonakopoulos; Tony Silveti-Falls; Volkan Cevher (CoRR, 2025)

Robustness in Both Domains: CLIP Needs a Robust Text Encoder. - Elías Abad-Rocamora; Christian Schlarmann; Naman Deep Singh; Yongtao Wu; Matthias Hein 001; Volkan Cevher (CoRR, 2025)

DiffCAP: Diffusion-based Cumulative Adversarial Purification for Vision Language Models. - Jia Fu 001; Yongtao Wu; Yihang Chen; Kunyu Peng; Xiao Zhang; Volkan Cevher; Sepideh Pashami; Anders Holst (CoRR, 2025)

Accelerating Spectral Clustering under Fairness Constraints. - Francesco Tonin; Alex Lambert; Johan A. K. Suykens; Volkan Cevher (CoRR, 2025)

BLUR: A Bi-Level Optimization Approach for LLM Unlearning. - Hadi Reisizadeh; Jinghan Jia; Zhiqi Bu; Bhanukiran Vinzamuri; Anil Ramakrishna; Kai-Wei Chang; Volkan Cevher; Sijia Liu 001; Mingyi Hong 001 (CoRR, 2025)

Hadamard Product in Deep Learning: Introduction, Advances and Challenges. - Grigorios G. Chrysos; Yongtao Wu; Razvan Pascanu; Philip H. S. Torr; Volkan Cevher (IEEE Trans. Pattern Anal. Mach. Intell., 2025)