Fading observation alignment via feedback. - Anand D. Sarwate; Michael Gastpar (IPSN, 2005)

Geographic gossip: efficient aggregation for sensor networks. - Alexandros G. Dimakis; Anand D. Sarwate; Martin J. Wainwright (IPSN, 2006)

Randomization bounds on Gaussian arbitrarily varying channels. - Anand D. Sarwate; Michael Gastpar (ISIT, 2006)

Exact emulation of a priority queue with a switch and delay lines. - Anand D. Sarwate; Venkat Anantharam (Queueing Syst. Theory Appl., 2006)

Using zero-rate feedback on binary additive channels with individual noise sequences. - Krishnan Eswaran; Anand D. Sarwate; Anant Sahai; Michael Gastpar (ISIT, 2007)

Channels with nosy "noise". - Anand D. Sarwate; Michael Gastpar (ISIT, 2007)

Limited feedback achieves the empirical capacity - Krishnan Eswaran; Anand D. Sarwate; Anant Sahai; Michael Gastpar (CoRR, 2007)

Rateless coding with partial state information at the decoder - Anand D. Sarwate; Michael Gastpar (CoRR, 2007)

Deterministic list codes for state-constrained arbitrarily varying channels - Anand D. Sarwate; Michael Gastpar (CoRR, 2007)

Broadcast gossip algorithms: Design and analysis for consensus. - Tuncer C. Aysal; Mehmet E. Yildiz; Anand D. Sarwate; Anna Scaglione (CDC, 2008)

Adversarial interference models for multiantenna cooperative systems. - Anand D. Sarwate; Michael Gastpar (CISS, 2008)

Arbitrarily dirty paper coding and applications. - Anand D. Sarwate; Michael Gastpar (ISIT, 2008)

Geographic Gossip: Efficient Averaging for Sensor Networks. - Alexandros G. Dimakis; Anand D. Sarwate; Martin J. Wainwright (IEEE Trans. Signal Process., 2008)

Reaching consensus in wireless networks with probabilistic broadcast. - Tuncer C. Aysal; Anand D. Sarwate; Alexandros G. Dimakis (Allerton, 2009)

Some observations on limited feedback for multiaccess channels. - Anand D. Sarwate; Michael Gastpar (ISIT, 2009)

Differentially Private Support Vector Machines - Anand D. Sarwate; Kamalika Chaudhuri; Claire Monteleoni (CoRR, 2009)

Broadcast gossip algorithms for consensus. - Tuncer C. Aysal; Mehmet E. Yildiz; Anand D. Sarwate; Anna Scaglione (IEEE Trans. Signal Process., 2009)

Redundancy of exchangeable estimators. - Narayana P. Santhanam; Mokshay M. Madiman; Anand D. Sarwate (Allerton, 2010)

Linear strategies for the Gaussian MAC with user cooperation. - Michèle A. Wigger; Anand D. Sarwate (Allerton, 2010)

Coding against delayed adversaries. - Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate (ISIT, 2010)

Coding against myopic adversaries. - Anand D. Sarwate (ITW, 2010)

Single-Ballot Risk-Limiting Audits Using Convex Optimization. - Stephen Checkoway; Anand D. Sarwate (EVT/WOTE, 2010)

A little feedback can simplify sensor network cooperation. - Anand D. Sarwate; Michael Gastpar (IEEE J. Sel. Areas Commun., 2010)

Zero-rate feedback can achieve the empirical capacity. - Krishnan Eswaran; Anand D. Sarwate; Anant Sahai; Michael Gastpar (IEEE Trans. Inf. Theory, 2010)

Rateless codes for AVC models. - Anand D. Sarwate; Michael Gastpar (IEEE Trans. Inf. Theory, 2010)

Opinion dynamics and distributed learning of distributions. - Anand D. Sarwate; Tara Javidi (Allerton, 2011)

Differentially Private Empirical Risk Minimization. - Kamalika Chaudhuri; Claire Monteleoni; Anand D. Sarwate (J. Mach. Learn. Res., 2011)

Merging opinions by social sampling of posteriors. - Anand D. Sarwate (Allerton Conference, 2012)

Distributed learning from social sampling. - Anand D. Sarwate; Tara Javidi (CISS, 2012)

Improved upper bounds on the capacity of binary channels with causal adversaries. - Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate (ISIT, 2012)

Near-optimal Differentially Private Principal Components. - Kamalika Chaudhuri; Anand D. Sarwate; Kaushik Sinha (NIPS, 2012)

Near-Optimal Algorithms for Differentially-Private Principal Components - Kamalika Chaudhuri; Anand D. Sarwate; Kaushik Sinha (CoRR, 2012)

Relaxing the Gaussian AVC - Anand D. Sarwate; Michael Gastpar (CoRR, 2012)

Protecting count queries in study design. - Staal Amund Vinterbo; Anand D. Sarwate; Aziz A. Boxwala (J. Am. Medical Informatics Assoc., 2012)

The Impact of Mobility on Gossip Algorithms. - Anand D. Sarwate; Alexandros G. Dimakis (IEEE Trans. Inf. Theory, 2012)

List-Decoding for the Arbitrarily Varying Channel Under State Constraints. - Anand D. Sarwate; Michael Gastpar (IEEE Trans. Inf. Theory, 2012)

Stochastic gradient descent with differentially private updates. - Shuang Song 001; Kamalika Chaudhuri; Anand D. Sarwate (GlobalSIP, 2013)

Assisted sampling of correlated sources. - Vinod M. Prabhakaran; Anand D. Sarwate (ISIT, 2013)

Auditing: Active Learning with Outcome-Dependent Query Costs. - Sivan Sabato; Anand D. Sarwate; Nati Srebro (NIPS, 2013)

A near-optimal algorithm for differentially-private principal components. - Kamalika Chaudhuri; Anand D. Sarwate; Kaushik Sinha (J. Mach. Learn. Res., 2013)

Signal Processing and Machine Learning with Differential Privacy: Algorithms and Challenges for Continuous Data. - Anand D. Sarwate; Kamalika Chaudhuri (IEEE Signal Process. Mag., 2013)

Upper Bounds on the Capacity of Binary Channels With Causal Adversaries. - Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate (IEEE Trans. Inf. Theory, 2013)

A rate-disortion perspective on local differential privacy. - Anand D. Sarwate; Lalitha Sankar (Allerton, 2014)

On Measure Concentration of Random Maximum A-Posteriori Perturbations. - Francesco Orabona; Tamir Hazan; Anand D. Sarwate; Tommi S. Jaakkola (ICML, 2014)

Tradeoffs for task parallelization in distributed optimization. - Konstantinos I. Tsianos; Anand D. Sarwate; Michael G. Rabbat (MLSP, 2014)

Redundancy of Exchangeable Estimators. - Narayana P. Santhanam; Anand D. Sarwate; Jae Oh Woo (Entropy, 2014)

Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation. - Anand D. Sarwate; Sergey M. Plis; Jessica A. Turner; Mohammad Arbabshirani; Vince D. Calhoun (Frontiers Neuroinformatics, 2014)

Generalized opinion dynamics from local optimization rules. - Avhishek Chatterjee; Anand D. Sarwate; Sriram Vishwanath (ACSSC, 2015)

Learning from Data with Heterogeneous Noise using SGD. - Shuang Song 001; Kamalika Chaudhuri; Anand D. Sarwate (AISTATS, 2015)

Distributed proportional stochastic coordinate descent with social sampling. - Mohsen Ghassemi; Anand D. Sarwate (Allerton, 2015)

Incentive Schemes for Privacy-Sensitive Consumers. - Chong Huang; Lalitha Sankar; Anand D. Sarwate (GameSec, 2015)

Large scale collaboration with autonomy: Decentralized data ICA. - Bradley T. Baker; Rogers F. Silva; Vince D. Calhoun; Anand D. Sarwate; Sergey M. Plis (MLSP, 2015)

Designing Incentive Schemes for Privacy-Sensitive Users. - Chong Huang; Lalitha Sankar; Anand D. Sarwate (J. Priv. Confidentiality, 2015)

Distributed Learning of Distributions via Social Sampling. - Anand D. Sarwate; Tara Javidi (IEEE Trans. Autom. Control., 2015)

Data-dependent bounds on network gradient descent. - Avleen Singh Bijral; Anand D. Sarwate; Nathan Srebro (Allerton, 2016)

Differentially Private Online Active Learning with Applications to Anomaly Detection. - Mohsen Ghassemi; Anand D. Sarwate; Rebecca N. Wright (AISec@CCS, 2016)

Privacy-preserving source separation for distributed data using independent component analysis. - Hafiz Imtiaz; Rogers F. Silva; Bradley T. Baker; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (CISS, 2016)

Analysis of a privacy-preserving PCA algorithm using random matrix theory. - Lu Wei 001; Anand D. Sarwate; Jukka Corander; Alfred O. Hero III; Vahid Tarokh (GlobalSIP, 2016)

Symmetric matrix perturbation for differentially-private principal component analysis. - Hafiz Imtiaz; Anand D. Sarwate (ICASSP, 2016)

Data-weighted ensemble learning for privacy-preserving distributed learning. - Liyang Xie; Sergey M. Plis; Anand D. Sarwate (ICASSP, 2016)

Randomized requantization with local differential privacy. - Sijie Xiong; Anand D. Sarwate; Narayan B. Mandayam (ICASSP, 2016)

A bit of delay is sufficient and stochastic encoding is necessary to overcome online adversarial erasures. - Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate (ISIT, 2016)

Optimal differential privacy mechanisms under Hamming distortion for structured source classes. - Kousha Kalantari; Lalitha Sankar; Anand D. Sarwate (ISIT, 2016)

Minimax lower bounds for Kronecker-structured dictionary learning. - Zahra Shakeri; Waheed Uz Zaman Bajwa; Anand D. Sarwate (ISIT, 2016)

The benefit of a 1-bit jump-start, and the necessity of stochastic encoding, in jamming channels. - Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate (CoRR, 2016)

The Optimal Differential Privacy Mechanism under Hamming Distortion for Universal Memoryless Source Classes. - Kousha Kalantari; Lalitha Sankar; Anand D. Sarwate (CoRR, 2016)

STARK: Structured dictionary learning through rank-one tensor recovery. - Mohsen Ghassemi; Zahra Shakeri; Anand D. Sarwate; Waheed U. Bajwa (CAMSAP, 2017)

Identification of kronecker-structured dictionaries: An asymptotic analysis. - Zahra Shakeri; Anand D. Sarwate; Waheed U. Bajwa (CAMSAP, 2017)

Differentially Private Noisy Search with Applications to Anomaly Detection (Abstract). - Daniel M. Bittner; Anand D. Sarwate; Rebecca N. Wright (AISec@CCS, 2017)

A Unified Optimization Approach for Sparse Tensor Operations on GPUs. - Bangtian Liu; Chengyao Wen; Anand D. Sarwate; Maryam Mehri Dehnavi (CLUSTER, 2017)

Differentially-private canonical correlation analysis. - Hafiz Imtiaz; Anand D. Sarwate (GlobalSIP, 2017)

Sample complexity bounds for dictionary learning of tensor data. - Zahra Shakeri; Waheed U. Bajwa; Anand D. Sarwate (ICASSP, 2017)

Decentralized independent vector analysis. - Nikolas P. Wojtalewicz; Rogers F. Silva; Vince D. Calhoun; Anand D. Sarwate; Sergey M. Plis (ICASSP, 2017)

COINSTAC: Decentralizing the future of brain imaging analysis. - Jing Ming; Eric Verner; Anand D. Sarwate; Ross Kelly; Cory Reed; Torran Kahleck; Rogers F. Silva; Sandeep R. Panta; Jessica A. Turner; Sergey M. Plis; Vince D. Calhoun (F1000Research, 2017)

Data-Dependent Convergence for Consensus Stochastic Optimization. - Avleen Singh Bijral; Anand D. Sarwate; Nathan Srebro (IEEE Trans. Autom. Control., 2017)

Using Noisy Binary Search for Differentially Private Anomaly Detection. - Daniel M. Bittner; Anand D. Sarwate; Rebecca N. Wright (CSCML, 2018)

Global Optimality in Inductive Matrix Completion. - Mohsen Ghassemi; Anand D. Sarwate; Naveen Goela (ICASSP, 2018)

Improved Algorithms for Differentially Private Orthogonal Tensor Decomposition. - Hafiz Imtiaz; Anand D. Sarwate (ICASSP, 2018)

Differentially Private Distributed Principal Component Analysis. - Hafiz Imtiaz; Anand D. Sarwate (ICASSP, 2018)

Defending Against Packet-Size Side-Channel Attacks in Iot Networks. - Sijie Xiong; Anand D. Sarwate; Narayan B. Mandayam (ICASSP, 2018)

Coordination Using Individually Shared Randomness. - Gowtham R. Kurri; Vinod M. Prabhakaran; Anand D. Sarwate (ISIT, 2018)

Quadratically Constrained Channels with Causal Adversaries. - Tongxin Li; Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate (ISIT, 2018)

Predictive Learning on Sign-Valued Hidden Markov Trees. - Konstantinos E. Nikolakakis; Dionysios S. Kalogerias; Anand D. Sarwate (CoRR, 2018)

Distributed Differentially Private Algorithms for Matrix and Tensor Factorization. - Hafiz Imtiaz; Anand D. Sarwate (IEEE J. Sel. Top. Signal Process., 2018)

Identifiability of Kronecker-Structured Dictionaries for Tensor Data. - Zahra Shakeri; Anand D. Sarwate; Waheed U. Bajwa (IEEE J. Sel. Top. Signal Process., 2018)

Robust Privacy-Utility Tradeoffs Under Differential Privacy and Hamming Distortion. - Kousha Kalantari; Lalitha Sankar; Anand D. Sarwate (IEEE Trans. Inf. Forensics Secur., 2018)

Social Learning and Distributed Hypothesis Testing. - Anusha Lalitha; Tara Javidi; Anand D. Sarwate (IEEE Trans. Inf. Theory, 2018)

Minimax Lower Bounds on Dictionary Learning for Tensor Data. - Zahra Shakeri; Waheed U. Bajwa; Anand D. Sarwate (IEEE Trans. Inf. Theory, 2018)

Learning Tree Structures from Noisy Data. - Konstantinos E. Nikolakakis; Dionysios S. Kalogerias; Anand D. Sarwate (AISTATS, 2019)

Distributed Differentially-private Canonical Correlation Analysis. - Hafiz Imtiaz; Anand D. Sarwate (ICASSP, 2019)

The Interplay of Causality and Myopia in Adversarial Channel Models. - Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate; Carol Wang (ISIT, 2019)

Sample Complexity Bounds for Low-Separation-Rank Dictionary Learning. - Mohsen Ghassemi; Zahra Shakeri; Waheed U. Bajwa; Anand D. Sarwate (ISIT, 2019)

Distributed Differentially Private Computation of Functions with Correlated Noise. - Hafiz Imtiaz; Jafar Mohammadi; Anand D. Sarwate (CoRR, 2019)

Non-Parametric Structure Learning on Hidden Tree-Shaped Distributions. - Konstantinos E. Nikolakakis; Dionysios S. Kalogerias; Anand D. Sarwate (CoRR, 2019)

Improved Differentially Private Decentralized Source Separation for fMRI Data. - Hafiz Imtiaz; Jafar Mohammadi; Rogers F. Silva; Bradley T. Baker; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (CoRR, 2019)

Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings. - Bradley T. Baker; Anees Abrol; Rogers F. Silva; Eswar Damaraju; Anand D. Sarwate; Vince D. Calhoun; Sergey M. Plis (NeuroImage, 2019)

High Dimensional Inference With Random Maximum A-Posteriori Perturbations. - Tamir Hazan; Francesco Orabona; Anand D. Sarwate; Subhransu Maji; Tommi S. Jaakkola (IEEE Trans. Inf. Theory, 2019)

Symmetrizability for Myopic AVCs. - Amitalok J. Budkuley; Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate; Carol Wang (ISIT, 2020)

Best-Arm Identification for Quantile Bandits with Privacy. - Dionysios S. Kalogerias; Konstantinos E. Nikolakakis; Anand D. Sarwate; Or Sheffet (CoRR, 2020)

COINSTAC: Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation. - Harshvardhan Gazula; Ross Kelly; Javier Tomas Romero; Eric Verner; Bradley T. Baker; Rogers F. Silva; Hafiz Imtiaz; Debbrata K. Saha; Rajikha Raja; Jessica A. Turner; Anand D. Sarwate; Sergey M. Plis; et al. (J. Open Source Softw., 2020)

Understanding Privacy-Utility Tradeoffs in Differentially Private Online Active Learning. - Daniel M. Bittner; Alejandro E. Brito; Mohsen Ghassemi; Shantanu Rane; Anand D. Sarwate; Rebecca N. Wright (J. Priv. Confidentiality, 2020)

Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and Algorithms. - Mohsen Ghassemi; Zahra Shakeri; Anand D. Sarwate; Waheed U. Bajwa (IEEE Trans. Signal Process., 2020)

A Minimax Lower Bound for Low-Rank Matrix-Variate Logistic Regression. - Batoul Taki; Mohsen Ghassemi; Anand D. Sarwate; Waheed U. Bajwa (ACSCC, 2021)

Influencers and the Giant Component: The Fundamental Hardness in Privacy Protection for Socially Contagious Attributes. - Aria Rezaei; Jie Gao 001; Anand D. Sarwate (SDM, 2021)

Predictive Learning on Hidden Tree-Structured Ising Models. - Konstantinos E. Nikolakakis; Dionysios S. Kalogerias; Anand D. Sarwate (J. Mach. Learn. Res., 2021)

Quantile Multi-Armed Bandits: Optimal Best-Arm Identification and a Differentially Private Scheme. - Konstantinos E. Nikolakakis; Dionysios S. Kalogerias; Or Sheffet; Anand D. Sarwate (IEEE J. Sel. Areas Inf. Theory, 2021)

Decentralized Multisite VBM Analysis During Adolescence Shows Structural Changes Linked to Age, Body Mass Index, and Smoking: a COINSTAC Analysis. - Harshvardhan Gazula; Bharath Holla; Zuo Zhang; Jiayuan Xu; Eric Verner; Ross Kelly; Sanjeev Jain; Rose Dawn Bharath; Gareth J. Barker; Debasish Basu; Amit Chakrabarti; Kartik Kalyanram; et al. (Neuroinformatics, 2021)

Coordination Through Shared Randomness. - Gowtham R. Kurri; Vinod M. Prabhakaran; Anand D. Sarwate (IEEE Trans. Inf. Theory, 2021)

A Correlated Noise-Assisted Decentralized Differentially Private Estimation Protocol, and its Application to fMRI Source Separation. - Hafiz Imtiaz; Jafar Mohammadi; Rogers F. Silva; Bradley T. Baker; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (IEEE Trans. Signal Process., 2021)

Low-Rank Phase Retrieval with Structured Tensor Models. - Soo Min Kwon; Xin Li; Anand D. Sarwate (ICASSP, 2022)

Privacy Leakage in Discrete-Time Updating Systems. - Nitya Sathyavageeswaran; Roy D. Yates; Anand D. Sarwate; Narayan B. Mandayam (ISIT, 2022)

The Capacity of Causal Adversarial Channels. - Yihan Zhang 001; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate (ISIT, 2022)

Privid: Practical, Privacy-Preserving Video Analytics Queries. - Frank Cangialosi; Neil Agarwal; Venkat Arun; Junchen Jiang; Srinivas Narayana; Anand D. Sarwate; Ravi Netravali (NSDI, 2022)

TorchNTK: A Library for Calculation of Neural Tangent Kernels of PyTorch Models. - Andrew Engel; Zhichao Wang; Anand D. Sarwate; Sutanay Choudhury; Tony Chiang (CoRR, 2022)

Privacy Leakage in Discrete Time Updating Systems. - Nitya Sathyavageesran; Roy D. Yates; Anand D. Sarwate; Narayan B. Mandayam (CoRR, 2022)

Decentralized Brain Age Estimation Using MRI Data. - Sunitha Basodi; Rajikha Raja; Bhaskar Ray; Harshvardhan Gazula; Anand D. Sarwate; Sergey M. Plis; Jingyu Liu 001; Eric Verner; Vince D. Calhoun (Neuroinformatics, 2022)

Federated Analysis of Neuroimaging Data: A Review of the Field. - Kelly Rootes-Murdy; Harshvardhan Gazula; Eric Verner; Ross Kelly; Thomas DeRamus; Sergey M. Plis; Anand D. Sarwate; Jessica A. Turner; Vince D. Calhoun (Neuroinformatics, 2022)

Quadratically Constrained Myopic Adversarial Channels. - Yihan Zhang 001; Shashank Vatedka; Sidharth Jaggi; Anand D. Sarwate (IEEE Trans. Inf. Theory, 2022)

Network Traffic Shaping for Enhancing Privacy in IoT Systems. - Sijie Xiong; Anand D. Sarwate; Narayan B. Mandayam (IEEE/ACM Trans. Netw., 2022)

Computationally Efficient Codes for Adversarial Binary-Erasure Channels. - Sijie Li; Prasad Krishnan; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate (ISIT, 2023)

Spectral Evolution and Invariance in Linear-width Neural Networks. - Zhichao Wang; Andrew Engel; Anand D. Sarwate; Ioana Dumitriu; Tony Chiang (NeurIPS, 2023)

Robust Explanations for Deep Neural Networks via Pseudo Neural Tangent Kernel Surrogate Models. - Andrew Engel; Zhichao Wang; Natalie S. Frank; Ioana Dumitriu; Sutanay Choudhury; Anand D. Sarwate; Tony Chiang (CoRR, 2023)

Minibatching Offers Improved Generalization Performance for Second Order Optimizers. - Eric Silk; Swarnita Chakraborty; Nairanjana Dasgupta; Anand D. Sarwate; Andrew Lumsdaine; Tony Chiang (CoRR, 2023)

Robust Nonparametric Hypothesis Testing to Understand Variability in Training Neural Networks. - Sinjini Banerjee; Reilly Cannon; Tim Marrinan; Tony Chiang; Anand D. Sarwate (CoRR, 2023)

Approximating Functions with Approximate Privacy for Applications in Signal Estimation and Learning. - Naima Tasnim; Jafar Mohammadi; Anand D. Sarwate; Hafiz Imtiaz (Entropy, 2023)

Structured Low-Rank Tensors for Generalized Linear Models. - Batoul Taki; Anand D. Sarwate; Waheed U. Bajwa (Trans. Mach. Learn. Res., 2023)

Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility. - Dylan Martin; Sunitha Basodi; Sandeep R. Panta; Kelly Rootes-Murdy; Paul Prae; Anand D. Sarwate; Ross Kelly; Javier Tomas Romero; Bradley T. Baker; Harshvardhan Gazula; Henry Jeremy Bockholt; Jessica A. Turner; et al. (Frontiers Neuroinformatics, 2023)

Differential Fairness: An Intersectional Framework for Fair AI. - Rashidul Islam; Kamrun Naher Keya; Shimei Pan; Anand D. Sarwate; James R. Foulds (Entropy, 2023)

Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains. - Harshvardhan Gazula; Kelly Rootes-Murdy; Bharath Holla; Sunitha Basodi; Zuo Zhang; Eric Verner; Ross Kelly; Pratima Murthy; Amit Chakrabarti; Debasish Basu; Subodh Bhagyalakshmi Nanjayya; Rajkumar Lenin Singh; et al. (Neuroinformatics, 2023)

Advanced machine learning in neuroimaging studies via federated learning. - Sunitha Basodi; Javier Tomas Romero; Sandeep R. Panta; Dylan Martin; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (IEEE Big Data, 2024)

Federated Privacy-Preserving Visualization: A Vision Paper. - Ye Tao; Anand D. Sarwate; Sandeep R. Panta; Sergey M. Plis; Vince D. Calhoun (IEEE Big Data, 2024)

Low Separation Rank in Tensor Generalized Linear Models: An Asymptotic Analysis. - Batoul Taki; Anand D. Sarwate; Waheed U. Bajwa (CISS, 2024)

Federated Learning of Tensor Generalized Linear Models with low Separation Rank. - Jose Hoyos Sanchez; Batoul Taki; Waheed U. Bajwa; Anand D. Sarwate (ICASSP, 2024)

Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models. - Andrew Engel; Zhichao Wang; Natalie Frank; Ioana Dumitriu; Sutanay Choudhury; Anand D. Sarwate; Tony Chiang (ICLR, 2024)

Privacy-Preserving Visualization of Brain Functional Network Connectivity. - Ye Tao; Anand D. Sarwate; Sandeep R. Panta; Sergey M. Plis; Vince D. Calhoun (ISBI, 2024)

Computationally Efficient Codes for Strongly Dobrushin-Stambler Nonsymmetrizable Oblivious AVCs. - Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate; Y. Zhang (ISIT, 2024)

Timely Offloading in Mobile Edge Cloud Systems. - Nitya Sathyavageeswaran; Roy D. Yates; Anand D. Sarwate; Narayan Mandayam Rutgers (ITW, 2024)

Timely Offloading in Mobile Edge Cloud Systems. - Nitya Sathyavageeswaran; Roy D. Yates; Anand D. Sarwate; Narayan B. Mandayam (CoRR, 2024)

Measuring model variability using robust non-parametric testing. - Sinjini Banerjee; Tim Marrinan; Reilly Cannon; Tony Chiang; Anand D. Sarwate (CoRR, 2024)

Understanding Generative AI Content with Embedding Models. - Max Vargas; Reilly Cannon; Andrew Engel; Anand D. Sarwate; Tony Chiang (CoRR, 2024)

LASERS: LAtent Space Encoding for Representations with Sparsity for Generative Modeling. - Xin Li; Anand D. Sarwate (CoRR, 2024)

Learning To Help: Training Models to Assist Legacy Devices. - Yu Wu 020; Anand D. Sarwate (CoRR, 2024)

Codes for Adversaries: Between Worst-Case and Average-Case Jamming. - Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate; Yihan Zhang 001 (Found. Trends Commun. Inf. Theory, 2024)

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC. - Kelly Rootes-Murdy; Sandeep R. Panta; Ross Kelly; Javier Tomas Romero; Yann Quidé; Murray J. Cairns; C. M. Loughland; Vaughan J. Carr; Stanley V. Catts; Assen Jablensky; Melissa J. Green; Frans Henskens; et al. (Patterns, 2024)

COINSTAC: Decentralizing the future of brain imaging analysis. - Vince D. Calhoun; Sergey M. Plis; Jessica A. Turner; Anand D. Sarwate (Zenodo, 2024)

Differentially Private Distribution Estimation Using Functional Approximation. - Ye Tao; Anand D. Sarwate (ICASSP, 2025)

Learning to Help in Multi-Class Settings. - Yu Wu 020; Yansong Li; Zeyu Dong; Nitya Sathyavageeswaran; Anand D. Sarwate (ICLR, 2025)

Federated Analysis of Neuroimaging Data Using Coinstac. - Sunitha Basodi; Ross Kelly; Javier Tomas Romero; Dylan Martin; Sandeep R. Panta; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (ISBI, 2025)

LSR-Adapt: Ultra-Efficient Parameter Tuning with Matrix Low Separation Rank Kernel Adaptation. - Xin Li; Anand D. Sarwate (CoRR, 2025)

Unraveling the Localized Latents: Learning Stratified Manifold Structures in LLM Embedding Space with Sparse Mixture-of-Experts. - Xin Li; Anand D. Sarwate (CoRR, 2025)

Sliding Window Adversarial Channels. - Bikash Kumar Dey; Sidharth Jaggi; Michael Langberg; Anand D. Sarwate; Yihan Zhang 001 (CoRR, 2025)