A geometrical approach to sampling signals with finite rate of innovation. - Yue M. Lu; Minh N. Do (ICASSP (2), 2004)

The finer directional wavelet transform [image processing applications]. - Yue M. Lu; Minh N. Do (ICASSP (4), 2005)

A New Contourlet Transform with Sharp Frequency Localization. - Yue M. Lu; Minh N. Do (ICIP, 2006)

Image interpolation using multiscale geometric representations. - Nickolaus Mueller; Yue M. Lu; Minh N. Do (Computational Imaging, 2007)

Finding Optimal Integral Sampling Lattices for a given Frequency Support in Multidimensions. - Yue M. Lu; Minh N. Do (ICIP (2), 2007)

Multidimensional Directional Filter Banks and Surfacelets. - Yue M. Lu; Minh N. Do (IEEE Trans. Image Process., 2007)

Multidimensional Geometrical Signal Representation: Constructions and Applications - Yue M. Lu (2007)

Assessing the challenges of environmental signal processing through the sensorscope project. - Guillermo Barrenetxea; François Ingelrest; Yue M. Lu; Martin Vetterli (ICASSP, 2008)

Sampling Signals from a Union of Subspaces. - Yue M. Lu; Minh N. Do (IEEE Signal Process. Mag., 2008)

A Mapping-Based Design for Nonsubsampled Hourglass Filter Banks in Arbitrary Dimensions. - Yue M. Lu; Minh N. Do (IEEE Trans. Signal Process., 2008)

A Theory for Sampling Signals From a Union of Subspaces. - Yue M. Lu; Minh N. Do (IEEE Trans. Signal Process., 2008)

Iterative demosaicking accelerated: theory and fast noniterative implementations. - Yue M. Lu; Mina Karzand; Martin Vetterli (Computational Imaging, 2009)

Optimal color filter array design: quantitative conditions and an efficient search procedure. - Yue M. Lu; Martin Vetterli (Digital Photography, 2009)

Spatial super-resolution of a diffusion field by temporal oversampling in sensor networks. - Yue M. Lu; Martin Vetterli (ICASSP, 2009)

Distributed sensing of signals linked by sparse filtering. - Olivier Roy; Ali Hormati; Yue M. Lu; Martin Vetterli (ICASSP, 2009)

Designing color filter arrays for the joint capture of visible and near-infrared images. - Yue M. Lu; Clément Fredembach; Martin Vetterli; Sabine Süsstrunk (ICIP, 2009)

A computable fourier condition generating alias-free sampling lattices. - Yue M. Lu; Minh N. Do; Richard S. Laugesen (IEEE Trans. Signal Process., 2009)

An optimal algorithm for reconstructing images from binary measurements. - Feng Yang; Yue M. Lu; Luciano Sbaiz; Martin Vetterli (Computational Imaging, 2010)

Learning sparse systems at sub-Nyquist rates: A frequency-domain approach. - Martin McCormick; Yue M. Lu; Martin Vetterli (ICASSP, 2010)

Demosaicking by Alternating Projections: Theory and Fast One-Step Implementation. - Yue M. Lu; Mina Karzand; Martin Vetterli (IEEE Trans. Image Process., 2010)

Distributed sampling of signals linked by sparse filtering: theory and applications. - Ali Hormati; Olivier Roy; Yue M. Lu; Martin Vetterli (IEEE Trans. Signal Process., 2010)

Localization of diffusive sources using spatiotemporal measurements. - Yue M. Lu; Pier Luigi Dragotti; Martin Vetterli (Allerton, 2011)

Can one hear the shape of a room: The 2-D polygonal case. - Ivan Dokmanic; Yue M. Lu; Martin Vetterli (ICASSP, 2011)

Sparse spectral factorization: Unicity and reconstruction algorithms. - Yue M. Lu; Martin Vetterli (ICASSP, 2011)

Sampling and reconstructing diffusion fields with localized sources. - Juri Ranieri; Amina Chebira; Yue M. Lu; Martin Vetterli (ICASSP, 2011)

Correlation-based joint acquisition and demosaicing of visible and near-infrared images. - Zahra Sadeghipoor; Yue M. Lu; Sabine Süsstrunk (ICIP, 2011)

Gigapixel Binary Sensing: Image Acquisition Using Oversampled One-Bit Poisson Statistics - Feng Yang; Yue M. Lu; Luciano Sbaiz; Martin Vetterli (CoRR, 2011)

Optimum spectral sensitivity functions for single sensor color imaging. - Zahra Sadeghipoor; Yue M. Lu; Sabine Süsstrunk (Digital Photography, 2012)

Uncertainty principles for signals defined on graphs: Bounds and characterizations. - Ameya Agaskar; Yue M. Lu (ICASSP, 2012)

Blind estimation and low-rate sampling of sparse mimo systems with common support. - Ying Xiong; Yue M. Lu (ICASSP, 2012)

Graph-based regularization for color image demosaicking. - Chenhui Hu; Lin Cheng; Yue M. Lu (ICIP, 2012)

Multidimensional Filter Banks and Multiscale Geometric Representations. - Minh N. Do; Yue M. Lu (Found. Trends Signal Process., 2012)

Bits From Photons: Oversampled Image Acquisition Using Binary Poisson Statistics. - Feng Yang; Yue M. Lu; Luciano Sbaiz; Martin Vetterli (IEEE Trans. Image Process., 2012)

Adaptive sensing and inference for single-photon imaging. - Yue M. Lu (CISS, 2013)

ALARM: A logistic auto-regressive model for binary processes on networks. - Ameya Agaskar; Yue M. Lu (GlobalSIP, 2013)

A framework for adaptive parameter estimation with finite memory. - Yue M. Lu (GlobalSIP, 2013)

Detecting randomwalks hidden in noise: Phase transition on large graphs. - Ameya Agaskar; Yue M. Lu (ICASSP, 2013)

Fast non-local filtering by random sampling: It works, especially for large images. - Stanley H. Chan; Todd E. Zickler; Yue M. Lu (ICASSP, 2013)

A novel compressive sensing approach to simultaneously acquire color and near-infrared images on a single sensor. - Zahra Sadeghipoor; Yue M. Lu; Sabine Süsstrunk (ICASSP, 2013)

Matched Signal Detection on Graphs: Theory and Application to Brain Network Classification. - Chenhui Hu; Lin Cheng; Jorge Sepulcre; Georges El Fakhri; Yue M. Lu; Quanzheng Li (IPMI, 2013)

A graph theoretical regression model for brain connectivity learning of Alzheimer'S disease. - Chenhui Hu; Lin Cheng; Jorge Sepulcre; Georges El Fakhri; Yue M. Lu; Quanzheng Li (ISBI, 2013)

Phase Retrieval for Sparse Signals: Uniqueness Conditions. - Juri Ranieri; Amina Chebira; Yue M. Lu; Martin Vetterli (CoRR, 2013)

A Spectral Graph Uncertainty Principle. - Ameya Agaskar; Yue M. Lu (IEEE Trans. Inf. Theory, 2013)

Optimal hypothesis testing with combinatorial structure: Detecting random walks on graphs. - Ameya Agaskar; Yue M. Lu (ACSSC, 2014)

Separation of interleaved Markov chains. - Ariana Minot; Yue M. Lu (ACSSC, 2014)

Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities. - Ameya Agaskar; Chuang Wang 007; Yue M. Lu (GlobalSIP, 2014)

Efficient image reconstruction for gigapixel quantum image sensors. - Stanley H. Chan; Yue M. Lu (GlobalSIP, 2014)

Finite dimensional FRI. - Jon Onativia; Yue M. Lu; Pier Luigi Dragoni (ICASSP, 2014)

Monte Carlo Non-Local Means: Random Sampling for Large-Scale Image Filtering. - Stanley H. Chan; Todd E. Zickler; Yue M. Lu (IEEE Trans. Image Process., 2014)

On Sparse Representation in Fourier and Local Bases. - Pier Luigi Dragotti; Yue M. Lu (IEEE Trans. Inf. Theory, 2014)

Phase retrieval using iterative projections: Dynamics in the large systems limit. - Gen Li 005; Yuantao Gu; Yue M. Lu (Allerton, 2015)

Blind calibration of multi-channel samplers using sparse recovery. - Yuanxin Li 003; Yingsheng He; Yuejie Chi; Yue M. Lu (CAMSAP, 2015)

Gradient-based correction of chromatic aberration in the joint acquisition of color and near-infrared images. - Zahra Sadeghipoor; Yue M. Lu; Sabine Süsstrunk (Digital Photography, 2015)

Multiscale guided deblurring: Chromatic aberration correction in color and near-infrared imaging. - Zahra Sadeghipoor; Yue M. Lu; Erick Méndez; Sabine Süsstrunk (EUSIPCO, 2015)

Sampling spherical finite rate of innovation signals. - Ivan Dokmanic; Yue M. Lu (ICASSP, 2015)

Sparsity pattern recovery using FRI methods. - Jon Onativia; Yue M. Lu; Pier Luigi Dragotti (ICASSP, 2015)

Understanding symmetric smoothing filters via Gaussian mixtures. - Stanley H. Chan; Todd E. Zickler; Yue M. Lu (ICIP, 2015)

Optimal Detection of Random Walks on Graphs: Performance Analysis via Statistical Physics. - Ameya Agaskar; Yue M. Lu (CoRR, 2015)

Randomized Kaczmarz Algorithm for Inconsistent Linear Systems: An Exact MSE Analysis. - Chuang Wang 007; Ameya Agaskar; Yue M. Lu (CoRR, 2015)

Prosparse denoise: Prony's based sparse pattern recovery in the presence of noise. - Jon Onativia; Yue M. Lu; Pier Luigi Dragotti (ICASSP, 2016)

Online learning for sparse PCA in high dimensions: Exact dynamics and phase transitions. - Chuang Wang 007; Yue M. Lu (ITW, 2016)

A parallel primal-dual interior-point method for DC optimal power flow. - Ariana Minot; Yue M. Lu; Na Li 002 (PSCC, 2016)

Demystifying Symmetric Smoothing Filters. - Stanley H. Chan; Todd E. Zickler; Yue M. Lu (CoRR, 2016)

Sparsity according to Prony: Average-Case Performance Analysis and Phase Transition. - Yue M. Lu; Jon Oñativia; Pier Luigi Dragotti (CoRR, 2016)

Matched signal detection on graphs: Theory and application to brain imaging data classification. - Chenhui Hu; Jorge Sepulcre; Keith A. Johnson; Georges El Fakhri; Yue M. Lu; Quanzheng Li (NeuroImage, 2016)

Kaczmarz Method for Solving Quadratic Equations. - Yuejie Chi; Yue M. Lu (IEEE Signal Process. Lett., 2016)

Decomposition of Space-Variant Blur in Image Deconvolution. - Filip Sroubek; Jan Kamenický; Yue M. Lu (IEEE Signal Process. Lett., 2016)

Sampling Sparse Signals on the Sphere: Algorithms and Applications. - Ivan Dokmanic; Yue M. Lu (IEEE Trans. Signal Process., 2016)

Phase retrieval via linear programming: Fundamental limits and algorithmic improvements. - Oussama Dhifallah; Christos Thrampoulidis; Yue M. Lu (Allerton, 2017)

Fundamental limits of phasemax for phase retrieval: A replica analysis. - Oussama Dhifallah; Yue M. Lu (CAMSAP, 2017)

Multiprocessor approximate message passing with column-wise partitioning. - Yanting Ma; Yue M. Lu; Dror Baron (ICASSP, 2017)

Learning optimal parameters for binary sensing image reconstruction algorithms. - Renan A. Rojas; Wangyu Luo; Víctor Murray; Yue M. Lu (ICIP, 2017)

Spectral initialization for nonconvex estimation: High-dimensional limit and phase transitions. - Yue M. Lu; Gen Li 005 (ISIT, 2017)

The Scaling Limit of High-Dimensional Online Independent Component Analysis. - Chuang Wang 007; Yue M. Lu (NIPS, 2017)

Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation. - Yue M. Lu; Gen Li 005 (CoRR, 2017)

Scaling Limit: Exact and Tractable Analysis of Online Learning Algorithms with Applications to Regularized Regression and PCA. - Chuang Wang 007; Jonathan Mattingly; Yue M. Lu (CoRR, 2017)

Understanding Symmetric Smoothing Filters: A Gaussian Mixture Model Perspective. - Stanley H. Chan; Todd E. Zickler; Yue M. Lu (IEEE Trans. Image Process., 2017)

Online Power Iteration For Subspace Estimation Under Incomplete Observations: Limiting Dynamics And Phase Transitions. - Hong Hu; Yue M. Lu (SSP, 2018)

Phase Retrieval via Polytope Optimization: Geometry, Phase Transitions, and New Algorithms. - Oussama Dhifallah; Christos Thrampoulidis; Yue M. Lu (CoRR, 2018)

Improving Pursuit Algorithms Using Stochastic Resonance. - Dror Simon; Jeremias Sulam; Yaniv Romano; Yue M. Lu; Michael Elad (CoRR, 2018)

Subspace Estimation From Incomplete Observations: A High-Dimensional Analysis. - Chuang Wang 007; Yonina C. Eldar; Yue M. Lu (IEEE J. Sel. Top. Signal Process., 2018)

Streaming PCA and Subspace Tracking: The Missing Data Case. - Laura Balzano; Yuejie Chi; Yue M. Lu (Proc. IEEE, 2018)

Sparse Representation in Fourier and Local Bases Using ProSparse: A Probabilistic Analysis. - Yue M. Lu; Jon Onativia; Pier Luigi Dragotti (IEEE Trans. Inf. Theory, 2018)

Generalized Approximate Survey Propagation for High-Dimensional Estimation. - Carlo Lucibello; Luca Saglietti; Yue M. Lu (ICML, 2019)

Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression. - Hong Hu; Yue M. Lu (ISIT, 2019)

A Solvable High-Dimensional Model of GAN. - Chuang Wang 007; Hong Hu; Yue M. Lu (NeurIPS, 2019)

Super Resolution Phase Retrieval for Sparse Signals. - Gilles Baechler; Miranda Krekovic; Juri Ranieri; Amina Chebira; Yue M. Lu; Martin Vetterli (IEEE Trans. Signal Process., 2019)

Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. - Yuejie Chi; Yue M. Lu; Yuxin Chen 002 (IEEE Trans. Signal Process., 2019)

Optimal Spectral Initialization for Signal Recovery With Applications to Phase Retrieval. - Wangyu Luo; Wael Alghamdi; Yue M. Lu (IEEE Trans. Signal Process., 2019)

MMSE Approximation For Sparse Coding Algorithms Using Stochastic Resonance. - Dror Simon; Jeremias Sulam; Yaniv Romano; Yue M. Lu; Michael Elad (IEEE Trans. Signal Process., 2019)

The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture. - Francesca Mignacco; Florent Krzakala; Yue M. Lu; Pierfrancesco Urbani; Lenka Zdeborová (ICML, 2020)

Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. - Benjamin Aubin; Florent Krzakala; Yue M. Lu; Lenka Zdeborová (NeurIPS, 2020)

The role of regularization in classification of high-dimensional noisy Gaussian mixture. - Francesca Mignacco; Florent Krzakala; Yue M. Lu; Lenka Zdeborová (CoRR, 2020)

A Precise Performance Analysis of Learning with Random Features. - Oussama Dhifallah; Yue M. Lu (CoRR, 2020)

The Limiting Poisson Law of Massive MIMO Detection With Box Relaxation. - Hong Hu; Yue M. Lu (IEEE J. Sel. Areas Inf. Theory, 2020)

Preparation of "Ion-Imprinting" Difunctional Magnetic Fluorescent Nanohybrid and Its Application to Detect Cadmium Ions. - Lina Chen; Yue M. Lu; Minshu Qin; Fa Liu; Liang Huang; Jing Wang; Hui Xu; Na Li; Guobao Huang; Zhihui Luo 004; Baodong Zheng (Sensors, 2020)

On the Inherent Regularization Effects of Noise Injection During Training. - Oussama Dhifallah; Yue M. Lu (ICML, 2021)

Construction of optimal spectral methods in phase retrieval. - Antoine Maillard; Florent Krzakala; Yue M. Lu; Lenka Zdeborová (MSML, 2021)

Phase Transitions in Transfer Learning for High-Dimensional Perceptrons. - Oussama Dhifallah; Yue M. Lu (Entropy, 2021)

Householder Dice: A Matrix-Free Algorithm for Simulating Dynamics on Gaussian and Random Orthogonal Ensembles. - Yue M. Lu (IEEE Trans. Inf. Theory, 2021)

Analysis of Random Sequential Message Passing Algorithms for Approximate Inference. - Burak Çakmak; Yue M. Lu; Manfred Opper (CoRR, 2022)

Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime. - Hong Hu; Yue M. Lu (CoRR, 2022)

SLOPE for Sparse Linear Regression: Asymptotics and Optimal Regularization. - Hong Hu; Yue M. Lu (IEEE Trans. Inf. Theory, 2022)

Keynote Speaker #2 : Exploring and exploiting the universality phenomenon in high-dimensional estimation and learning. - Yue M. Lu (ICCAIS, 2023)

Universality Laws for High-Dimensional Learning With Random Features. - Hong Hu; Yue M. Lu (IEEE Trans. Inf. Theory, 2023)

Asymptotics of feature learning in two-layer networks after one gradient-step. - Hugo Cui; Luca Pesce; Yatin Dandi; Florent Krzakala; Yue M. Lu; Lenka Zdeborová; Bruno Loureiro (ICML, 2024)

A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification. - Burak Çakmak; Yue M. Lu; Manfred Opper (ISIT, 2024)

Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime. - Hong Hu; Yue M. Lu; Theodor Misiakiewicz (CoRR, 2024)

Asymptotic theory of in-context learning by linear attention. - Yue M. Lu; Mary I. Letey; Jacob A. Zavatone-Veth; Anindita Maiti; Cengiz Pehlevan (CoRR, 2024)

Spectral Universality in Regularized Linear Regression With Nearly Deterministic Sensing Matrices. - Rishabh Dudeja; Subhabrata Sen; Yue M. Lu (IEEE Trans. Inf. Theory, 2024)

A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities. - Yatin Dandi; Luca Pesce; Hugo Cui; Florent Krzakala; Yue M. Lu; Bruno Loureiro (AISTATS, 2025)

A precise asymptotic analysis of learning diffusion models: theory and insights. - Hugo Cui; Cengiz Pehlevan; Yue M. Lu (CoRR, 2025)