Yue M. Lu - RankMe

145 papers A* 6A 1B 10Misc 20Journal 81Unranked 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Random Matrix Theory of Masked Self-Supervised Regression. CoRR Arie Wortsman Zurich, Federica Gerace, Bruno Loureiro, Yue M. Lu
2026	J	`jnl`	Asymptotic Theory of Iterated Empirical Risk Minimization, with Applications to Active Learning. CoRR Hugo Cui, Yue M. Lu
2025	A	`conf`	A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities. AISTATS Yatin Dandi, Luca Pesce, Hugo Cui, Florent Krzakala, Yue M. Lu, Bruno Loureiro
2025	J	`jnl`	A precise asymptotic analysis of learning diffusion models: theory and insights. CoRR Hugo Cui, Cengiz Pehlevan, Yue M. Lu
2025	J	`jnl`	High-Dimensional Analysis of Single-Layer Attention for Sparse-Token Classification. CoRR Nicholas Barnfield, Hugo Cui, Yue M. Lu
2025	J	`jnl`	Pretrain-Test Task Alignment Governs Generalization in In-Context Learning. CoRR Mary I. Letey, Jacob A. Zavatone-Veth, Yue M. Lu, Cengiz Pehlevan
2025	J	`jnl`	When does Gaussian equivalence fail and how to fix it: Non-universal behavior of random features with quadratic scaling. CoRR Garrett G. Wen, Hong Hu, Yue M. Lu, Zhou Fan, Theodor Misiakiewicz
2024	B	`conf`	A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification. ISIT Burak Çakmak, Yue M. Lu, Manfred Opper
2024	J	`jnl`	A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification. CoRR Burak Çakmak, Yue M. Lu, Manfred Opper
2024	J	`jnl`	A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities. CoRR Yatin Dandi, Luca Pesce, Hugo Cui, Florent Krzakala, Yue M. Lu, Bruno Loureiro
2024	J	`jnl`	Asymptotic theory of in-context learning by linear attention. CoRR Yue M. Lu, Mary I. Letey, Jacob A. Zavatone-Veth, Anindita Maiti, Cengiz Pehlevan
2024	J	`jnl`	Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime. CoRR Hong Hu, Yue M. Lu, Theodor Misiakiewicz
2024	A*	`conf`	Asymptotics of feature learning in two-layer networks after one gradient-step. ICML Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborová, Bruno Loureiro
2024	J	`jnl`	Asymptotics of feature learning in two-layer networks after one gradient-step. CoRR Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborová, Bruno Loureiro
2024	J	`jnl`	Spectral Universality in Regularized Linear Regression With Nearly Deterministic Sensing Matrices. IEEE Trans. Inf. Theory Rishabh Dudeja, Subhabrata Sen, Yue M. Lu
2023	—	`conf`	Keynote Speaker #2 : Exploring and exploiting the universality phenomenon in high-dimensional estimation and learning. ICCAIS Yue M. Lu
2023	J	`jnl`	Universality Laws for High-Dimensional Learning With Random Features. IEEE Trans. Inf. Theory Hong Hu, Yue M. Lu
2022	J	`jnl`	Analysis of Random Sequential Message Passing Algorithms for Approximate Inference. CoRR Burak Çakmak, Yue M. Lu, Manfred Opper
2022	J	`jnl`	SLOPE for Sparse Linear Regression: Asymptotics and Optimal Regularization. IEEE Trans. Inf. Theory Hong Hu, Yue M. Lu
2022	J	`jnl`	Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime. CoRR Hong Hu, Yue M. Lu
2022	J	`jnl`	Spectral Universality of Regularized Linear Regression with Nearly Deterministic Sensing Matrices. CoRR Rishabh Dudeja, Subhabrata Sen, Yue M. Lu
2021	—	`conf`	Construction of optimal spectral methods in phase retrieval. MSML Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2021	J	`jnl`	Householder Dice: A Matrix-Free Algorithm for Simulating Dynamics on Gaussian and Random Orthogonal Ensembles. CoRR Yue M. Lu
2021	J	`jnl`	Householder Dice: A Matrix-Free Algorithm for Simulating Dynamics on Gaussian and Random Orthogonal Ensembles. IEEE Trans. Inf. Theory Yue M. Lu
2021	A*	`conf`	On the Inherent Regularization Effects of Noise Injection During Training. ICML Oussama Dhifallah, Yue M. Lu
2021	J	`jnl`	On the Inherent Regularization Effects of Noise Injection During Training. CoRR Oussama Dhifallah, Yue M. Lu
2021	J	`jnl`	Phase Transitions in Transfer Learning for High-Dimensional Perceptrons. CoRR Oussama Dhifallah, Yue M. Lu
2021	J	`jnl`	Phase Transitions in Transfer Learning for High-Dimensional Perceptrons. Entropy Oussama Dhifallah, Yue M. Lu
2020	J	`jnl`	A Precise Performance Analysis of Learning with Random Features. CoRR Oussama Dhifallah, Yue M. Lu
2020	J	`jnl`	Construction of optimal spectral methods in phase retrieval. CoRR Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2020	A*	`conf`	Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. NeurIPS Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2020	J	`jnl`	Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. CoRR Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2020	J	`jnl`	Preparation of "Ion-Imprinting" Difunctional Magnetic Fluorescent Nanohybrid and Its Application to Detect Cadmium Ions. Sensors Lina Chen, Yue M. Lu, Minshu Qin, Fa Liu, Liang Huang, Jing Wang, Hui Xu, Na Li, Guobao Huang, Zhihui Luo, Baodong Zheng
2020	J	`jnl`	The Limiting Poisson Law of Massive MIMO Detection With Box Relaxation. IEEE J. Sel. Areas Inf. Theory Hong Hu, Yue M. Lu
2020	J	`jnl`	The Limiting Poisson Law of Massive MIMO Detection with Box Relaxation. CoRR Hong Hu, Yue M. Lu
2020	A*	`conf`	The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture. ICML Francesca Mignacco, Florent Krzakala, Yue M. Lu, Pierfrancesco Urbani, Lenka Zdeborová
2020	J	`jnl`	The role of regularization in classification of high-dimensional noisy Gaussian mixture. CoRR Francesca Mignacco, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2020	J	`jnl`	Universality Laws for High-Dimensional Learning with Random Features. CoRR Hong Hu, Yue M. Lu
2019	A*	`conf`	A Solvable High-Dimensional Model of GAN. NeurIPS Chuang Wang, Hong Hu, Yue M. Lu
2019	B	`conf`	Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression. ISIT Hong Hu, Yue M. Lu
2019	J	`jnl`	Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression. CoRR Hong Hu, Yue M. Lu
2019	A*	`conf`	Generalized Approximate Survey Propagation for High-Dimensional Estimation. ICML Carlo Lucibello, Luca Saglietti, Yue M. Lu
2019	J	`jnl`	Generalized Approximate Survey Propagation for High-Dimensional Estimation. CoRR Luca Saglietti, Yue M. Lu, Carlo Lucibello
2019	J	`jnl`	MMSE Approximation For Sparse Coding Algorithms Using Stochastic Resonance. IEEE Trans. Signal Process. Dror Simon, Jeremias Sulam, Yaniv Romano, Yue M. Lu, Michael Elad
2019	J	`jnl`	Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. IEEE Trans. Signal Process. Yuejie Chi, Yue M. Lu, Yuxin Chen
2019	J	`jnl`	Optimal Spectral Initialization for Signal Recovery With Applications to Phase Retrieval. IEEE Trans. Signal Process. Wangyu Luo, Wael Alghamdi, Yue M. Lu
2019	J	`jnl`	Super Resolution Phase Retrieval for Sparse Signals. IEEE Trans. Signal Process. Gilles Baechler, Miranda Krekovic, Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli
2018	J	`jnl`	A Solvable High-Dimensional Model of GAN. CoRR Chuang Wang, Hong Hu, Yue M. Lu
2018	J	`jnl`	Improving Pursuit Algorithms Using Stochastic Resonance. CoRR Dror Simon, Jeremias Sulam, Yaniv Romano, Yue M. Lu, Michael Elad
2018	J	`jnl`	Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. CoRR Yuejie Chi, Yue M. Lu, Yuxin Chen
2018	—	`conf`	Online Power Iteration For Subspace Estimation Under Incomplete Observations: Limiting Dynamics And Phase Transitions. SSP Hong Hu, Yue M. Lu
2018	J	`jnl`	Optimal Spectral Initialization for Signal Recovery with Applications to Phase Retrieval. CoRR Wangyu Luo, Wael Alghamdi, Yue M. Lu
2018	J	`jnl`	Phase Retrieval via Polytope Optimization: Geometry, Phase Transitions, and New Algorithms. CoRR Oussama Dhifallah, Christos Thrampoulidis, Yue M. Lu
2018	J	`jnl`	Sparse Representation in Fourier and Local Bases Using ProSparse: A Probabilistic Analysis. IEEE Trans. Inf. Theory Yue M. Lu, Jon Onativia, Pier Luigi Dragotti
2018	J	`jnl`	Streaming PCA and Subspace Tracking: The Missing Data Case. CoRR Laura Balzano, Yuejie Chi, Yue M. Lu
2018	J	`jnl`	Streaming PCA and Subspace Tracking: The Missing Data Case. Proc. IEEE Laura Balzano, Yuejie Chi, Yue M. Lu
2018	J	`jnl`	Subspace Estimation From Incomplete Observations: A High-Dimensional Analysis. IEEE J. Sel. Top. Signal Process. Chuang Wang, Yonina C. Eldar, Yue M. Lu
2018	J	`jnl`	Subspace Estimation from Incomplete Observations: A High-Dimensional Analysis. CoRR Chuang Wang, Yonina C. Eldar, Yue M. Lu
2018	J	`jnl`	Super Resolution Phase Retrieval for Sparse Signals. CoRR Gilles Baechler, Miranda Krekovic, Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli
2017	J	`jnl`	Fundamental Limits of PhaseMax for Phase Retrieval: A Replica Analysis. CoRR Oussama Dhifallah, Yue M. Lu
2017	—	`conf`	Fundamental limits of phasemax for phase retrieval: A replica analysis. CAMSAP Oussama Dhifallah, Yue M. Lu
2017	B	`conf`	Learning optimal parameters for binary sensing image reconstruction algorithms. ICIP Renan A. Rojas, Wangyu Luo, Víctor Murray, Yue M. Lu
2017	J	`jnl`	Multiprocessor Approximate Message Passing with Column-Wise Partitioning. CoRR Yanting Ma, Yue M. Lu, Dror Baron
2017	Misc	`conf`	Multiprocessor approximate message passing with column-wise partitioning. ICASSP Yanting Ma, Yue M. Lu, Dror Baron
2017	J	`jnl`	Phase Retrieval via Linear Programming: Fundamental Limits and Algorithmic Improvements. CoRR Oussama Dhifallah, Christos Thrampoulidis, Yue M. Lu
2017	J	`jnl`	Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation. CoRR Yue M. Lu, Gen Li
2017	—	`conf`	Phase retrieval via linear programming: Fundamental limits and algorithmic improvements. Allerton Oussama Dhifallah, Christos Thrampoulidis, Yue M. Lu
2017	J	`jnl`	Scaling Limit: Exact and Tractable Analysis of Online Learning Algorithms with Applications to Regularized Regression and PCA. CoRR Chuang Wang, Jonathan Mattingly, Yue M. Lu
2017	B	`conf`	Spectral initialization for nonconvex estimation: High-dimensional limit and phase transitions. ISIT Yue M. Lu, Gen Li
2017	—	`conf`	The Scaling Limit of High-Dimensional Online Independent Component Analysis. NIPS Chuang Wang, Yue M. Lu
2017	J	`jnl`	The Scaling Limit of High-Dimensional Online Independent Component Analysis. CoRR Chuang Wang, Yue M. Lu
2017	J	`jnl`	Understanding Symmetric Smoothing Filters: A Gaussian Mixture Model Perspective. IEEE Trans. Image Process. Stanley H. Chan, Todd E. Zickler, Yue M. Lu
2016	—	`conf`	A parallel primal-dual interior-point method for DC optimal power flow. PSCC Ariana Minot, Yue M. Lu, Na Li
2016	J	`jnl`	Decomposition of Space-Variant Blur in Image Deconvolution. IEEE Signal Process. Lett. Filip Sroubek, Jan Kamenický, Yue M. Lu
2016	J	`jnl`	Demystifying Symmetric Smoothing Filters. CoRR Stanley H. Chan, Todd E. Zickler, Yue M. Lu
2016	J	`jnl`	Kaczmarz Method for Solving Quadratic Equations. IEEE Signal Process. Lett. Yuejie Chi, Yue M. Lu
2016	J	`jnl`	Matched signal detection on graphs: Theory and application to brain imaging data classification. NeuroImage Chenhui Hu, Jorge Sepulcre, Keith A. Johnson, Georges El Fakhri, Yue M. Lu, Quanzheng Li
2016	J	`jnl`	Online Learning for Sparse PCA in High Dimensions: Exact Dynamics and Phase Transitions. CoRR Chuang Wang, Yue M. Lu
2016	B	`conf`	Online learning for sparse PCA in high dimensions: Exact dynamics and phase transitions. ITW Chuang Wang, Yue M. Lu
2016	Misc	`conf`	Prosparse denoise: Prony's based sparse pattern recovery in the presence of noise. ICASSP Jon Onativia, Yue M. Lu, Pier Luigi Dragotti
2016	J	`jnl`	Sampling Sparse Signals on the Sphere: Algorithms and Applications. IEEE Trans. Signal Process. Ivan Dokmanic, Yue M. Lu
2016	J	`jnl`	Sparsity according to Prony: Average-Case Performance Analysis and Phase Transition. CoRR Yue M. Lu, Jon Oñativia, Pier Luigi Dragotti
2015	—	`conf`	Blind calibration of multi-channel samplers using sparse recovery. CAMSAP Yuanxin Li, Yingsheng He, Yuejie Chi, Yue M. Lu
2015	—	`conf`	Gradient-based correction of chromatic aberration in the joint acquisition of color and near-infrared images. Digital Photography Zahra Sadeghipoor, Yue M. Lu, Sabine Süsstrunk
2015	—	`conf`	Multiscale guided deblurring: Chromatic aberration correction in color and near-infrared imaging. EUSIPCO Zahra Sadeghipoor, Yue M. Lu, Erick Méndez, Sabine Süsstrunk
2015	J	`jnl`	Optimal Detection of Random Walks on Graphs: Performance Analysis via Statistical Physics. CoRR Ameya Agaskar, Yue M. Lu
2015	—	`conf`	Phase retrieval using iterative projections: Dynamics in the large systems limit. Allerton Gen Li, Yuantao Gu, Yue M. Lu
2015	J	`jnl`	Randomized Kaczmarz Algorithm for Inconsistent Linear Systems: An Exact MSE Analysis. CoRR Chuang Wang, Ameya Agaskar, Yue M. Lu
2015	J	`jnl`	Sampling Sparse Signals on the Sphere: Algorithms and Applications. CoRR Ivan Dokmanic, Yue M. Lu
2015	Misc	`conf`	Sampling spherical finite rate of innovation signals. ICASSP Ivan Dokmanic, Yue M. Lu
2015	Misc	`conf`	Sparsity pattern recovery using FRI methods. ICASSP Jon Onativia, Yue M. Lu, Pier Luigi Dragotti
2015	B	`conf`	Understanding symmetric smoothing filters via Gaussian mixtures. ICIP Stanley H. Chan, Todd E. Zickler, Yue M. Lu
2014	—	`conf`	Efficient image reconstruction for gigapixel quantum image sensors. GlobalSIP Stanley H. Chan, Yue M. Lu
2014	Misc	`conf`	Finite dimensional FRI. ICASSP Jon Onativia, Yue M. Lu, Pier Luigi Dragoni
2014	J	`jnl`	Monte Carlo Non-Local Means: Random Sampling for Large-Scale Image Filtering. IEEE Trans. Image Process. Stanley H. Chan, Todd E. Zickler, Yue M. Lu
2014	J	`jnl`	On Sparse Representation in Fourier and Local Bases. IEEE Trans. Inf. Theory Pier Luigi Dragotti, Yue M. Lu
2014	Misc	`conf`	Optimal hypothesis testing with combinatorial structure: Detecting random walks on graphs. ACSSC Ameya Agaskar, Yue M. Lu
2014	—	`conf`	Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities. GlobalSIP Ameya Agaskar, Chuang Wang, Yue M. Lu
2014	Misc	`conf`	Separation of interleaved Markov chains. ACSSC Ariana Minot, Yue M. Lu
2013	J	`jnl`	A Spectral Graph Uncertainty Principle. IEEE Trans. Inf. Theory Ameya Agaskar, Yue M. Lu
2013	—	`conf`	A framework for adaptive parameter estimation with finite memory. GlobalSIP Yue M. Lu
2013	—	`conf`	A graph theoretical regression model for brain connectivity learning of Alzheimer'S disease. ISBI Chenhui Hu, Lin Cheng, Jorge Sepulcre, Georges El Fakhri, Yue M. Lu, Quanzheng Li
2013	Misc	`conf`	A novel compressive sensing approach to simultaneously acquire color and near-infrared images on a single sensor. ICASSP Zahra Sadeghipoor, Yue M. Lu, Sabine Süsstrunk
2013	—	`conf`	ALARM: A logistic auto-regressive model for binary processes on networks. GlobalSIP Ameya Agaskar, Yue M. Lu
2013	Misc	`conf`	Adaptive sensing and inference for single-photon imaging. CISS Yue M. Lu
2013	Misc	`conf`	Detecting randomwalks hidden in noise: Phase transition on large graphs. ICASSP Ameya Agaskar, Yue M. Lu
2013	Misc	`conf`	Fast non-local filtering by random sampling: It works, especially for large images. ICASSP Stanley H. Chan, Todd E. Zickler, Yue M. Lu
2013	—	`conf`	Matched Signal Detection on Graphs: Theory and Application to Brain Network Classification. IPMI Chenhui Hu, Lin Cheng, Jorge Sepulcre, Georges El Fakhri, Yue M. Lu, Quanzheng Li
2013	J	`jnl`	Monte Carlo non local means: Random sampling for large-scale image filtering. CoRR Stanley H. Chan, Todd E. Zickler, Yue M. Lu
2013	J	`jnl`	On Sparse Representation in Fourier and Local Bases. CoRR Pier Luigi Dragotti, Yue M. Lu
2013	J	`jnl`	Phase Retrieval for Sparse Signals: Uniqueness Conditions. CoRR Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli
2012	J	`jnl`	A Spectral Graph Uncertainty Principle CoRR Ameya Agaskar, Yue M. Lu
2012	J	`jnl`	Bits From Photons: Oversampled Image Acquisition Using Binary Poisson Statistics. IEEE Trans. Image Process. Feng Yang, Yue M. Lu, Luciano Sbaiz, Martin Vetterli
2012	Misc	`conf`	Blind estimation and low-rate sampling of sparse mimo systems with common support. ICASSP Ying Xiong, Yue M. Lu
2012	B	`conf`	Graph-based regularization for color image demosaicking. ICIP Chenhui Hu, Lin Cheng, Yue M. Lu
2012	J	`jnl`	Multidimensional Filter Banks and Multiscale Geometric Representations. Found. Trends Signal Process. Minh N. Do, Yue M. Lu
2012	—	`conf`	Optimum spectral sensitivity functions for single sensor color imaging. Digital Photography Zahra Sadeghipoor, Yue M. Lu, Sabine Süsstrunk
2012	Misc	`conf`	Uncertainty principles for signals defined on graphs: Bounds and characterizations. ICASSP Ameya Agaskar, Yue M. Lu
2011	Misc	`conf`	Can one hear the shape of a room: The 2-D polygonal case. ICASSP Ivan Dokmanic, Yue M. Lu, Martin Vetterli
2011	B	`conf`	Correlation-based joint acquisition and demosaicing of visible and near-infrared images. ICIP Zahra Sadeghipoor, Yue M. Lu, Sabine Süsstrunk
2011	J	`jnl`	Gigapixel Binary Sensing: Image Acquisition Using Oversampled One-Bit Poisson Statistics CoRR Feng Yang, Yue M. Lu, Luciano Sbaiz, Martin Vetterli
2011	—	`conf`	Localization of diffusive sources using spatiotemporal measurements. Allerton Yue M. Lu, Pier Luigi Dragotti, Martin Vetterli
2011	Misc	`conf`	Sampling and reconstructing diffusion fields with localized sources. ICASSP Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli
2011	Misc	`conf`	Sparse spectral factorization: Unicity and reconstruction algorithms. ICASSP Yue M. Lu, Martin Vetterli
2010	—	`conf`	An optimal algorithm for reconstructing images from binary measurements. Computational Imaging Feng Yang, Yue M. Lu, Luciano Sbaiz, Martin Vetterli
2010	J	`jnl`	Demosaicking by Alternating Projections: Theory and Fast One-Step Implementation. IEEE Trans. Image Process. Yue M. Lu, Mina Karzand, Martin Vetterli
2010	J	`jnl`	Distributed sampling of signals linked by sparse filtering: theory and applications. IEEE Trans. Signal Process. Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetterli
2010	Misc	`conf`	Learning sparse systems at sub-Nyquist rates: A frequency-domain approach. ICASSP Martin McCormick, Yue M. Lu, Martin Vetterli
2009	J	`jnl`	A computable fourier condition generating alias-free sampling lattices. IEEE Trans. Signal Process. Yue M. Lu, Minh N. Do, Richard S. Laugesen
2009	B	`conf`	Designing color filter arrays for the joint capture of visible and near-infrared images. ICIP Yue M. Lu, Clément Fredembach, Martin Vetterli, Sabine Süsstrunk
2009	Misc	`conf`	Distributed sensing of signals linked by sparse filtering. ICASSP Olivier Roy, Ali Hormati, Yue M. Lu, Martin Vetterli
2009	—	`conf`	Iterative demosaicking accelerated: theory and fast noniterative implementations. Computational Imaging Yue M. Lu, Mina Karzand, Martin Vetterli
2009	—	`conf`	Optimal color filter array design: quantitative conditions and an efficient search procedure. Digital Photography Yue M. Lu, Martin Vetterli
2009	Misc	`conf`	Spatial super-resolution of a diffusion field by temporal oversampling in sensor networks. ICASSP Yue M. Lu, Martin Vetterli
2008	J	`jnl`	A Mapping-Based Design for Nonsubsampled Hourglass Filter Banks in Arbitrary Dimensions. IEEE Trans. Signal Process. Yue M. Lu, Minh N. Do
2008	J	`jnl`	A Theory for Sampling Signals From a Union of Subspaces. IEEE Trans. Signal Process. Yue M. Lu, Minh N. Do
2008	Misc	`conf`	Assessing the challenges of environmental signal processing through the sensorscope project. ICASSP Guillermo Barrenetxea, François Ingelrest, Yue M. Lu, Martin Vetterli
2008	J	`jnl`	Sampling Signals from a Union of Subspaces. IEEE Signal Process. Mag. Yue M. Lu, Minh N. Do
2007	—	`conf`	Finding Optimal Integral Sampling Lattices for a given Frequency Support in Multidimensions. ICIP (2) Yue M. Lu, Minh N. Do
2007	—	`conf`	Image interpolation using multiscale geometric representations. Computational Imaging Nickolaus Mueller, Yue M. Lu, Minh N. Do
2007	J	`jnl`	Multidimensional Directional Filter Banks and Surfacelets. IEEE Trans. Image Process. Yue M. Lu, Minh N. Do
2007	—	`—`	Multidimensional Geometrical Signal Representation: Constructions and Applications Yue M. Lu
2006	B	`conf`	A New Contourlet Transform with Sharp Frequency Localization. ICIP Yue M. Lu, Minh N. Do
2005	—	`conf`	The finer directional wavelet transform [image processing applications]. ICASSP (4) Yue M. Lu, Minh N. Do
2004	—	`conf`	A geometrical approach to sampling signals with finite rate of innovation. ICASSP (2) Yue M. Lu, Minh N. Do