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2020 – today
- 2024
[j31]Rishabh Dudeja
, Subhabrata Sen, Yue M. Lu:
Spectral Universality in Regularized Linear Regression With Nearly Deterministic Sensing Matrices. IEEE Trans. Inf. Theory 70(11): 7923-7951 (2024)- [c61]Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborová, Bruno Loureiro:
Asymptotics of feature learning in two-layer networks after one gradient-step. ICML 2024 - [c60]Burak Çakmak, Yue M. Lu, Manfred Opper:
A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification. ISIT 2024: 747-752 - [i44]Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborová, Bruno Loureiro:
Asymptotics of feature learning in two-layer networks after one gradient-step. CoRR abs/2402.04980 (2024) - [i43]Burak Çakmak, Yue M. Lu, Manfred Opper:
A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification. CoRR abs/2402.08676 (2024) - [i42]Hong Hu, Yue M. Lu, Theodor Misiakiewicz:
Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime. CoRR abs/2403.08160 (2024) - [i41]Yue M. Lu, Mary I. Letey, Jacob A. Zavatone-Veth, Anindita Maiti, Cengiz Pehlevan:
Asymptotic theory of in-context learning by linear attention. CoRR abs/2405.11751 (2024) - [i40]Yatin Dandi, Luca Pesce, Hugo Cui, Florent Krzakala, Yue M. Lu, Bruno Loureiro:
A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities. CoRR abs/2410.18938 (2024) - 2023
- [j30]Hong Hu, Yue M. Lu:
Universality Laws for High-Dimensional Learning With Random Features. IEEE Trans. Inf. Theory 69(3): 1932-1964 (2023) - [c59]Yue M. Lu:
Keynote Speaker #2 : Exploring and exploiting the universality phenomenon in high-dimensional estimation and learning. ICCAIS 2023: 1 - 2022
- [j29]Hong Hu, Yue M. Lu:
SLOPE for Sparse Linear Regression: Asymptotics and Optimal Regularization. IEEE Trans. Inf. Theory 68(11): 7627-7664 (2022) - [i39]Burak Çakmak, Yue M. Lu, Manfred Opper:
Analysis of Random Sequential Message Passing Algorithms for Approximate Inference. CoRR abs/2202.08198 (2022) - [i38]Hong Hu, Yue M. Lu:
Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime. CoRR abs/2205.06798 (2022) - [i37]Rishabh Dudeja, Subhabrata Sen, Yue M. Lu:
Spectral Universality of Regularized Linear Regression with Nearly Deterministic Sensing Matrices. CoRR abs/2208.02753 (2022) - 2021
- [j28]Oussama Dhifallah, Yue M. Lu:
Phase Transitions in Transfer Learning for High-Dimensional Perceptrons. Entropy 23(4): 400 (2021) - [j27]Yue M. Lu:
Householder Dice: A Matrix-Free Algorithm for Simulating Dynamics on Gaussian and Random Orthogonal Ensembles. IEEE Trans. Inf. Theory 67(12): 8264-8272 (2021) - [c58]Oussama Dhifallah, Yue M. Lu:
On the Inherent Regularization Effects of Noise Injection During Training. ICML 2021: 2665-2675 - [c57]Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová:
Construction of optimal spectral methods in phase retrieval. MSML 2021: 693-720 - [i36]Oussama Dhifallah, Yue M. Lu:
Phase Transitions in Transfer Learning for High-Dimensional Perceptrons. CoRR abs/2101.01918 (2021) - [i35]Yue M. Lu:
Householder Dice: A Matrix-Free Algorithm for Simulating Dynamics on Gaussian and Random Orthogonal Ensembles. CoRR abs/2101.07464 (2021) - [i34]Oussama Dhifallah, Yue M. Lu:
On the Inherent Regularization Effects of Noise Injection During Training. CoRR abs/2102.07379 (2021) - 2020
- [j26]Hong Hu, Yue M. Lu:
The Limiting Poisson Law of Massive MIMO Detection With Box Relaxation. IEEE J. Sel. Areas Inf. Theory 1(3): 695-704 (2020) - [j25]Lina Chen, Yue M. Lu, Minshu Qin, Fa Liu, Liang Huang, Jing Wang, Hui Xu, Na Li, Guobao Huang, Zhihui Luo, Baodong Zheng:
Preparation of "Ion-Imprinting" Difunctional Magnetic Fluorescent Nanohybrid and Its Application to Detect Cadmium Ions. Sensors 20(4): 995 (2020) - [c56]Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová:
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. NeurIPS 2020 - [i33]Francesca Mignacco, Florent Krzakala, Yue M. Lu, Lenka Zdeborová:
The role of regularization in classification of high-dimensional noisy Gaussian mixture. CoRR abs/2002.11544 (2020) - [i32]Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová:
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. CoRR abs/2006.06560 (2020) - [i31]Hong Hu, Yue M. Lu:
The Limiting Poisson Law of Massive MIMO Detection with Box Relaxation. CoRR abs/2006.08416 (2020) - [i30]Oussama Dhifallah, Yue M. Lu:
A Precise Performance Analysis of Learning with Random Features. CoRR abs/2008.11904 (2020) - [i29]Hong Hu, Yue M. Lu:
Universality Laws for High-Dimensional Learning with Random Features. CoRR abs/2009.07669 (2020) - [i28]Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová:
Construction of optimal spectral methods in phase retrieval. CoRR abs/2012.04524 (2020)
2010 – 2019
- 2019
- [j24]Wangyu Luo, Wael Alghamdi, Yue M. Lu:
Optimal Spectral Initialization for Signal Recovery With Applications to Phase Retrieval. IEEE Trans. Signal Process. 67(9): 2347-2356 (2019) - [j23]Dror Simon, Jeremias Sulam, Yaniv Romano, Yue M. Lu, Michael Elad:
MMSE Approximation For Sparse Coding Algorithms Using Stochastic Resonance. IEEE Trans. Signal Process. 67(17): 4597-4610 (2019) - [j22]Gilles Baechler, Miranda Krekovic, Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli:
Super Resolution Phase Retrieval for Sparse Signals. IEEE Trans. Signal Process. 67(18): 4839-4854 (2019) - [j21]Yuejie Chi, Yue M. Lu, Yuxin Chen:
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. IEEE Trans. Signal Process. 67(20): 5239-5269 (2019) - [c55]Carlo Lucibello, Luca Saglietti, Yue M. Lu:
Generalized Approximate Survey Propagation for High-Dimensional Estimation. ICML 2019: 4173-4182 - [c54]Hong Hu, Yue M. Lu:
Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression. ISIT 2019: 375-379 - [c53]Chuang Wang, Hong Hu, Yue M. Lu:
A Solvable High-Dimensional Model of GAN. NeurIPS 2019: 13759-13768 - [i27]Hong Hu, Yue M. Lu:
Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression. CoRR abs/1903.11582 (2019) - [i26]Luca Saglietti, Yue M. Lu, Carlo Lucibello:
Generalized Approximate Survey Propagation for High-Dimensional Estimation. CoRR abs/1905.05313 (2019) - 2018
- [j20]Chuang Wang, Yonina C. Eldar, Yue M. Lu:
Subspace Estimation From Incomplete Observations: A High-Dimensional Analysis. IEEE J. Sel. Top. Signal Process. 12(6): 1240-1252 (2018) - [j19]Laura Balzano, Yuejie Chi, Yue M. Lu:
Streaming PCA and Subspace Tracking: The Missing Data Case. Proc. IEEE 106(8): 1293-1310 (2018) - [j18]Yue M. Lu, Jon Onativia, Pier Luigi Dragotti:
Sparse Representation in Fourier and Local Bases Using ProSparse: A Probabilistic Analysis. IEEE Trans. Inf. Theory 64(4): 2639-2647 (2018) - [c52]Hong Hu, Yue M. Lu:
Online Power Iteration For Subspace Estimation Under Incomplete Observations: Limiting Dynamics And Phase Transitions. SSP 2018: 851-855 - [i25]Chuang Wang, Yonina C. Eldar, Yue M. Lu:
Subspace Estimation from Incomplete Observations: A High-Dimensional Analysis. CoRR abs/1805.06834 (2018) - [i24]Chuang Wang, Hong Hu, Yue M. Lu:
A Solvable High-Dimensional Model of GAN. CoRR abs/1805.08349 (2018) - [i23]Oussama Dhifallah, Christos Thrampoulidis, Yue M. Lu:
Phase Retrieval via Polytope Optimization: Geometry, Phase Transitions, and New Algorithms. CoRR abs/1805.09555 (2018) - [i22]Laura Balzano, Yuejie Chi, Yue M. Lu:
Streaming PCA and Subspace Tracking: The Missing Data Case. CoRR abs/1806.04609 (2018) - [i21]Dror Simon, Jeremias Sulam, Yaniv Romano, Yue M. Lu, Michael Elad:
Improving Pursuit Algorithms Using Stochastic Resonance. CoRR abs/1806.10171 (2018) - [i20]Gilles Baechler, Miranda Krekovic, Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli:
Super Resolution Phase Retrieval for Sparse Signals. CoRR abs/1808.01961 (2018) - [i19]Yuejie Chi, Yue M. Lu, Yuxin Chen:
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. CoRR abs/1809.09573 (2018) - [i18]Wangyu Luo, Wael Alghamdi, Yue M. Lu:
Optimal Spectral Initialization for Signal Recovery with Applications to Phase Retrieval. CoRR abs/1811.04420 (2018) - 2017
- [j17]Stanley H. Chan, Todd E. Zickler, Yue M. Lu:
Understanding Symmetric Smoothing Filters: A Gaussian Mixture Model Perspective. IEEE Trans. Image Process. 26(11): 5107-5121 (2017) - [c51]Oussama Dhifallah, Christos Thrampoulidis, Yue M. Lu:
Phase retrieval via linear programming: Fundamental limits and algorithmic improvements. Allerton 2017: 1071-1077 - [c50]Oussama Dhifallah, Yue M. Lu:
Fundamental limits of phasemax for phase retrieval: A replica analysis. CAMSAP 2017: 1-5 - [c49]Yanting Ma, Yue M. Lu, Dror Baron:
Multiprocessor approximate message passing with column-wise partitioning. ICASSP 2017: 4765-4769 - [c48]Renan A. Rojas, Wangyu Luo, Víctor Murray, Yue M. Lu:
Learning optimal parameters for binary sensing image reconstruction algorithms. ICIP 2017: 2791-2795 - [c47]Yue M. Lu, Gen Li:
Spectral initialization for nonconvex estimation: High-dimensional limit and phase transitions. ISIT 2017: 3015-3019 - [c46]Chuang Wang, Yue M. Lu:
The Scaling Limit of High-Dimensional Online Independent Component Analysis. NIPS 2017: 6638-6647 - [i17]Yanting Ma, Yue M. Lu, Dror Baron:
Multiprocessor Approximate Message Passing with Column-Wise Partitioning. CoRR abs/1701.02578 (2017) - [i16]Yue M. Lu, Gen Li:
Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation. CoRR abs/1702.06435 (2017) - [i15]Oussama Dhifallah, Yue M. Lu:
Fundamental Limits of PhaseMax for Phase Retrieval: A Replica Analysis. CoRR abs/1708.03355 (2017) - [i14]Oussama Dhifallah, Christos Thrampoulidis, Yue M. Lu:
Phase Retrieval via Linear Programming: Fundamental Limits and Algorithmic Improvements. CoRR abs/1710.05234 (2017) - [i13]Chuang Wang, Yue M. Lu:
The Scaling Limit of High-Dimensional Online Independent Component Analysis. CoRR abs/1710.05384 (2017) - [i12]Chuang Wang, Jonathan Mattingly, Yue M. Lu:
Scaling Limit: Exact and Tractable Analysis of Online Learning Algorithms with Applications to Regularized Regression and PCA. CoRR abs/1712.04332 (2017) - 2016
- [j16]Chenhui Hu, Jorge Sepulcre, Keith A. Johnson, Georges El Fakhri, Yue M. Lu, Quanzheng Li:
Matched signal detection on graphs: Theory and application to brain imaging data classification. NeuroImage 125: 587-600 (2016) - [j15]Filip Sroubek, Jan Kamenický, Yue M. Lu:
Decomposition of Space-Variant Blur in Image Deconvolution. IEEE Signal Process. Lett. 23(3): 346-350 (2016) - [j14]Yuejie Chi, Yue M. Lu:
Kaczmarz Method for Solving Quadratic Equations. IEEE Signal Process. Lett. 23(9): 1183-1187 (2016) - [j13]Ivan Dokmanic, Yue M. Lu:
Sampling Sparse Signals on the Sphere: Algorithms and Applications. IEEE Trans. Signal Process. 64(1): 189-202 (2016) - [c45]Jon Onativia, Yue M. Lu, Pier Luigi Dragotti:
Prosparse denoise: Prony's based sparse pattern recovery in the presence of noise. ICASSP 2016: 4084-4088 - [c44]Chuang Wang, Yue M. Lu:
Online learning for sparse PCA in high dimensions: Exact dynamics and phase transitions. ITW 2016: 186-190 - [c43]Ariana Minot, Yue M. Lu, Na Li:
A parallel primal-dual interior-point method for DC optimal power flow. PSCC 2016: 1-7 - [i11]Stanley H. Chan, Todd E. Zickler, Yue M. Lu:
Demystifying Symmetric Smoothing Filters. CoRR abs/1601.00088 (2016) - [i10]Chuang Wang, Yue M. Lu:
Online Learning for Sparse PCA in High Dimensions: Exact Dynamics and Phase Transitions. CoRR abs/1609.02191 (2016) - [i9]Yue M. Lu, Jon Oñativia, Pier Luigi Dragotti:
Sparsity according to Prony: Average-Case Performance Analysis and Phase Transition. CoRR abs/1611.07971 (2016) - 2015
- [c42]Gen Li, Yuantao Gu, Yue M. Lu:
Phase retrieval using iterative projections: Dynamics in the large systems limit. Allerton 2015: 1114-1118 - [c41]Yuanxin Li, Yingsheng He, Yuejie Chi, Yue M. Lu:
Blind calibration of multi-channel samplers using sparse recovery. CAMSAP 2015: 33-36 - [c40]Zahra Sadeghipoor, Yue M. Lu, Sabine Süsstrunk:
Gradient-based correction of chromatic aberration in the joint acquisition of color and near-infrared images. Digital Photography 2015: 94040F - [c39]Zahra Sadeghipoor, Yue M. Lu, Erick Méndez, Sabine Süsstrunk:
Multiscale guided deblurring: Chromatic aberration correction in color and near-infrared imaging. EUSIPCO 2015: 2336-2340 - [c38]Ivan Dokmanic, Yue M. Lu:
Sampling spherical finite rate of innovation signals. ICASSP 2015: 5962-5966 - [c37]Jon Onativia, Yue M. Lu, Pier Luigi Dragotti:
Sparsity pattern recovery using FRI methods. ICASSP 2015: 5967-5971 - [c36]Stanley H. Chan, Todd E. Zickler, Yue M. Lu:
Understanding symmetric smoothing filters via Gaussian mixtures. ICIP 2015: 2500-2504 - [i8]Chuang Wang, Ameya Agaskar, Yue M. Lu:
Randomized Kaczmarz Algorithm for Inconsistent Linear Systems: An Exact MSE Analysis. CoRR abs/1502.00190 (2015) - [i7]Ivan Dokmanic, Yue M. Lu:
Sampling Sparse Signals on the Sphere: Algorithms and Applications. CoRR abs/1502.07577 (2015) - [i6]Ameya Agaskar, Yue M. Lu:
Optimal Detection of Random Walks on Graphs: Performance Analysis via Statistical Physics. CoRR abs/1504.06924 (2015) - 2014
- [j12]Stanley H. Chan, Todd E. Zickler, Yue M. Lu:
Monte Carlo Non-Local Means: Random Sampling for Large-Scale Image Filtering. IEEE Trans. Image Process. 23(8): 3711-3725 (2014) - [j11]Pier Luigi Dragotti, Yue M. Lu:
On Sparse Representation in Fourier and Local Bases. IEEE Trans. Inf. Theory 60(12): 7888-7899 (2014) - [c35]Ameya Agaskar, Yue M. Lu:
Optimal hypothesis testing with combinatorial structure: Detecting random walks on graphs. ACSSC 2014: 733-737 - [c34]Ariana Minot, Yue M. Lu:
Separation of interleaved Markov chains. ACSSC 2014: 1757-1761 - [c33]Stanley H. Chan, Yue M. Lu:
Efficient image reconstruction for gigapixel quantum image sensors. GlobalSIP 2014: 312-316 - [c32]Ameya Agaskar, Chuang Wang, Yue M. Lu:
Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities. GlobalSIP 2014: 389-393 - [c31]Jon Onativia, Yue M. Lu, Pier Luigi Dragoni:
Finite dimensional FRI. ICASSP 2014: 1808-1812 - 2013
- [j10]Ameya Agaskar, Yue M. Lu:
A Spectral Graph Uncertainty Principle. IEEE Trans. Inf. Theory 59(7): 4338-4356 (2013) - [c30]Yue M. Lu:
Adaptive sensing and inference for single-photon imaging. CISS 2013: 1-6 - [c29]Yue M. Lu:
A framework for adaptive parameter estimation with finite memory. GlobalSIP 2013: 213-216 - [c28]Ameya Agaskar, Yue M. Lu:
ALARM: A logistic auto-regressive model for binary processes on networks. GlobalSIP 2013: 305-308 - [c27]Stanley H. Chan, Todd E. Zickler, Yue M. Lu:
Fast non-local filtering by random sampling: It works, especially for large images. ICASSP 2013: 1603-1607 - [c26]Zahra Sadeghipoor, Yue M. Lu, Sabine Süsstrunk:
A novel compressive sensing approach to simultaneously acquire color and near-infrared images on a single sensor. ICASSP 2013: 1646-1650 - [c25]Ameya Agaskar, Yue M. Lu:
Detecting randomwalks hidden in noise: Phase transition on large graphs. ICASSP 2013: 6377-6381 - [c24]Chenhui Hu, Lin Cheng, Jorge Sepulcre, Georges El Fakhri, Yue M. Lu, Quanzheng Li:
Matched Signal Detection on Graphs: Theory and Application to Brain Network Classification. IPMI 2013: 1-12 - [c23]Chenhui Hu, Lin Cheng, Jorge Sepulcre, Georges El Fakhri, Yue M. Lu, Quanzheng Li:
A graph theoretical regression model for brain connectivity learning of Alzheimer'S disease. ISBI 2013: 616-619 - [i5]Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli:
Phase Retrieval for Sparse Signals: Uniqueness Conditions. CoRR abs/1308.3058 (2013) - [i4]Pier Luigi Dragotti, Yue M. Lu:
On Sparse Representation in Fourier and Local Bases. CoRR abs/1310.6011 (2013) - [i3]Stanley H. Chan, Todd E. Zickler, Yue M. Lu:
Monte Carlo non local means: Random sampling for large-scale image filtering. CoRR abs/1312.7366 (2013) - 2012
- [j9]Minh N. Do, Yue M. Lu:
Multidimensional Filter Banks and Multiscale Geometric Representations. Found. Trends Signal Process. 5(3): 157-264 (2012) - [j8]Feng Yang, Yue M. Lu, Luciano Sbaiz, Martin Vetterli:
Bits From Photons: Oversampled Image Acquisition Using Binary Poisson Statistics. IEEE Trans. Image Process. 21(4): 1421-1436 (2012) - [c22]Zahra Sadeghipoor, Yue M. Lu, Sabine Süsstrunk:
Optimum spectral sensitivity functions for single sensor color imaging. Digital Photography 2012: 829904 - [c21]Ameya Agaskar, Yue M. Lu:
Uncertainty principles for signals defined on graphs: Bounds and characterizations. ICASSP 2012: 3493-3496 - [c20]Ying Xiong, Yue M. Lu:
Blind estimation and low-rate sampling of sparse mimo systems with common support. ICASSP 2012: 3893-3896 - [c19]Chenhui Hu, Lin Cheng, Yue M. Lu:
Graph-based regularization for color image demosaicking. ICIP 2012: 2769-2772 - [i2]Ameya Agaskar, Yue M. Lu:
A Spectral Graph Uncertainty Principle. CoRR abs/1206.6356 (2012) - 2011
- [c18]Yue M. Lu, Pier Luigi Dragotti, Martin Vetterli:
Localization of diffusive sources using spatiotemporal measurements. Allerton 2011: 1072-1076 - [c17]Ivan Dokmanic, Yue M. Lu, Martin Vetterli:
Can one hear the shape of a room: The 2-D polygonal case. ICASSP 2011: 321-324 - [c16]Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli:
Sampling and reconstructing diffusion fields with localized sources. ICASSP 2011: 4016-4019 - [c15]Yue M. Lu, Martin Vetterli:
Sparse spectral factorization: Unicity and reconstruction algorithms. ICASSP 2011: 5976-5979 - [c14]Zahra Sadeghipoor, Yue M. Lu, Sabine Süsstrunk:
Correlation-based joint acquisition and demosaicing of visible and near-infrared images. ICIP 2011: 3165-3168 - [i1]Feng Yang, Yue M. Lu, Luciano Sbaiz, Martin Vetterli:
Gigapixel Binary Sensing: Image Acquisition Using Oversampled One-Bit Poisson Statistics. CoRR abs/1106.0954 (2011) - 2010
- [j7]Yue M. Lu, Mina Karzand, Martin Vetterli:
Demosaicking by Alternating Projections: Theory and Fast One-Step Implementation. IEEE Trans. Image Process. 19(8): 2085-2098 (2010) - [j6]Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetterli:
Distributed sampling of signals linked by sparse filtering: theory and applications. IEEE Trans. Signal Process. 58(3): 1095-1109 (2010) - [c13]Feng Yang, Yue M. Lu, Luciano Sbaiz, Martin Vetterli:
An optimal algorithm for reconstructing images from binary measurements. Computational Imaging 2010: 75330 - [c12]Martin McCormick, Yue M. Lu, Martin Vetterli:
Learning sparse systems at sub-Nyquist rates: A frequency-domain approach. ICASSP 2010: 4018-4021
2000 – 2009
- 2009
- [j5]Yue M. Lu, Minh N. Do, Richard S. Laugesen:
A computable fourier condition generating alias-free sampling lattices. IEEE Trans. Signal Process. 57(5): 1768-1782 (2009) - [c11]Yue M. Lu, Mina Karzand, Martin Vetterli:
Iterative demosaicking accelerated: theory and fast noniterative implementations. Computational Imaging 2009: 72460 - [c10]Yue M. Lu, Martin Vetterli:
Optimal color filter array design: quantitative conditions and an efficient search procedure. Digital Photography 2009: 725009 - [c9]Yue M. Lu, Martin Vetterli:
Spatial super-resolution of a diffusion field by temporal oversampling in sensor networks. ICASSP 2009: 2249-2252 - [c8]Olivier Roy, Ali Hormati, Yue M. Lu, Martin Vetterli:
Distributed sensing of signals linked by sparse filtering. ICASSP 2009: 2409-2412 - [c7]Yue M. Lu, Clément Fredembach, Martin Vetterli, Sabine Süsstrunk:
Designing color filter arrays for the joint capture of visible and near-infrared images. ICIP 2009: 3797-3800 - 2008
- [j4]Yue M. Lu, Minh N. Do:
Sampling Signals from a Union of Subspaces. IEEE Signal Process. Mag. 25(2): 41-47 (2008) - [j3]Yue M. Lu, Minh N. Do:
A Mapping-Based Design for Nonsubsampled Hourglass Filter Banks in Arbitrary Dimensions. IEEE Trans. Signal Process. 56(4): 1466-1478 (2008) - [j2]Yue M. Lu, Minh N. Do:
A Theory for Sampling Signals From a Union of Subspaces. IEEE Trans. Signal Process. 56(6): 2334-2345 (2008) - [c6]Guillermo Barrenetxea, François Ingelrest, Yue M. Lu, Martin Vetterli:
Assessing the challenges of environmental signal processing through the sensorscope project. ICASSP 2008: 5149-5152 - 2007
- [b1]Yue M. Lu:
Multidimensional Geometrical Signal Representation: Constructions and Applications. University of Illinois Urbana-Champaign, USA, 2007 - [j1]Yue M. Lu, Minh N. Do:
Multidimensional Directional Filter Banks and Surfacelets. IEEE Trans. Image Process. 16(4): 918-931 (2007) - [c5]Nickolaus Mueller, Yue M. Lu, Minh N. Do:
Image interpolation using multiscale geometric representations. Computational Imaging 2007: 64980A - [c4]Yue M. Lu, Minh N. Do:
Finding Optimal Integral Sampling Lattices for a given Frequency Support in Multidimensions. ICIP (2) 2007: 165-168 - 2006
- [c3]Yue M. Lu, Minh N. Do:
A New Contourlet Transform with Sharp Frequency Localization. ICIP 2006: 1629-1632 - 2005
- [c2]Yue M. Lu, Minh N. Do:
The finer directional wavelet transform [image processing applications]. ICASSP (4) 2005: 573-576 - 2004
- [c1]Yue M. Lu, Minh N. Do:
A geometrical approach to sampling signals with finite rate of innovation. ICASSP (2) 2004: 565-568
Coauthor Index
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