Yue M. Lu

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 70

Top Venues

CoRR

ICASSP

IEEE Trans. Inf. Theory

IEEE Trans. Signal Process.

Publications

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 (2024)
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 (2024)
Yue M. Lu, Mary I. Letey, Jacob A. Zavatone-Veth, Anindita Maiti, Cengiz Pehlevan
Asymptotic theory of in-context learning by linear attention. CoRR (2024)
Hong Hu, Yue M. Lu, Theodor Misiakiewicz
Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime. CoRR (2024)
Yue M. Lu
Keynote Speaker #2 : Exploring and exploiting the universality phenomenon in high-dimensional estimation and learning. ICCAIS (2023)
Hong Hu, Yue M. Lu
Universality Laws for High-Dimensional Learning With Random Features. IEEE Trans. Inf. Theory 69 (3) (2023)
Burak Çakmak, Yue M. Lu, Manfred Opper
Analysis of Random Sequential Message Passing Algorithms for Approximate Inference. CoRR (2022)
Hong Hu, Yue M. Lu
Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime. CoRR (2022)
Hong Hu, Yue M. Lu
SLOPE for Sparse Linear Regression: Asymptotics and Optimal Regularization. IEEE Trans. Inf. Theory 68 (11) (2022)
Rishabh Dudeja, Subhabrata Sen, Yue M. Lu
Spectral Universality of Regularized Linear Regression with Nearly Deterministic Sensing Matrices. CoRR (2022)
Oussama Dhifallah, Yue M. Lu
Phase Transitions in Transfer Learning for High-Dimensional Perceptrons. CoRR (2021)
Oussama Dhifallah, Yue M. Lu
On the Inherent Regularization Effects of Noise Injection During Training. CoRR (2021)
Yue M. Lu
Householder Dice: A Matrix-Free Algorithm for Simulating Dynamics on Gaussian and Random Orthogonal Ensembles. CoRR (2021)
Oussama Dhifallah, Yue M. Lu
Phase Transitions in Transfer Learning for High-Dimensional Perceptrons. Entropy 23 (4) (2021)
Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
Construction of optimal spectral methods in phase retrieval. MSML (2021)
Yue M. Lu
Householder Dice: A Matrix-Free Algorithm for Simulating Dynamics on Gaussian and Random Orthogonal Ensembles. IEEE Trans. Inf. Theory 67 (12) (2021)
Oussama Dhifallah, Yue M. Lu
On the Inherent Regularization Effects of Noise Injection During Training. ICML (2021)
Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. NeurIPS (2020)
Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
Construction of optimal spectral methods in phase retrieval. CoRR (2020)
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) (2020)
Hong Hu, Yue M. Lu
The Limiting Poisson Law of Massive MIMO Detection With Box Relaxation. IEEE J. Sel. Areas Inf. Theory 1 (3) (2020)
Hong Hu, Yue M. Lu
Universality Laws for High-Dimensional Learning with Random Features. CoRR (2020)
Francesca Mignacco, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
The role of regularization in classification of high-dimensional noisy Gaussian mixture. CoRR (2020)
Hong Hu, Yue M. Lu
The Limiting Poisson Law of Massive MIMO Detection with Box Relaxation. CoRR (2020)
Oussama Dhifallah, Yue M. Lu
A Precise Performance Analysis of Learning with Random Features. CoRR (2020)
Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. CoRR (2020)
Chuang Wang, Hong Hu, Yue M. Lu
A Solvable High-Dimensional Model of GAN. NeurIPS (2019)
Yuejie Chi, Yue M. Lu, Yuxin Chen
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. IEEE Trans. Signal Process. 67 (20) (2019)
Wangyu Luo, Wael Alghamdi, Yue M. Lu
Optimal Spectral Initialization for Signal Recovery With Applications to Phase Retrieval. IEEE Trans. Signal Process. 67 (9) (2019)
Luca Saglietti, Yue M. Lu, Carlo Lucibello
Generalized Approximate Survey Propagation for High-Dimensional Estimation. CoRR (2019)
Hong Hu, Yue M. Lu
Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression. CoRR (2019)
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) (2019)
Hong Hu, Yue M. Lu
Asymptotics and Optimal Designs of SLOPE for Sparse Linear Regression. ISIT (2019)
Carlo Lucibello, Luca Saglietti, Yue M. Lu
Generalized Approximate Survey Propagation for High-Dimensional Estimation. ICML (2019)
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) (2019)
Gilles Baechler, Miranda Krekovic, Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli
Super Resolution Phase Retrieval for Sparse Signals. CoRR (2018)
Yuejie Chi, Yue M. Lu, Yuxin Chen
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. CoRR (2018)
Dror Simon, Jeremias Sulam, Yaniv Romano, Yue M. Lu, Michael Elad
Improving Pursuit Algorithms Using Stochastic Resonance. CoRR (2018)
Chuang Wang, Yonina C. Eldar, Yue M. Lu
Subspace Estimation from Incomplete Observations: A High-Dimensional Analysis. CoRR (2018)
Laura Balzano, Yuejie Chi, Yue M. Lu
Streaming PCA and Subspace Tracking: The Missing Data Case. Proc. IEEE 106 (8) (2018)
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) (2018)
Hong Hu, Yue M. Lu
Online Power Iteration For Subspace Estimation Under Incomplete Observations: Limiting Dynamics And Phase Transitions. SSP (2018)
Wangyu Luo, Wael Alghamdi, Yue M. Lu
Optimal Spectral Initialization for Signal Recovery with Applications to Phase Retrieval. CoRR (2018)
Laura Balzano, Yuejie Chi, Yue M. Lu
Streaming PCA and Subspace Tracking: The Missing Data Case. CoRR (2018)
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) (2018)
Oussama Dhifallah, Christos Thrampoulidis, Yue M. Lu
Phase Retrieval via Polytope Optimization: Geometry, Phase Transitions, and New Algorithms. CoRR (2018)
Chuang Wang, Hong Hu, Yue M. Lu
A Solvable High-Dimensional Model of GAN. CoRR (2018)
Yue M. Lu, Gen Li
Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation. CoRR (2017)
Stanley H. Chan, Todd E. Zickler, Yue M. Lu
Understanding Symmetric Smoothing Filters: A Gaussian Mixture Model Perspective. IEEE Trans. Image Process. 26 (11) (2017)
Chuang Wang, Yue M. Lu
The Scaling Limit of High-Dimensional Online Independent Component Analysis. NIPS (2017)
Yanting Ma, Yue M. Lu, Dror Baron
Multiprocessor Approximate Message Passing with Column-Wise Partitioning. CoRR (2017)
Yue M. Lu, Gen Li
Spectral initialization for nonconvex estimation: High-dimensional limit and phase transitions. ISIT (2017)
Yanting Ma, Yue M. Lu, Dror Baron
Multiprocessor approximate message passing with column-wise partitioning. ICASSP (2017)
Oussama Dhifallah, Christos Thrampoulidis, Yue M. Lu
Phase Retrieval via Linear Programming: Fundamental Limits and Algorithmic Improvements. CoRR (2017)
Oussama Dhifallah, Yue M. Lu
Fundamental Limits of PhaseMax for Phase Retrieval: A Replica Analysis. CoRR (2017)
Renan A. Rojas, Wangyu Luo, Víctor Murray, Yue M. Lu
Learning optimal parameters for binary sensing image reconstruction algorithms. ICIP (2017)
Chuang Wang, Yue M. Lu
The Scaling Limit of High-Dimensional Online Independent Component Analysis. CoRR (2017)
Oussama Dhifallah, Yue M. Lu
Fundamental limits of phasemax for phase retrieval: A replica analysis. CAMSAP (2017)
Oussama Dhifallah, Christos Thrampoulidis, Yue M. Lu
Phase retrieval via linear programming: Fundamental limits and algorithmic improvements. Allerton (2017)
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 (2017)
Yuejie Chi, Yue M. Lu
Kaczmarz Method for Solving Quadratic Equations. IEEE Signal Process. Lett. 23 (9) (2016)
Jon Onativia, Yue M. Lu, Pier Luigi Dragotti
Prosparse denoise: Prony's based sparse pattern recovery in the presence of noise. ICASSP (2016)
Filip Sroubek, Jan Kamenický, Yue M. Lu
Decomposition of Space-Variant Blur in Image Deconvolution. IEEE Signal Process. Lett. 23 (3) (2016)
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 (2016)
Ariana Minot, Yue M. Lu, Na Li
A parallel primal-dual interior-point method for DC optimal power flow. PSCC (2016)
Chuang Wang, Yue M. Lu
Online learning for sparse PCA in high dimensions: Exact dynamics and phase transitions. ITW (2016)
Chuang Wang, Yue M. Lu
Online Learning for Sparse PCA in High Dimensions: Exact Dynamics and Phase Transitions. CoRR (2016)
Yue M. Lu, Jon Oñativia, Pier Luigi Dragotti
Sparsity according to Prony: Average-Case Performance Analysis and Phase Transition. CoRR (2016)
Ivan Dokmanic, Yue M. Lu
Sampling Sparse Signals on the Sphere: Algorithms and Applications. IEEE Trans. Signal Process. 64 (1) (2016)
Stanley H. Chan, Todd E. Zickler, Yue M. Lu
Demystifying Symmetric Smoothing Filters. CoRR (2016)
Ivan Dokmanic, Yue M. Lu
Sampling spherical finite rate of innovation signals. ICASSP (2015)
Ivan Dokmanic, Yue M. Lu
Sampling Sparse Signals on the Sphere: Algorithms and Applications. CoRR (2015)
Ameya Agaskar, Yue M. Lu
Optimal Detection of Random Walks on Graphs: Performance Analysis via Statistical Physics. CoRR (2015)
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)
Yuanxin Li, Yingsheng He, Yuejie Chi, Yue M. Lu
Blind calibration of multi-channel samplers using sparse recovery. CAMSAP (2015)
Chuang Wang, Ameya Agaskar, Yue M. Lu
Randomized Kaczmarz Algorithm for Inconsistent Linear Systems: An Exact MSE Analysis. CoRR (2015)
Zahra Sadeghipoor, Yue M. Lu, Erick Méndez, Sabine Süsstrunk
Multiscale guided deblurring: Chromatic aberration correction in color and near-infrared imaging. EUSIPCO (2015)
Stanley H. Chan, Todd E. Zickler, Yue M. Lu
Understanding symmetric smoothing filters via Gaussian mixtures. ICIP (2015)
Gen Li, Yuantao Gu, Yue M. Lu
Phase retrieval using iterative projections: Dynamics in the large systems limit. Allerton (2015)
Jon Onativia, Yue M. Lu, Pier Luigi Dragotti
Sparsity pattern recovery using FRI methods. ICASSP (2015)
Pier Luigi Dragotti, Yue M. Lu
On Sparse Representation in Fourier and Local Bases. IEEE Trans. Inf. Theory 60 (12) (2014)
Ameya Agaskar, Chuang Wang, Yue M. Lu
Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities. GlobalSIP (2014)
Stanley H. Chan, Yue M. Lu
Efficient image reconstruction for gigapixel quantum image sensors. GlobalSIP (2014)
Ariana Minot, Yue M. Lu
Separation of interleaved Markov chains. ACSSC (2014)
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) (2014)
Jon Onativia, Yue M. Lu, Pier Luigi Dragoni
Finite dimensional FRI. ICASSP (2014)
Ameya Agaskar, Yue M. Lu
Optimal hypothesis testing with combinatorial structure: Detecting random walks on graphs. ACSSC (2014)
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)
Pier Luigi Dragotti, Yue M. Lu
On Sparse Representation in Fourier and Local Bases. CoRR (2013)
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)
Yue M. Lu
A framework for adaptive parameter estimation with finite memory. GlobalSIP (2013)
Ameya Agaskar, Yue M. Lu
Detecting randomwalks hidden in noise: Phase transition on large graphs. ICASSP (2013)
Stanley H. Chan, Todd E. Zickler, Yue M. Lu
Fast non-local filtering by random sampling: It works, especially for large images. ICASSP (2013)
Ameya Agaskar, Yue M. Lu
A Spectral Graph Uncertainty Principle. IEEE Trans. Inf. Theory 59 (7) (2013)
Stanley H. Chan, Todd E. Zickler, Yue M. Lu
Monte Carlo non local means: Random sampling for large-scale image filtering. CoRR (2013)
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)
Juri Ranieri, Amina Chebira, Yue M. Lu, Martin Vetterli
Phase Retrieval for Sparse Signals: Uniqueness Conditions. CoRR (2013)
Yue M. Lu
Adaptive sensing and inference for single-photon imaging. CISS (2013)
Ameya Agaskar, Yue M. Lu
ALARM: A logistic auto-regressive model for binary processes on networks. GlobalSIP (2013)
Minh N. Do, Yue M. Lu
Multidimensional Filter Banks and Multiscale Geometric Representations. Found. Trends Signal Process. 5 (3) (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Yue M. Lu