research
∙
03/23/2023
Predicting the Future of the CMS Detector: Crystal Radiation Damage and Machine Learning at the LHC
The 75,848 lead tungstate crystals in CMS experiment at the CERN Large H...
share
research
∙
03/23/2023
Optimization and Optimizers for Adversarial Robustness
Empirical robustness evaluation (RE) of deep learning models against adv...
research
∙
03/06/2023
Robust Autoencoders for Collective Corruption Removal
Robust PCA is a standard tool for learning a linear subspace in the pres...
research
∙
02/17/2023
Welfare and Fairness Dynamics in Federated Learning: A Client Selection Perspective
Federated learning (FL) is a privacy-preserving learning technique that ...
research
∙
02/15/2023
Interpretable Deep Learning Methods for Multiview Learning
Technological advances have enabled the generation of unique and complem...
research
∙
11/02/2022
Practical Phase Retrieval Using Double Deep Image Priors
Phase retrieval (PR) concerns the recovery of complex phases from comple...
research
∙
10/03/2022
NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learning
Imposing explicit constraints is relatively new but increasingly pressin...
research
∙
10/02/2022
Optimization for Robustness Evaluation beyond ℓ_p Metrics
Empirical evaluation of deep learning models against adversarial attacks...
research
∙
08/18/2022
Blind Image Deblurring with Unknown Kernel Size and Substantial Noise
Blind image deblurring (BID) has been extensively studied in computer vi...
research
∙
12/11/2021
Early Stopping for Deep Image Prior
Deep image prior (DIP) and its variants have showed remarkable potential...
research
∙
11/27/2021
NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning
Optimizing nonconvex (NCVX) problems, especially nonsmooth and constrain...
research
∙
10/23/2021
Self-Validation: Early Stopping for Single-Instance Deep Generative Priors
Recent works have shown the surprising effectiveness of deep generative ...
research
∙
06/09/2021
Rethink Transfer Learning in Medical Image Classification
Transfer learning (TL) with deep convolutional neural networks (DCNNs) h...
research
∙
06/09/2021
Phase Retrieval using Single-Instance Deep Generative Prior
Several deep learning methods for phase retrieval exist, but most of the...
research
∙
06/03/2021
A Prospective Observational Study to Investigate Performance of a Chest X-ray Artificial Intelligence Diagnostic Support Tool Across 12 U.S. Hospitals
Importance: An artificial intelligence (AI)-based model to predict COVID...
research
∙
05/24/2021
Towards Low-Photon Nanoscale Imaging: Holographic Phase Retrieval via Maximum Likelihood Optimization
A new algorithmic framework is presented for holographic phase retrieval...
research
∙
03/20/2020
Inverse Problems, Deep Learning, and Symmetry Breaking
In many physical systems, inputs related by intrinsic system symmetries ...
research
∙
02/07/2019
Dual-Reference Design for Holographic Coherent Diffraction Imaging
A new reference design is introduced for Holographic Coherent Diffractio...
research
∙
01/19/2019
Holographic Phase Retrieval and Optimal Reference Design
A general mathematical framework and recovery algorithm is presented for...
research
∙
10/25/2018
Subgradient Descent Learns Orthogonal Dictionaries
This paper concerns dictionary learning, i.e., sparse coding, a fundamen...
research
∙
08/10/2018
Weighted AdaGrad with Unified Momentum
Integrating adaptive learning rate and momentum techniques into SGD lead...
research
∙
12/06/2017
A Local Analysis of Block Coordinate Descent for Gaussian Phase Retrieval
While convergence of the Alternating Direction Method of Multipliers (AD...
research
∙
02/22/2016
A Geometric Analysis of Phase Retrieval
Can we recover a complex signal from its Fourier magnitudes? More genera...
research
∙
11/15/2015
Complete Dictionary Recovery over the Sphere II: Recovery by Riemannian Trust-region Method
We consider the problem of recovering a complete (i.e., square and inver...
research
∙
11/11/2015
Complete Dictionary Recovery over the Sphere I: Overview and the Geometric Picture
We consider the problem of recovering a complete (i.e., square and inver...
research
∙
10/21/2015
When Are Nonconvex Problems Not Scary?
In this note, we focus on smooth nonconvex optimization problems that ob...
research
∙
04/26/2015
Complete Dictionary Recovery over the Sphere
We consider the problem of recovering a complete (i.e., square and inver...
research
∙
12/15/2014
Finding a sparse vector in a subspace: Linear sparsity using alternating directions
Is it possible to find the sparsest vector (direction) in a generic subs...
research
∙
11/05/2012
Efficient Point-to-Subspace Query in ℓ^1: Theory and Applications in Computer Vision
Motivated by vision tasks such as robust face and object recognition, we...
research
∙
08/02/2012
Efficient Point-to-Subspace Query in ℓ^1 with Application to Robust Object Instance Recognition
Motivated by vision tasks such as robust face and object recognition, we...
research
∙
11/22/2010
Closed-Form Solutions to A Category of Nuclear Norm Minimization Problems
It is an efficient and effective strategy to utilize the nuclear norm ap...
research
∙
10/27/2010
Selective Image Super-Resolution
In this paper we propose a vision system that performs image Super Resol...
research
∙
10/14/2010
Robust Recovery of Subspace Structures by Low-Rank Representation
In this work we address the subspace recovery problem. Given a set of da...
research
∙
09/20/2010
