Xingguo Li
16 papers · 2015–2020 · 5 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Bronze π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (27)
π€
Dynamic Duo
(10)
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(83)
π₯
Unstoppable Β· Bronze
Top co-authors
Research topics
Machine Learning
(15)
Optimization & Theory Β· Machine Learning
(14)
Mathematics & Optimization
(8)
Core Methods
(7)
Optimization
(7)
Learning Types
(4)
Computer Vision
(1)
Deep Learning
(1)
Reinforcement Learning
(1)
Architectures
(1)
Core AI
(1)
Mathematics
(1)
Methods
(1)
Optimization & Theory Β· Deep Learning
(1)
Techniques
(1)
Keywords
non-convex optimization
(4)
sparse learning
(3)
stochastic optimization
(3)
iteration complexity
(2)
strongly convex
(2)
sparse coding
(2)
convergence analysis
(2)
robust optimization
(1)
compressed sensing
(1)
active learning
(1)
matrix factorization
(1)
convex optimization
(1)
compressive sensing
(1)
black-box optimization
(1)
representation learning
(1)
sparse estimation
(1)
sample complexity
(1)
sequential decision making
(1)
adversarial training
(1)
online learning
(1)
Papers
On Computation and Generalization of Generative Adversarial Imitation Learning
ICLR 2020
On Generalization Bounds of a Family of Recurrent Neural Networks
AISTATS 2020
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality
NeurIPS 2020
Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning
NeurIPS 2020
NOODL: Provable Online Dictionary Learning and Sparse Coding
ICLR 2019
On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition
AISTATS 2019
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python
JMLR 2019
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
NeurIPS 2019
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
JMLR 2018
Towards Black-box Iterative Machine Teaching
ICML 2018
Deep Hyperspherical Learning
NeurIPS 2017
Near Optimal Sketching of Low-Rank Tensor Regression
NeurIPS 2017
On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning
NeurIPS 2017
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
AISTATS 2016
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning
ICML 2016
The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R
JMLR 2015