Xiao-Tong Yuan
16 papers · 2013–2024 · 9 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (26) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Topic Evolution
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Keyword Champion
(2)
ποΈ
Keyword Collector
(81)
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Century Club Β· Bronze
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Prolific Year Β· Productive
Top co-authors
Research topics
Machine Learning
(14)
Mathematics & Optimization
(12)
Optimization
(12)
Optimization & Theory Β· Machine Learning
(11)
Core Methods
(5)
Deep Learning
(3)
Learning Types
(2)
Mathematics
(2)
Optimization & Theory Β· Deep Learning
(2)
Artificial Intelligence
(1)
Computer Vision
(1)
Analysis
(1)
Core AI
(1)
Learning Paradigms
(1)
Models
(1)
Keywords
convex optimization
(4)
sparse recovery
(4)
compressed sensing
(3)
non-convex optimization
(3)
sparsity-constrained optimization
(2)
cardinality constraint
(2)
gradient descent
(2)
newton method
(2)
greedy algorithm
(2)
dual optimization
(2)
iterative hard thresholding
(2)
hard thresholding
(2)
mini-batch optimization
(2)
duality theory
(2)
sparse learning
(1)
logistic regression
(1)
contrastive learning
(1)
compressive sensing
(1)
principal component analysis
(1)
stochastic optimization
(1)
Papers
Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery
AAAI 2024
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation
JMLR 2023
DeepACG: Co-Saliency Detection via Semantic-Aware Contrast Gromov-Wasserstein Distance
CVPR 2021
Task similarity aware meta learning: theory-inspired improvement on MAML
UAI 2021
Dual Iterative Hard Thresholding
JMLR 2020
Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization
ICML 2020
Meta-Learning with Network Pruning
ECCV 2020
Nearly Non-Expansive Bounds for Mahalanobis Hard Thresholding
COLT 2020
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond
JMLR 2020
Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning
AISTATS 2019
Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds
AISTATS 2019
Gradient Hard Thresholding Pursuit
JMLR 2018
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
ICML 2017
Additive Nearest Neighbor Feature Maps
ICCV 2015
Newton Greedy Pursuit: A Quadratic Approximation Method for Sparsity-Constrained Optimization
CVPR 2014
Truncated Power Method for Sparse Eigenvalue Problems
JMLR 2013