Zijian Liu
14 papers · 2022–2026 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (21) π Conference Polyglot Β· Silver π¬ Deep Specialist (10) ποΈ Keyword Collector (62)
π₯
Unstoppable Β· Bronze
π
Renaissance Researcher
(6)
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(13)
Optimization & Theory Β· Machine Learning
(11)
Mathematics & Optimization
(10)
Optimization
(10)
Deep Learning
(3)
Learning Types
(3)
Optimization & Theory Β· Deep Learning
(3)
Reinforcement Learning
(2)
Methods
(2)
Artificial Intelligence
(1)
Computer Vision
(1)
Robotics
(1)
Speech & Audio
(1)
Analysis Β· Computer Vision
(1)
Analysis Β· Speech & Audio
(1)
Keywords
convergence rate
(6)
stochastic gradient descent
(4)
non-convex optimization
(3)
last-iterate convergence
(3)
convex optimization
(3)
variance reduction
(2)
shuffling gradient methods
(2)
heavy-tailed noise
(2)
high probability convergence
(2)
stochastic optimization
(2)
reinforcement learning
(2)
distributionally robust optimization
(2)
gradient clipping
(2)
random reshuffle
(2)
speaker recognition
(1)
incremental gradient
(1)
finite-sum optimization
(1)
robust reinforcement learning
(1)
pseudo labeling
(1)
semi-supervised learning
(1)
Papers
HTNav: A Hybrid Navigation Framework with Tiered Structure for Urban Aerial Vision-and-Language Navigation
CVPR 2026
Online Convex Optimization with Heavy Tails: Old Algorithms, New Regrets, and Applications
ALT 2026
Random Reshuffling Dominates Stochastic Gradient Descent
COLT 2026
Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization
ICML 2025
Int*-Match: Balancing Intra-Class Compactness and Inter-Class Discrepancy for Semi-Supervised Speaker Recognition
AAAI 2025
Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
ICLR 2025
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
ICML 2024
On the Last-Iterate Convergence of Shuffling Gradient Methods
ICML 2024
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
ICLR 2024
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise
COLT 2023
High Probability Convergence of Stochastic Gradient Methods
ICML 2023
On the Convergence of AdaGrad(Norm) on R^d: Beyond Convexity, Non-Asymptotic Rate and Acceleration
ICLR 2023
Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction
ICML 2022
Distributionally Robust Q-Learning
ICML 2022