Guanghui Wang
44 papers · 2018–2026 · 15 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (15) π Conference Polyglot (13)
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Keyword Pioneer
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Hot Topic Early Bird
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Academic Marathon
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Dynamic Duo
(16)
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Grand Slam
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Deep Specialist
(13)
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Unstoppable
(9)
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Conference Pioneer
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Keyword Collector
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Century Club
(41)
Conferences
NIPS (6)
ICML (5)
JMLR (5)
WACV (5)
IJCAI (4)
AAAI (3)
AISTATS (3)
CVPR (3)
ICLR (3)
ALT (2)
ACL (1)
COLING (1)
COLT (1)
ICCV (1)
UAI (1)
Top co-authors
Keywords
online learning
(9)
regret bound
(9)
online convex optimization
(6)
strong convexity
(3)
convex optimization
(3)
gradient descent
(3)
dynamic regret
(3)
neural network optimization
(3)
riemannian manifold
(3)
upper confidence bound
(2)
sequential decision-making
(2)
representation learning
(2)
strongly convex
(2)
online optimization
(2)
change-point detection
(2)
model selection
(2)
stochastic optimization
(2)
attention mechanism
(2)
statistical inference
(2)
convolutional neural network
(2)
Papers
SIAM: Synchronous Interaction Attention for Human Mesh Recovery
WACV 2026
Last-iterate Convergence for Symmetric, General-sum, $2 \times 2$ Games Under The Exponential Weights Dynamic
ALT 2026
Better Literary Translation: A Multi-Aspect Data Generation and LLM Training Approach
ACL 2026
Multi-distribution Learning: From Worst-Case Optimality to Lexicographic Min-Max Optimality
ALT 2026
Learning Imbalanced Data with Beneficial Label Noise
ICML 2025
Autoencoder-Based Hybrid Replay for Class-Incremental Learning
ICML 2025
Federated Class-Incremental Learning: A Hybrid Approach Using Latent Exemplars and Data-Free Techniques to Address Local and Global Forgetting
ICLR 2025
Universal Online Convex Optimization Meets Second-order Bounds
JMLR 2025
Exposure-slot: Exposure-centric Representations Learning with Slot-in-Slot Attention for Region-aware Exposure Correction
CVPR 2025
DEGAP: Dual Event-Guided Adaptive Prefixes for Templated-Based Event Argument Extraction with Slot Querying
COLING 2025
Reliever: Relieving the Burden of Costly Model Fits for Changepoint Detection
JMLR 2025
ABKD: Pursuing a Proper Allocation of the Probability Mass in Knowledge Distillation via $Ξ±$-$Ξ²$-Divergence
ICML 2025
Keypoints as Dynamic Centroids for Unified Human Pose and Segmentation
IJCAI 2025
Extragradient Type Methods for Riemannian Variational Inequality Problems
AISTATS 2024
Zipper: Addressing Degeneracy in Algorithm-Agnostic Inference
NIPS 2024
Uncertainty Quantification for Data-Driven Change-Point Learning via Cross-Validation
AAAI 2024
Low-Rank Matrix Estimation in the Presence of Change-Points
JMLR 2024
Riemannian Projection-free Online Learning
NIPS 2023
Faster Margin Maximization Rates for Generic Optimization Methods
NIPS 2023
On Accelerated Perceptrons and Beyond
ICLR 2023
Accumulated Trivial Attention Matters in Vision Transformers on Small Datasets
WACV 2023
Minimizing Dynamic Regret on Geodesic Metric Spaces
COLT 2023
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization
AISTATS 2022
Adaptive Oracle-Efficient Online Learning
NIPS 2022
Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks With Implicit Gradients
CVPR 2022
A Simple yet Universal Strategy for Online Convex Optimization
ICML 2022
Projection-free Distributed Online Learning with Sublinear Communication Complexity
JMLR 2022
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions
NIPS 2021
Stochastic Graphical Bandits with Adversarial Corruptions
AAAI 2021
Bandit Convex Optimization in Non-stationary Environments
JMLR 2021
Online Convex Optimization with Continuous Switching Constraint
NIPS 2021
DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer
ICCV 2021
SAdam: A Variant of Adam for Strongly Convex Functions
ICLR 2020
Plug-and-Play Rescaling Based Crowd Counting in Static Images
WACV 2020
Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization
AAAI 2020
Bandit Convex Optimization in Non-stationary Environments
AISTATS 2020
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs
IJCAI 2020
Towards Learning Affine-Invariant Representations via Data-Efficient CNNs
WACV 2020
Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters
WACV 2020
Multi-Objective Generalized Linear Bandits
IJCAI 2019
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards
ICML 2019
Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization
UAI 2019
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning
CVPR 2018
Minimizing Adaptive Regret with One Gradient per Iteration
IJCAI 2018