Weizhong Zhang
36 papers · 2017–2026 · 9 conferences · across top CS/AI conferences
Achievements
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(12)
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(8)
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Unstoppable
(9)
Conferences
AAAI (9)
CVPR (7)
ICML (7)
ICLR (5)
NIPS (4)
ACL (1)
AISTATS (1)
JMLR (1)
NAACL (1)
Top co-authors
Keywords
model compression
(5)
sparse learning
(3)
coreset selection
(3)
neural network optimization
(3)
feature selection
(3)
federated learning
(3)
diffusion model
(2)
bilevel optimization
(2)
client heterogeneity
(2)
distributed learning
(2)
domain generalization
(2)
3d pose estimation
(2)
generative model
(2)
support vector machine
(2)
human pose estimation
(2)
neural network pruning
(2)
image generation
(2)
neural network training
(2)
model aggregation
(2)
weight pruning
(2)
Papers
Investigating Data Pruning for Pretraining Biological Foundation Models at Scale
AAAI 2026
Advanced Black-Box Tuning of Large Language Models with Limited API Calls
AAAI 2026
Explore and Establish Synergistic Effects Between Weight Pruning and Coreset Selection in Neural Network Training
AAAI 2026
DreamText: High Fidelity Scene Text Synthesis
CVPR 2025
Optimized Gradient Clipping for Noisy Label Learning
AAAI 2025
Achieving Ensemble-Like Performance in a Single Model: A Feature Diversification Framework for Image-Text Matching
AAAI 2025
Expanding the Scope of Negatives: Boosting Image-Text Matching with Negatives Distribution Guided Learning
AAAI 2025
Bypass Back-propagation: Optimization-based Structural Pruning for Large Language Models via Policy Gradient
ACL 2025
Population Normalization for Federated Learning
CVPR 2025
Towards Robust Influence Functions with Flat Validation Minima
ICML 2025
TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data
NAACL 2025
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost
ICLR 2024
Efficient Denoising Diffusion via Probabilistic Masking
ICML 2024
Point Cloud Part Editing: Segmentation, Generation, Assembly, and Selection
AAAI 2024
High-fidelity Person-centric Subject-to-Image Synthesis
CVPR 2024
Low Precision Local Training is Enough for Federated Learning
NIPS 2024
FusionFormer: A Concise Unified Feature Fusion Transformer for 3D Pose Estimation
AAAI 2024
Spurious Feature Diversification Improves Out-of-distribution Generalization
ICLR 2024
PoseIRM: Enhance 3D Human Pose Estimation on Unseen Camera Settings via Invariant Risk Minimization
CVPR 2024
DynaFed: Tackling Client Data Heterogeneity With Global Dynamics
CVPR 2023
A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond
ICLR 2023
DynaMS: Dyanmic Margin Selection for Efficient Deep Learning
ICLR 2023
Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning
ICLR 2023
Finding Dynamics Preserving Adversarial Winning Tickets
AISTATS 2022
Model Agnostic Sample Reweighting for Out-of-Distribution Learning
ICML 2022
Sparse Invariant Risk Minimization
ICML 2022
Probabilistic Bilevel Coreset Selection
ICML 2022
Efficient Neural Network Training via Forward and Backward Propagation Sparsification
NIPS 2021
Effective Sparsification of Neural Networks With Global Sparsity Constraint
CVPR 2021
How to Characterize The Landscape of Overparameterized Convolutional Neural Networks
NIPS 2020
Gradient Method for Continuous Influence Maximization with Budget-Saving Considerations
AAAI 2020
A Sufficient Condition for Convergences of Adam and RMSProp
CVPR 2019
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
JMLR 2019
Safe Element Screening for Submodular Function Minimization
ICML 2018
Parsimonious Quantile Regression of Financial Asset Tail Dynamics via Sequential Learning
NIPS 2018
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
ICML 2017