Haotao Wang
18 papers · 2019–2024 · 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.
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Research topics
Machine Learning
(17)
Deep Learning
(10)
Application Areas
(10)
Artificial Intelligence
(9)
Learning Types Β· Machine Learning
(9)
Core AI
(6)
Techniques
(5)
Optimization & Theory Β· Machine Learning
(4)
Architectures
(3)
Core Methods
(3)
Learning Paradigms
(3)
Learning Types Β· Deep Learning
(3)
Optimization & Theory Β· Deep Learning
(3)
Security & Privacy
(1)
Differential Privacy
(1)
Keywords
adversarial robustness
(5)
model compression
(4)
adversarial training
(4)
out-of-distribution detection
(3)
batch normalization
(3)
neural network
(3)
federated learning
(2)
non-iid data
(2)
knowledge distillation
(1)
model robustness
(1)
link prediction
(1)
graph representation learning
(1)
feature selection
(1)
data augmentation
(1)
ensemble learning
(1)
contrastive learning
(1)
network pruning
(1)
image reconstruction
(1)
neural architecture search
(1)
anomaly detection
(1)
Papers
Safe and Robust Watermark Injection with a Single OoD Image
ICLR 2024
Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning
AAAI 2023
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling
NeurIPS 2023
Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection
ICLR 2023
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization
ICLR 2022
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition
ICML 2022
Removing Batch Normalization Boosts Adversarial Training
ICML 2022
Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork
NeurIPS 2022
AugMax: Adversarial Composition of Random Augmentations for Robust Training
NeurIPS 2021
Learning Model-Based Privacy Protection under Budget Constraints
AAAI 2021
Troubleshooting Blind Image Quality Models in the Wild
CVPR 2021
UMEC: Unified model and embedding compression for efficient recommendation systems
ICLR 2021
AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
ICML 2020
GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework
ECCV 2020
I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively
ICLR 2020
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free
NeurIPS 2020
Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference
ICLR 2020
Model Compression with Adversarial Robustness: A Unified Optimization Framework
NeurIPS 2019