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04/27/2023
Moderately Distributional Exploration for Domain Generalization
Domain generalization (DG) aims to tackle the distribution shift between...
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03/24/2023
Hard Sample Matters a Lot in Zero-Shot Quantization
Zero-shot quantization (ZSQ) is promising for compressing and accelerati...
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03/03/2023
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training
Federated Learning (FL) enables collaborations among clients for train m...
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09/29/2022
Towards Lightweight Black-Box Attacks against Deep Neural Networks
Black-box attacks can generate adversarial examples without accessing th...
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06/15/2022
Pareto Invariant Risk Minimization
Despite the success of invariant risk minimization (IRM) in tackling the...
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06/06/2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
In federated learning (FL), model performance typically suffers from cli...
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05/06/2022
Prompt Distribution Learning
We present prompt distribution learning for effectively adapting a pre-t...
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02/16/2022
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
Recently Graph Injection Attack (GIA) emerges as a practical attack scen...
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02/11/2022
Invariance Principle Meets Out-of-Distribution Generalization on Graphs
Despite recent developments in using the invariance principle from causa...
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06/11/2021
