research
∙
04/15/2023
Practical Differentially Private and Byzantine-resilient Federated Learning
Privacy and Byzantine resilience are two indispensable requirements for ...
share
research
∙
03/13/2023
SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency
This work presents an effective depth-consistency self-prompt Transforme...
research
∙
10/07/2022
1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct)
Recent years have seen advances on principles and guidance relating to a...
research
∙
03/29/2022
OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks
This paper proposes a new eXplanation framework, called OrphicX, for gen...
research
∙
01/23/2022
Towards Private Learning on Decentralized Graphs with Local Differential Privacy
Many real-world networks are inherently decentralized. For example, in s...
research
∙
04/14/2021
Generative Causal Explanations for Graph Neural Networks
This paper presents Gem, a model-agnostic approach for providing interpr...
research
∙
10/28/2019