90 citations · 563 across the 40 of their papers we have counts for
17 papers · 1 filter
Structure-Preserving Graph Kernel for Brain Network Classification
Jun Yu, Zhaoming Kong, Aditya Kendre +5
This paper presents a novel graph-based kernel learning approach for connectome analysis. Specifically, we demonstrate how to leverage the naturally available structure within the…
DoubleStar: Long-Range Attack Towards Depth Estimation based Obstacle Avoidance in Autonomous Systems
Ce Zhou, Qiben Yan, Yan Shi +1
Depth estimation-based obstacle avoidance has been widely adopted by autonomous systems (drones and vehicles) for safety purpose. It normally relies on a stereo camera to automatic…
Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding
Sijia Wang, Mo Yu, Shiyu Chang +2
Event extraction is typically modeled as a multi-class classification problem where event types and argument roles are treated as atomic symbols. These approaches are usually limit…
Source Inference Attacks in Federated Learning
Hongsheng Hu, Zoran Salcic, Lichao Sun +2
Federated learning (FL) has emerged as a promising privacy-aware paradigm that allows multiple clients to jointly train a model without sharing their private data. Recently, many s…
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data
Zhiyuan Zhang, Lingjuan Lyu, Weiqiang Wang +2
Since training a large-scale backdoored model from scratch requires a large training dataset, several recent attacks have considered to inject backdoors into a trained clean model…
DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN
Yu Wang, Zhiwei Liu, Ziwei Fan +2
In the information explosion era, recommender systems (RSs) are widely studied and applied to discover user-preferred information. A RS performs poorly when suffering from the cold…