14 papers
Self-Supervised Representation-Guided Generative Dataset Distillation
Mingzhuo Li, Guang Li, Linfeng Ye +4
Dataset distillation compresses a large training set into a compact synthetic set while retaining its downstream utility. Most existing methods target randomly initialized networks…
Dynamic Neural Graph Encoding of Inference Processes in Deep Weight Space
Di Wu, Huan Liu, Zhixiang Chi +3
The rapid advancements in using neural networks as implicit data representations have attracted significant interest in developing machine learning methods that analyze and process…
X-Palm: Paired Multispectral-to-Smartphone Dataset for Cross-Domain Palmprint Authentication
Jamal Seyedmohammadi, Pai Chet Ng, Angelo Genovese +3
Palmprint modality offers a privacy-preserving biometric solution, yet its deployment is hindered by the domain gap between controlled enrollment and unconstrained authentication.…
Privacy-Preserving Federated Action Recognition via Differentially Private Selective Tuning and Efficient Communication
Idris Zakariyya, Pai Chet Ng, Kaushik Bhargav Sivangi +3
Federated video action recognition enables collaborative model training without sharing raw video data, yet remains vulnerable to two key challenges: \textit{model exposure} and \t…
ASMIL: Attention-Stabilized Multiple Instance Learning for Whole Slide Imaging
Linfeng Ye, Shayan Mohajer Hamidi, Zhixiang Chi +5
Attention-based multiple instance learning (MIL) has emerged as a powerful framework for whole slide image (WSI) diagnosis, leveraging attention to aggregate instance-level feature…
Normalized Conditional Mutual Information Surrogate Loss for Deep Neural Classifiers
Linfeng Ye, Zhixiang Chi, Konstantinos N. Plataniotis +1
In this paper, we propose a novel information theoretic surrogate loss; normalized conditional mutual information (NCMI); as a drop in alternative to the de facto cross-entropy (CE…