8 papers
AnchorMoE: Interpretable Time Series Classification via Anchor-Routed MoE
Tao Xie, Zexi Tan, Haoyi Xiao +5
Multivariate time series classification (MTSC) is pivotal in high-stakes domains, such as clinical diagnosis and industrial fault detection, where safe deployment necessitates tran…
CARE: Class-Adaptive Expert Consensus for Reliable Learning with Long-Tailed Noisy Labels
Mengke Li, Haiquan Ling, Lihao Chen +3
Learning from real-world data is frequently hindered by the compound challenge of long-tailed class distributions and noisy annotations. Existing methods partially address these is…
On Unified and Sharpened CMI Bounds for Generalization Errors
Yang Lu, Matthias Frey, Margreta Kuijper +1
We present a new family of information-theoretic generalization bounds within the framework of conditional mutual information (CMI). Most of our results are established based on th…
HyReaL: Clustering Attributed Graph via Hyper-Complex Space Representation Learning
Junyang Chen, Yang Lu, Mengke Li +3
Clustering complex data in the form of attributed graphs has attracted increasing attention, where powerful graph representation is a critical prerequisite. However, the well-known…
Stitch the Fragments: One-Shot Hierarchical Federated Clustering
Shenghong Cai, Zihua Yang, Yang Lu +4
Federated Clustering (FC) faces a critical bottleneck in real-world scenarios, i.e., global clusters are rarely intact, often fragmenting into incomplete, multi-granular unlabeled…
PI-H2T: Enhancing Long-Tailed Visual Recognition with Permutation-Invariant and Head-to-Tail Feature Fusion
Mengke Li, Zhikai Hu, Yang Lu +3
The imbalanced distribution of long-tailed data presents a significant challenge for deep learning models, causing them to prioritize head classes while neglecting tail classes. Tw…