2 citations · 4 across the 6 of their papers we have counts for
6 papers
Hierarchical Multi-Graphs Learning for Robust Group Re-Identification
Ruiqi Liu, Xingyu Liu, Xiaohao Xu +3
Group Re-identification (G-ReID) faces greater complexity than individual Re-identification (ReID) due to challenges like mutual occlusion, dynamic member interactions, and evolvin…
Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA
Yixuan Zhang, Dongyan Huo, Yudong Chen +1
Motivated by Q-learning, we study nonsmooth contractive stochastic approximation (SA) with constant stepsize. We focus on two important classes of dynamics: 1) nonsmooth contractiv…
Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation
Yixuan Zhang, Qiaomin Xie
Stochastic Approximation (SA) is a widely used algorithmic approach in various fields, including optimization and reinforcement learning (RL). Among RL algorithms, Q-learning is pa…
Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes
Yixuan Zhang, Quyu Kong, Feng Zhou
In this study, we propose a novel deep spatio-temporal point process model, Deep Kernel Mixture Point Processes (DKMPP), that incorporates multimodal covariate information. DKMPP i…
Advancing Acoustic Howling Suppression through Recursive Training of Neural Networks
Hao Zhang, Yixuan Zhang, Meng Yu +1
In this paper, we introduce a novel training framework designed to comprehensively address the acoustic howling issue by examining its fundamental formation process. This framework…
Unifying Robustness and Fidelity: A Comprehensive Study of Pretrained Generative Methods for Speech Enhancement in Adverse Conditions
Heming Wang, Meng Yu, Hao Zhang +5
Enhancing speech signal quality in adverse acoustic environments is a persistent challenge in speech processing. Existing deep learning based enhancement methods often struggle to…