9 papers
Machine Learning-Assisted High-Dimensional Matrix Estimation
Wan Tian, Hui Yang, Zhouhui Lian +2
Efficient estimation of high-dimensional matrices-including covariance and precision matrices-is a cornerstone of modern multivariate statistics. Most existing studies have focused…
Adaptive Robust Estimator for Multi-Agent Reinforcement Learning
Zhongyi Li, Wan Tian, Jingyu Chen +8
Multi-agent collaboration has emerged as a powerful paradigm for enhancing the reasoning capabilities of large language models, yet it suffers from interaction-level ambiguity that…
Sharper Generalization Bounds for Transformer
Yawen Li, Tao Hu, Zhouhui Lian +4
This paper studies generalization error bounds for Transformer models. Based on the offset Rademacher complexity, we derive sharper generalization bounds for different Transformer…
Omni-Masked Gradient Descent: Memory-Efficient Optimization via Mask Traversal with Improved Convergence
Hui Yang, Tao Ren, Jinyang Jiang +2
Memory-efficient optimization methods have recently gained increasing attention for scaling full-parameter training of large language models under the GPU-memory bottleneck. Existi…
RiskPO: Risk-based Policy Optimization via Verifiable Reward for LLM Post-Training
Tao Ren, Jinyang Jiang, Hui Yang +10
Reinforcement learning with verifiable reward has recently emerged as a central paradigm for post-training large language models (LLMs); however, prevailing mean-based methods, suc…
Interval-Valued Time Series Classification Using -Distance
Wan Tian, Zhongfeng Qin
In recent years, modeling and analysis of interval-valued time series have garnered increasing attention in econometrics, finance, and statistics. However, these studies have predo…