9 papers
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…
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…
Stochastic Approximation Methods for Distortion Risk Measure Optimization
Jinyang Jiang, Bernd Heidergott, Jiaqiao Hu +1
Distortion Risk Measures (DRMs) capture risk preferences in decision-making and serve as general criteria for managing uncertainty. This paper proposes gradient descent algorithms…
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…
A Parameter-Efficient Quantum Anomaly Detection Method on a Superconducting Quantum Processor
Maida Wang, Jinyang Jiang, Peter V. Coveney
Quantum machine learning has gained attention for its potential to address computational challenges. However, whether those algorithms can effectively solve practical problems and…
CoNNect: Connectivity-Based Regularization for Structural Pruning
Christian Franssen, Jinyang Jiang, Yijie Peng +1
Pruning encompasses a range of techniques aimed at increasing the sparsity of neural networks (NNs). These techniques can generally be framed as minimizing a loss function subject…