3 citations · 10 across the 17 of their papers we have counts for
5 papers · 1 filter
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…
Forward Learning with Differential Privacy
Mingqian Feng, Zeliang Zhang, Jinyang Jiang +2
Differential privacy (DP) in deep learning is a critical concern as it ensures the confidentiality of training data while maintaining model utility. Existing DP training algorithms…
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…
Integrated Offline and Online Learning to Solve a Large Class of Scheduling Problems
Anbang Liu, Zhi-Long Chen, Jinyang Jiang +1
In this paper, we develop a unified machine learning (ML) approach to predict high-quality solutions for single-machine scheduling problems with a non-decreasing min-sum objective…