4 papers
Adaptive Multi-view Graph Contrastive Learning via Fractional-order Neural Diffusion Networks
Yanan Zhao, Feng Ji, Jingyang Dai +4
Graph contrastive learning (GCL) learns node and graph representations by contrasting multiple views of the same graph. Existing methods typically rely on fixed, handcrafted views-…
Exploiting Electrolyzer Flexibility via Multiscale Model Predictive Control Cross Heterogeneous Energy Markets
Zhichao Chen, Hongyuan Sheng, Hao Wang +1
Green hydrogen production via electrolysis is crucial for decarbonization but faces significant economic hurdles primarily due to the high cost of the electricity. However, current…
A Survey of Reinforcement Learning for Large Reasoning Models
Kaiyan Zhang, Yuxin Zuo, Bingxiang He +36
In this paper, we survey recent advances in Reinforcement Learning (RL) for reasoning with Large Language Models (LLMs). RL has achieved remarkable success in advancing the frontie…
Relaxing Probabilistic Latent Variable Models' Specification via Infinite-Horizon Optimal Control
Zhichao Chen, Hao Wang, Licheng Pan +6
In this paper, we address the issue of model specification in probabilistic latent variable models (PLVMs) using an infinite-horizon optimal control approach. Traditional PLVMs rel…