ICML

A Theoretical Justification for Asymmetric Actor-Critic Algorithms

Gaspard Lambrechts, Damien Ernst, Aditya Mahajan

机构 * Montefiore Institute, University of Liège（利根大学蒙特菲尔研究所） ； Department of Electrical and Computer Engineering, McGill University（麦吉尔大学电气与计算机工程系） 纠错

Comments 8 pages, 31 pages total

Journal ref International Conference on Machine Learning, 2025

Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer

Yihang Wang, Yuying Qiu, Peng Chen, Kai Zhao, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo

机构 * East China Normal University, Shanghai, China（东华大学） ； Aalborg University, Aalborg, Denmark（奥尔堡大学） ； Huawei Noah's Ark Lab, Shenzhen, China（华为诺亚实验室） 纠错

Comments Accepted by the Forty-second International Conference on Machine Learning (ICML2025)

Toward Efficient and Scalable Design of In-Memory Graph-Based Vector Search

Ilias Azizi, Karima Echihab, Themis Palpanas, Vassilis Christophides

Comments Presented at ICML 2025 VecDB Workshop; an extended version appeared in ACM SIGMOD 2025 ('Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Art')

KABB: Knowledge-Aware Bayesian Bandits for Dynamic Expert Coordination in Multi-Agent Systems

Jusheng Zhang, Zimeng Huang, Yijia Fan, Ningyuan Liu, Mingyan Li, Zhuojie Yang, Jiawei Yao, Jian Wang, Keze Wang

机构 * Department of XXX, University of YYY, Location, Country（YYY大学XXX系） ； School of ZZZ, Institute of WWW, Location, Country（WWW研究所ZZZ学院） 纠错

Comments Accepted by the Main Conference of ICML 2025. Code: https://github.com/HCP-AI-Research-Lab/KABB