38 citations · 141 across the 21 of their papers we have counts for
9 papers · 1 filter
Personalized Adaptive Meta Learning for Cold-start User Preference Prediction
Runsheng Yu, Yu Gong, Xu He +4
A common challenge in personalized user preference prediction is the cold-start problem. Due to the lack of user-item interactions, directly learning from the new users' log data c…
MetaInfoNet: Learning Task-Guided Information for Sample Reweighting
Hongxin Wei, Lei Feng, Rundong Wang +1
Deep neural networks have been shown to easily overfit to biased training data with label noise or class imbalance. Meta-learning algorithms are commonly designed to alleviate this…
Efficient Reservoir Management through Deep Reinforcement Learning
Xinrun Wang, Tarun Nair, Haoyang Li +7
Dams impact downstream river dynamics through flow regulation and disruption of upstream-downstream linkages. However, current dam operation is far from satisfactory due to the ina…
Deep Stock Trading: A Hierarchical Reinforcement Learning Framework for Portfolio Optimization and Order Execution
Rundong Wang, Hongxin Wei, Bo An +2
Portfolio management via reinforcement learning is at the forefront of fintech research, which explores how to optimally reallocate a fund into different financial assets over the…
Complexity and Algorithms for Exploiting Quantal Opponents in Large Two-Player Games
David Milec, Jakub Černý, Viliam Lisý +1
Solution concepts of traditional game theory assume entirely rational players; therefore, their ability to exploit subrational opponents is limited. One type of subrationality that…
Computing Ex Ante Coordinated Team-Maxmin Equilibria in Zero-Sum Multiplayer Extensive-Form Games
Youzhi Zhang, Bo An, Jakub Černý
Computational game theory has many applications in the modern world in both adversarial situations and the optimization of social good. While there exist many algorithms for comput…