11 citations · 13 across the 5 of their papers we have counts for
7 papers · 1 filter
Dueling Bandits: From Two-dueling to Multi-dueling
Yihan Du, Siwei Wang, Longbo Huang
We study a general multi-dueling bandit problem, where an agent compares multiple options simultaneously and aims to minimize the regret due to selecting suboptimal arms. This sett…
Multi-view Clustering via Deep Matrix Factorization and Partition Alignment
Chen Zhang, Siwei Wang, Jiyuan Liu +5
Multi-view clustering (MVC) has been extensively studied to collect multiple source information in recent years. One typical type of MVC methods is based on matrix factorization to…
Pure Exploration Bandit Problem with General Reward Functions Depending on Full Distributions
Siwei Wang, Wei Chen
In this paper, we study the pure exploration bandit model on general distribution functions, which means that the reward function of each arm depends on the whole distribution, not…
Multi-view Clustering with Deep Matrix Factorization and Global Graph Refinement
Chen Zhang, Siwei Wang, Wenxuan Tu +4
Multi-view clustering is an important yet challenging task in machine learning and data mining community. One popular strategy for multi-view clustering is matrix factorization whi…
Adaptive Algorithms for Multi-armed Bandit with Composite and Anonymous Feedback
Siwei Wang, Haoyun Wang, Longbo Huang
We study the multi-armed bandit (MAB) problem with composite and anonymous feedback. In this model, the reward of pulling an arm spreads over a period of time (we call this period…
Restless-UCB, an Efficient and Low-complexity Algorithm for Online Restless Bandits
Siwei Wang, Longbo Huang, John C. S. Lui
We study the online restless bandit problem, where the state of each arm evolves according to a Markov chain, and the reward of pulling an arm depends on both the pulled arm and th…