4 citations · 9 across the 4 of their papers we have counts for
8 papers
Neural Collaborative Filtering Bandits via Meta Learning
Yikun Ban, Yunzhe Qi, Tianxin Wei +1
Contextual multi-armed bandits provide powerful tools to solve the exploitation-exploration dilemma in decision making, with direct applications in the personalized recommendation.…
Multi-facet Contextual Bandits: A Neural Network Perspective
Yikun Ban, Jingrui He, Curtiss B. Cook
Contextual multi-armed bandit has shown to be an effective tool in recommender systems. In this paper, we study a novel problem of multi-facet bandits involving a group of bandits,…
Generic Outlier Detection in Multi-Armed Bandit
Yikun Ban, Jingrui He
In this paper, we study the problem of outlier arm detection in multi-armed bandit settings, which finds plenty of applications in many high-impact domains such as finance, healthc…
Coalesced TLB to Exploit Diverse Contiguity of Memory Mapping
Yikun Ban, Yuchen Zhou, Xu Cheng +1
The miss rate of TLB is crucial to the performance of address translation for virtual memory. To reduce the TLB misses, improving translation coverage of TLB has been an primary ap…
Catching Loosely Synchronized Behavior in Face of Camouflage
Yikun Ban, Jiao Sun, Xin Liu
Fraud has severely detrimental impacts on the business of social networks and other online applications. A user can become a fake celebrity by purchasing "zombie followers" on Twit…
On Finding Dense Subgraphs in Bipartite Graphs: Linear Algorithms
Yikun Ban
Detecting dense subgraphs from large graphs is a core component in many applications, ranging from social networks mining, bioinformatics. In this paper, we focus on mining dense s…