32 citations · 60 across the 7 of their papers we have counts for
6 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.…
Adaptive Transfer Learning for Plant Phenotyping
Jun Wu, Elizabeth A. Ainsworth, Sheng Wang +2
Plant phenotyping (Guo et al. 2021; Pieruschka et al. 2019) focuses on studying the diverse traits of plants related to the plants' growth. To be more specific, by accurately measu…
From Intrinsic to Counterfactual: On the Explainability of Contextualized Recommender Systems
Yao Zhou, Haonan Wang, Jingrui He +1
With the prevalence of deep learning based embedding approaches, recommender systems have become a proven and indispensable tool in various information filtering applications. Howe…
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,…
Deep Co-Attention Network for Multi-View Subspace Learning
Lecheng Zheng, Yu Cheng, Hongxia Yang +2
Many real-world applications involve data from multiple modalities and thus exhibit the view heterogeneity. For example, user modeling on social media might leverage both the topol…
GAN-based Recommendation with Positive-Unlabeled Sampling
Yao Zhou, Jianpeng Xu, Jun Wu +4
Recommender systems are popular tools for information retrieval tasks on a large variety of web applications and personalized products. In this work, we propose a Generative Advers…