8 papers
Dynamic Prior Thompson Sampling for Cold-Start Exploration in Recommender Systems
Zhenyu Zhao, David Zhang, Ellie Zhao +1
Cold-start exploration is a core challenge in large-scale recommender systems: new or data-sparse items must receive traffic to estimate value, but over-exploration harms users and…
CoPHo: Classifier-guided Conditional Topology Generation with Persistent Homology
Gongli Xi, Ye Tian, Mengyu Yang +5
The structure of topology underpins much of the research on performance and robustness, yet available topology data are typically scarce, necessitating the generation of synthetic…
Humanoid Everyday: A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation
Zhenyu Zhao, Hongyi Jing, Xiawei Liu +7
From loco-motion to dextrous manipulation, humanoid robots have made remarkable strides in demonstrating complex full-body capabilities. However, the majority of current robot lear…
Algorithm Adaptation Bias in Recommendation System Online Experiments
Chen Zheng, Zhenyu Zhao
Online experiments (A/B tests) are widely regarded as the gold standard for evaluating recommender system variants and guiding launch decisions. However, a variety of biases can di…
Causal Feature Selection Method for Contextual Multi-Armed Bandits in Recommender System
Zhenyu Zhao, Yexi Jiang
Effective feature selection is essential for optimizing contextual multi-armed bandits (CMABs) in large-scale online systems, where suboptimal features can degrade rewards, interpr…
Integrating Active Learning in Causal Inference with Interference: A Novel Approach in Online Experiments
Hongtao Zhu, Sizhe Zhang, Yang Su +2
In the domain of causal inference research, the prevalent potential outcomes framework, notably the Rubin Causal Model (RCM), often overlooks individual interference and assumes in…
Treatment Effect Estimation Amidst Dynamic Network Interference in Online Gaming Experiments
Yu Zhu, Zehang Richard Li, Yang Su +1
The evolving landscape of online multiplayer gaming presents unique challenges in assessing the causal impacts of game features. Traditional A/B testing methodologies fall short du…
Effective Anomaly Detection in Smart Home by Integrating Event Time Intervals
Chenxu Jiang, Chenglong Fu, Zhenyu Zhao +2
Smart home IoT systems and devices are susceptible to attacks and malfunctions. As a result, users' concerns about their security and safety issues arise along with the prevalence…