18 citations · 46 across the 12 of their papers we have counts for
11 papers
Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs
Behnam Rahdari, Hao Ding, Ziwei Fan +4
The unique capabilities of Large Language Models (LLMs), such as the natural language text generation ability, position them as strong candidates for providing explanation for reco…
Pessimistic Off-Policy Multi-Objective Optimization
Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy +3
Multi-objective optimization is a type of decision making problems where multiple conflicting objectives are optimized. We study offline optimization of multi-objective policies fr…
Multiplier Bootstrap-based Exploration
Runzhe Wan, Haoyu Wei, Branislav Kveton +1
Despite the great interest in the bandit problem, designing efficient algorithms for complex models remains challenging, as there is typically no analytical way to quantify uncerta…
Thompson Sampling with Diffusion Generative Prior
Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton +1
In this work, we initiate the idea of using denoising diffusion models to learn priors for online decision making problems. Our special focus is on the meta-learning for bandit fra…
Does Weather Matter? Causal Analysis of TV Logs
Shi Zong, Branislav Kveton, Shlomo Berkovsky +3
Weather affects our mood and behaviors, and many aspects of our life. When it is sunny, most people become happier; but when it rains, some people get depressed. Despite this evide…
Stochastic Rank-1 Bandits
Sumeet Katariya, Branislav Kveton, Csaba Szepesvari +2
We propose stochastic rank- bandits, a class of online learning problems where at each step a learning agent chooses a pair of row and column arms, and receives the product of t…