12 citations · 12 across the 4 of their papers we have counts for
4 papers
Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms
MohammadJavad Azizi, Thang Duong, Yasin Abbasi-Yadkori +3
We study a sequential decision problem where the learner faces a sequence of -armed bandit tasks. The task boundaries might be known (the bandit meta-learning setting), or unkno…
Meta-Learning for Simple Regret Minimization
Mohammadjavad Azizi, Branislav Kveton, Mohammad Ghavamzadeh +1
We develop a meta-learning framework for simple regret minimization in bandits. In this framework, a learning agent interacts with a sequence of bandit tasks, which are sampled i.i…
Fixed-Budget Best-Arm Identification in Structured Bandits
Mohammad Javad Azizi, Branislav Kveton, Mohammad Ghavamzadeh
Best-arm identification (BAI) in a fixed-budget setting is a bandit problem where the learning agent maximizes the probability of identifying the optimal (best) arm after a fixed n…
Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making
Sina Aghaei, Mohammad Javad Azizi, Phebe Vayanos
In recent years, automated data-driven decision-making systems have enjoyed a tremendous success in a variety of fields (e.g., to make product recommendations, or to guide the prod…