1 citations · 1 across the 27 of their papers we have counts for
5 papers · 1 filter
Decision Tree Learning on Product Spaces
Arshia Soltani Moakhar, Faraz Ghahremani, Kiarash Banihashem +1
Decision tree learning has long been a central topic in theoretical computer science, driven by its practical importance. A fundamental and widely used method for decision tree con…
Replicable Composition
Kiarash Banihashem, MohammadHossein Bateni, Hossein Esfandiari +2
Replicability requires that algorithmic conclusions remain consistent when rerun on independently drawn data. A central structural question is composition: given problems each…
Active Learning for Decision Trees with Provable Guarantees
Arshia Soltani Moakhar, Tanapoom Laoaron, Faraz Ghahremani +2
This paper advances the theoretical understanding of active learning label complexity for decision trees as binary classifiers. We make two main contributions. First, we provide th…
Tokenized Bandit for LLM Decoding and Alignment
Suho Shin, Chenghao Yang, Haifeng Xu +1
We introduce the tokenized linear bandit (TLB) and multi-armed bandit (TMAB), variants of linear and stochastic multi-armed bandit problems inspired by LLM decoding and alignment.…
An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin +1
We present an oracle-efficient relaxation for the adversarial contextual bandits problem, where the contexts are sequentially drawn i.i.d from a known distribution and the cost seq…