15 citations · 40 across the 14 of their papers we have counts for
15 papers
Algebraic Model Counting for Global Analysis of Optimal Decision Trees
Hiroki Arimura
Ensuring model reliability in Explainable AI requires a global assessment of the hypothesis space. We propose a formal framework for the exhaustive analysis of optimal and near-opt…
Optimally Computing Compressed Indexing Arrays Based on the Compact Directed Acyclic Word Graph
Hiroki Arimura, Shunsuke Inenaga, Yasuaki Kobayashi +2
In this paper, we present the first study of the computational complexity of converting an automata-based text index structure, called the Compact Directed Acyclic Word Graph (CDAW…
Computing the Collection of Good Models for Rule Lists
Kota Mata, Kentaro Kanamori, Hiroki Arimura
Since the seminal paper by Breiman in 2001, who pointed out a potential harm of prediction multiplicities from the view of explainable AI, global analysis of a collection of all go…
BRPO: Batch Residual Policy Optimization
Sungryull Sohn, Yinlam Chow, Jayden Ooi +4
In batch reinforcement learning (RL), one often constrains a learned policy to be close to the behavior (data-generating) policy, e.g., by constraining the learned action distribut…
Constant Amortized Time Enumeration of Independent Sets for Graphs with Bounded Clique Number
Kazuhiro Kurita, Kunihiro Wasa, Hiroki Arimura +1
In this study, we address the independent set enumeration problem. Although several efficient enumeration algorithms and careful analyses have been proposed for maximal independent…
Enumeration of Distinct Support Vectors for Interactive Decision Making
Kentaro Kanamori, Satoshi Hara, Masakazu Ishihata +1
In conventional prediction tasks, a machine learning algorithm outputs a single best model that globally optimizes its objective function, which typically is accuracy. Therefore, u…