activity
20212026
most citedGenerating Explainable Rule Sets from Tree-Ensemble Learning Methods by Answer Set Programming

5 citations · 8 across the 8 of their papers we have counts for

collaborators
Showing 2024Show all

3 papers · 1 filter

cs.AI2024★ 1 cited

Generating Global and Local Explanations for Tree-Ensemble Learning Methods by Answer Set Programming

Akihiro Takemura, Katsumi Inoue

We propose a method for generating rule sets as global and local explanations for tree-ensemble learning methods using Answer Set Programming (ASP). To this end, we adopt a decompo…

cs.AI2024

Differentiable Logic Programming for Distant Supervision

Akihiro Takemura, Katsumi Inoue

We introduce a new method for integrating neural networks with logic programming in Neural-Symbolic AI (NeSy), aimed at learning with distant supervision, in which direct labels ar…

cs.CV2024★ 1 cited

MOD-CL: Multi-label Object Detection with Constrained Loss

Sota Moriyama, Koji Watanabe, Katsumi Inoue +1

We introduce MOD-CL, a multi-label object detection framework that utilizes constrained loss in the training process to produce outputs that better satisfy the given requirements.…