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cs.DS2026
Learning-Augmented Approximation for Unrelated-Machines Makespan Scheduling
Kaito Baba, Evripidis Bampis, Giorgos Mitropoulos
Recently, Antoniadis et al. (ICLR 2025) proposed a framework for incorporating predictions to approximate NP-hard selection problems. Despite its simplicity, this approach tightly…
cs.CV2026
Multi-Modal Multi-Agent Reinforcement Learning for Radiology Report Generation
Kaito Baba, Risa Kishikawa, Satoshi Kodera
We propose MARL-Rad, a multi-modal multi-agent reinforcement learning framework for radiology report generation that trains the entire agentic system on policy within its deployed…
cs.LG2026
Conditional PED-ANOVA: Hyperparameter Importance in Hierarchical & Dynamic Search Spaces
Kaito Baba, Yoshihiko Ozaki, Shuhei Watanabe
We propose conditional PED-ANOVA (condPED-ANOVA), a principled framework for estimating hyperparameter importance (HPI) in conditional search spaces, where the presence or domain o…