Dicey Games characterize optimal strategies and complexity for teams using pairwise or limited shared randomness, proving they can exceed 1/4 win probability in a 4-player matching-pennies game against an adversary.
LExCI: A framework for reinforcement learning with embedded sys- tems
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The authors introduce aspect-aware datasets GoldRiM and SilverRiM for math papers and AchGNN, a heterogeneous GNN that outperforms prior methods by jointly modeling textual semantics, citations, and author lineage across aspects.
Residual reinforcement learning automates map-based ECU calibration to closely match series production references with minimal human intervention.
citing papers explorer
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Dicey Games: Shared Sources of Randomness in Distributed Systems
Dicey Games characterize optimal strategies and complexity for teams using pairwise or limited shared randomness, proving they can exceed 1/4 win probability in a 4-player matching-pennies game against an adversary.
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Aspect-Aware Content-Based Recommendations for Mathematical Research Papers
The authors introduce aspect-aware datasets GoldRiM and SilverRiM for math papers and AchGNN, a heterogeneous GNN that outperforms prior methods by jointly modeling textual semantics, citations, and author lineage across aspects.
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Production-Ready Automated ECU Calibration using Residual Reinforcement Learning
Residual reinforcement learning automates map-based ECU calibration to closely match series production references with minimal human intervention.