A Graph Tsetlin Machine with hypervectorized macro multigraphs and message-passing clauses anticipates four USD/JPY regimes, reaching 70.7% overall OOS accuracy and beating reduced-graph and CoTM baselines on stagnant and choppy classes.
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A hybrid RL and self-supervised learning method accelerates generalized Benders decomposition by 57.5% on a MINLP case study while recovering optimal solutions.
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Macroeconomic Message Passing for Anticipating Foreign Exchange Regime Changes: A Deep Logical Learning Approach using Graph Tsetlin Machines
A Graph Tsetlin Machine with hypervectorized macro multigraphs and message-passing clauses anticipates four USD/JPY regimes, reaching 70.7% overall OOS accuracy and beating reduced-graph and CoTM baselines on stagnant and choppy classes.
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A Hybrid Reinforcement and Self-Supervised Learning Aided Benders Decomposition Algorithm
A hybrid RL and self-supervised learning method accelerates generalized Benders decomposition by 57.5% on a MINLP case study while recovering optimal solutions.