Abstract: The paper studies discrete-time statistical filtering problems with the goal to minimize expected total costs. Such problems are usually defined by pairs of stochastic equations and by ...
Official implementation of the paper: "CONSTRAINT MATTERS: MULTI-MODAL REPRESENTATION FOR REDUCING MIXED-INTEGER LINEAR PROGRAMMING", accepted by ICLR 2026. Model reduction is a powerful way to ...
Abstract: This study utilizes machine learning and optimization techniques to lower energy costs in factory operations. By incorporating weather forecast data and machine learning techniques, we aim ...
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