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Variational Entropic Optimal Transport
Announce Type: replace Abstract: Entropic optimal transport (EOT) in continuous spaces with quadratic cost is a classical tool for solving the domain translation problem. In practice, recent approaches optimize a weak dual EOT objective depending on a single potential, but doing so is computationally not efficient due to the intractable log-partition term. Existing methods typically resolve this obstacle in one of two ways: by significantly restricting the transport family to obtain...
Entropic Optimal Transport Eigenmaps for Nonlinear Alignment and Joint Embedding of High-Dimensional Datasets
arXiv:2407.01718v2 Announce Type: replace-cross Abstract: Embedding high-dimensional data into a low-dimensional space is an indispensable component of data analysis. In numerous applications, it is necessary to align and jointly embed multiple datasets from different studies or experimental conditions. Such datasets may share underlying structures of interest but exhibit individual distortions, resulting in misaligned embeddings using traditional techniques.
As China and Pakistan move forward with their fifth generation plans, India's two short term options
Russian president Vladimir Putin reaffirmed Russia’s commitment to deepening ties with India as Moscow continues to offer the Su-57 fifth generation fighter jet with technology transfer and local production. While addressing journalists in St Petersburg the Russian President said, “We are ready to work with India to supply the Sukhoi Su-57, to develop it.” Putin remarks come at a time when the Indian air force is facing depleting squadron numbers and delays in his domestic programs.
A Data-Driven Methodology for Scalable Distributed MPC in Heterogeneous Building Aggregation: From Systematic Feature Selection to Convex Optimization
arXiv:2605.30763v1 Announce Type: new Abstract: Coordinating large-scale, heterogeneous building aggregations for demand response (DR) is impeded by a dual challenge: the computational intractability of centralized Model Predictive Control (MPC) and the inadequacy of conventional feature selection methods, which fail to address the error-compounding nature of multi-step forecasting required by MPC. This paper proposes a comprehensive, data-driven framework that first employs a systematic,...