Hierarchical optimal transport
WebHierarchical Optimal Transport for Multimodal Distribution Alignment John Lee y, Max Dabagia , Eva L. Dyeryzy, Christopher J. Rozellyy ySchool of Electrical and Computer Engineering, zCoulter Department of Biomedical Engineering Georgia Institute of Technology, Atlanta, GA, 30332 USA {john.lee, maxdabagia, evadyer, crozell}@gatech.edu Web3 de dez. de 2024 · Hierarchical optimal transport, is an effective and efficient paradigm to induce structures in the transportation procedure. It has been recently used for different tasks such as multi-level clustering ho2024multilevel , multimodal distribution alignment NEURIPS2024_e41990b1 , document representation NEURIPS2024_8b5040a8
Hierarchical optimal transport
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WebA two-level hierarchical optimal control method is proposed in this paper. At the upper level, the reference signals (set-point) are optimized with a data-driven model-free adaptive control (MFAC) method. Traffic signals are regulated with the model predictive control (MPC) with the desired reference signals specified by the upper level. WebOptimal transport (OT)-based approaches pose alignment as a divergence minimization problem: the aim is to transform a source dataset to match a target dataset using the Wasserstein distance as a divergence measure. We introduce a hierarchical formulation of OT which leverages clustered structure in data to improve alignment in noisy, ambiguous ...
Web1 de ago. de 2024 · This paper presents an agglomerative hierarchical clustering, which incorporates optimal transport, and thus, takes the distributional aspects of the clusters … Web6 de abr. de 2024 · We give a concrete example of a kanji distance function obtained in this way as a proof of concept. Based on this function, we produce 2D kanji maps by multidimensional scaling and a table of 100 randomly selected Jōjō kanji with their 16 nearest neighbors. Our kanji distance functions can be used to help Japanese learners …
WebCopula theory, optimal transport, information geometry for processing and clustering financial time series with applications to the credit default swap market. Jury: Damiano Brigo, Fabrizio Lillo, Rama Cont, ... hierarchical clustering. In this work, we first show… Web3 de dez. de 2024 · In this paper, we propose a novel approach for unsupervised domain adaptation, that relates notions of optimal transport, learning probability measures and …
WebWe introduce hierarchical optimal transport to measure dissimilarities between distributions with common structure. We apply our method to document classification, …
WebHierarchical Optimal Transport for Multimodal Distribution Alignment: Reviewer 1. Post-rebuttal update: The authors' response is very thorough and clarifies many of my concerns, mostly those due to what it seems was a misunderstanding of what their baselines were (due to inexact/missing explanations). design on a dime consignment myrtle beach scWeb29 de out. de 2024 · Hierarchical optimal transport is an effective and efficient paradigm to induce structural information into the transportation procedure. It has been recently used for different tasks such as ... chuck e cheese kansas city mo couponsWebProceedings of Machine Learning Research design on a dime coffee tableWebThe algorithm only takes into account a sparse subset of possible assignment pairs while still guaranteeing global optimality of the solution. These subsets are determined by a multiscale approach together with a hierarchical consistency check in order to solve problems at successively finer scales. design on a dime faux leather wall treatmentWeb5 de abr. de 2024 · They propose a “meta-distance” between documents, called the hierarchical optimal topic transport (HOTT), providing a scalable metric incorporating … design one build many adipecWeb4 de jun. de 2024 · Unfortunately, these two assumptions may be questionable in practice, which limits the application of multi-view learning. In this work, we propose a hierarchical optimal transport (HOT) method to mitigate the dependency on these two assumptions. Given unaligned multi-view data, the HOT method penalizes the sliced Wasserstein … design on back sweatshirtsWebSantambrogio F Optimal transport for applied mathematicians 2015 Birkäuser 55 58-63 10.1007/978-3-319-20828-2 1401.49002 Google Scholar; Schmitzer, B., & Schnörr, C. (2013). A hierarchical approach to optimal transport. In International conference on scale space and variational methods in computer vision, (pp. 452–464). Springer. Google Scholar chuck e cheese kansas city antioch