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08/29/2023
Few-Shot Object Detection via Synthetic Features with Optimal Transport
Few-shot object detection aims to simultaneously localize and classify t...
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01/31/2023
Dynamic Flows on Curved Space Generated by Labeled Data
The scarcity of labeled data is a long-standing challenge for many machi...
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02/22/2022
Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics
Optimal transport (OT) is a popular measure to compare probability distr...
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09/30/2021
Adversarial Regression with Doubly Non-negative Weighting Matrices
Many machine learning tasks that involve predicting an output response c...
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06/08/2021
Nonsmooth Implicit Differentiation for Machine Learning and Optimization
In view of training increasingly complex learning architectures, we esta...
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01/24/2021
Entropy Partial Transport with Tree Metrics: Theory and Practice
Optimal transport (OT) theory provides powerful tools to compare probabi...
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06/13/2020
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search
Neural architecture search (NAS) automates the design of deep neural net...
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10/10/2019
On Scalable Variant of Wasserstein Barycenter
We study a variant of Wasserstein barycenter problem, which we refer to ...
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10/10/2019
Computationally Efficient Tree Variants of Gromov-Wasserstein
We propose two novel variants of Gromov-Wasserstein (GW) between probabi...
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09/05/2019
LSMI-Sinkhorn: Semi-supervised Squared-Loss Mutual Information Estimation with Optimal Transport
Estimating mutual information is an important machine learning and stati...
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02/26/2019
Topological Bayesian Optimization with Persistence Diagrams
Finding an optimal parameter of a black-box function is important for se...
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02/01/2019
Tree-Sliced Approximation of Wasserstein Distances
Optimal transport () theory provides a useful set of tools to compare pr...
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10/12/2018
Safe Grid Search with Optimal Complexity
Popular machine learning estimators involve regularization parameters th...
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02/10/2018