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07/17/2023
Modular Neural Network Approaches for Surgical Image Recognition
Deep learning-based applications have seen a lot of success in recent ye...
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10/24/2022
Theoretical Guarantees for Domain Adaptation with Hierarchical Optimal Transport
Domain adaptation arises as an important problem in statistical learning...
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03/30/2022
A quantum learning approach based on Hidden Markov Models for failure scenarios generation
Finding the failure scenarios of a system is a very complex problem in t...
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03/28/2022
Convex Non-negative Matrix Factorization Through Quantum Annealing
In this paper we provide the quantum version of the Convex Non-negative ...
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12/14/2021
Inductive Semi-supervised Learning Through Optimal Transport
In this paper, we tackle the inductive semi-supervised learning problem ...
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12/03/2021
Hierarchical Optimal Transport for Unsupervised Domain Adaptation
In this paper, we propose a novel approach for unsupervised domain adapt...
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10/01/2021
Label Propagation Through Optimal Transport
In this paper, we tackle the transductive semi-supervised learning probl...
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09/09/2021
On the use of Wasserstein metric in topological clustering of distributional data
This paper deals with a clustering algorithm for histogram data based on...
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03/24/2021
Unsupervised collaborative learning using privileged information
In the collaborative clustering framework, the hope is that by combining...
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03/22/2021
Selective information exchange in collaborative clustering using regularized Optimal Transport
Collaborative learning has recently achieved very significant results. I...
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03/22/2021
Regularized Optimal Transport for Dynamic Semi-supervised Learning
Semi-supervised learning provides an effective paradigm for leveraging u...
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04/24/2020
A survey on domain adaptation theory
All famous machine learning algorithms that correspond to both supervise...
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05/17/2017
Co-clustering through Optimal Transport
In this paper, we present a novel method for co-clustering, an unsupervi...
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10/20/2016