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06/07/2023
Adversarial Sample Detection Through Neural Network Transport Dynamics
We propose a detector of adversarial samples that is based on the view o...
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05/25/2023
Unifying GANs and Score-Based Diffusion as Generative Particle Models
Particle-based deep generative models, such as gradient flows and score-...
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03/10/2023
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals
When dealing with electro or magnetoencephalography records, many superv...
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01/26/2023
Personalised Federated Learning On Heterogeneous Feature Spaces
Most personalised federated learning (FL) approaches assume that raw dat...
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06/07/2022
Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances
The Sliced-Wasserstein distance (SW) is a computationally efficient and ...
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05/19/2022
Diverse Weight Averaging for Out-of-Distribution Generalization
Standard neural networks struggle to generalize under distribution shift...
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02/01/2022
Generalizing to New Physical Systems via Context-Informed Dynamics Model
Data-driven approaches to modeling physical systems fail to generalize t...
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09/16/2021
Unsupervised domain adaptation with non-stochastic missing data
We consider unsupervised domain adaptation (UDA) for classification prob...
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07/05/2021
Differentially Private Sliced Wasserstein Distance
Developing machine learning methods that are privacy preserving is today...
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06/07/2021
Photonic Differential Privacy with Direct Feedback Alignment
Optical Processing Units (OPUs) – low-power photonic chips dedicated to ...
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11/19/2020
Wasserstein Learning of Determinantal Point Processes
Determinantal point processes (DPPs) have received significant attention...
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07/02/2020
Partial Trace Regression and Low-Rank Kraus Decomposition
The trace regression model, a direct extension of the well-studied linea...
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06/24/2020
Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression
Owing to their statistical properties, non-convex sparse regularizers ha...
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06/23/2020
Multi-source Domain Adaptation via Weighted Joint Distributions Optimal Transport
The problem of domain adaptation on an unlabeled target dataset using kn...
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06/20/2019
Screening Sinkhorn Algorithm for Regularized Optimal Transport
We introduce in this paper a novel strategy for efficiently approximate ...
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02/16/2019
Screening Rules for Lasso with Non-Convex Sparse Regularizers
Leveraging on the convexity of the Lasso problem , screening rules help ...
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03/01/2018
Wasserstein Distance Measure Machines
This paper presents a distance-based discriminative framework for learni...
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11/02/2017
Concave losses for robust dictionary learning
Traditional dictionary learning methods are based on quadratic convex lo...
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05/24/2017
Joint Distribution Optimal Transportation for Domain Adaptation
This paper deals with the unsupervised domain adaptation problem, where ...
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08/29/2016
Wasserstein Discriminant Analysis
Wasserstein Discriminant Analysis (WDA) is a new supervised method that ...
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10/28/2015
Operator-valued Kernels for Learning from Functional Response Data
In this paper we consider the problems of supervised classification and ...
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10/22/2015
Generalized conditional gradient: analysis of convergence and applications
The objectives of this technical report is to provide additional results...
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07/02/2015
DC Proximal Newton for Non-Convex Optimization Problems
We introduce a novel algorithm for solving learning problems where both ...
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01/12/2013
Functional Regularized Least Squares Classi cation with Operator-valued Kernels
Although operator-valued kernels have recently received increasing inter...
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06/27/2012
Adaptive Canonical Correlation Analysis Based On Matrix Manifolds
In this paper, we formulate the Canonical Correlation Analysis (CCA) pro...
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06/27/2012
Sparse Support Vector Infinite Push
In this paper, we address the problem of embedded feature selection for ...
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03/07/2012
Multiple Operator-valued Kernel Learning
Positive definite operator-valued kernels generalize the well-known noti...
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10/06/2009
