Florian Yger | DeepAI

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∙ 09/14/2023

Structure-Preserving Transformers for Sequences of SPD Matrices

In recent years, Transformer-based auto-attention mechanisms have been s...

0 Mathieu Seraphim, et al. ∙

∙ 12/27/2022

Challenges in anomaly and change point detection

This paper presents an introduction to the state-of-the-art in anomaly a...

0 Madalina Olteanu, et al. ∙

∙ 07/06/2022

Is the U-Net Directional-Relationship Aware?

CNNs are often assumed to be capable of using contextual information abo...

0 Mateus Riva, et al. ∙

∙ 01/17/2022

Multi-winner Approval Voting Goes Epistemic

Epistemic voting interprets votes as noisy signals about a ground truth....

0 Tahar Allouche, et al. ∙

∙ 12/08/2021

Non parametric estimation of causal populations in a counterfactual scenario

In causality, estimating the effect of a treatment without confounding i...

0 Celine Beji, et al. ∙

∙ 12/07/2021

Truth-tracking via Approval Voting: Size Matters

Epistemic social choice aims at unveiling a hidden ground truth given vo...

0 Tahar Allouche, et al. ∙

∙ 11/29/2021

A new Sinkhorn algorithm with Deletion and Insertion operations

This technical report is devoted to the continuous estimation of an epsi...

0 Luc Brun, et al. ∙

∙ 11/04/2021

Functional connectivity ensemble method to enhance BCI performance (FUCONE)

Functional connectivity is a key approach to investigate oscillatory act...

9 Marie-Constance Corsi, et al. ∙

∙ 07/30/2021

The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections [Extended Version]

The inference of minimum spanning arborescences within a set of objects ...

0 Lucas Gnecco, et al. ∙

∙ 07/16/2021

Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences

Ordinary supervised learning is useful when we have paired training data...

0 Ikko Yamane, et al. ∙

∙ 07/05/2021

Template-Based Graph Clustering

We propose a novel graph clustering method guided by additional informat...

0 Mateus Riva, et al. ∙

∙ 04/08/2021

Scaling up graph homomorphism for classification via sampling

Feature generation is an open topic of investigation in graph machine le...

0 Paul Beaujean, et al. ∙

∙ 02/22/2021

Approximation of dilation-based spatial relations to add structural constraints in neural networks

Spatial relations between objects in an image have proved useful for str...

0 Mateus Riva, et al. ∙

∙ 02/22/2021

On the robustness of randomized classifiers to adversarial examples

This paper investigates the theory of robustness against adversarial att...

0 Rafael Pinot, et al. ∙

∙ 02/09/2021

Clinical BCI Challenge-WCCI2020: RIGOLETTO – RIemannian GeOmetry LEarning, applicaTion To cOnnectivity

This short technical report describes the approach submitted to the Clin...

14 Marie-Constance Corsi, et al. ∙

∙ 06/19/2019

A unified view on differential privacy and robustness to adversarial examples

This short note highlights some links between two lines of research with...

0 Rafael Pinot, et al. ∙

∙ 03/25/2019

Robust Neural Networks using Randomized Adversarial Training

Since the discovery of adversarial examples in machine learning, researc...

0 Alexandre Araujo, et al. ∙

∙ 02/04/2019

Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family

This paper investigates the theory of robustness against adversarial att...

0 Rafael Pinot, et al. ∙

∙ 03/14/2018

Uplift Modeling from Separate Labels

Uplift modeling is aimed at estimating the incremental impact of an acti...

0 Ikko Yamane, et al. ∙

∙ 03/10/2018

Graph-based Clustering under Differential Privacy

In this paper, we present the first differentially private clustering me...

0 Rafael Pinot, et al. ∙

∙ 09/03/2017

Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario

Item cold-start is a classical issue in recommender systems that affects...

0 Jill-Jênn Vie, et al. ∙

∙ 10/10/2014

Challenge IEEE-ISBI/TCB : Application of Covariance matrices and wavelet marginals

This short memo aims at explaining our approach for the challenge IEEE-I...

0 Florian Yger, et al. ∙

∙ 06/27/2012

Adaptive Canonical Correlation Analysis Based On Matrix Manifolds

In this paper, we formulate the Canonical Correlation Analysis (CCA) pro...

0 Florian Yger, et al. ∙

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