Search Results for author: Florian Yger

Found 25 papers, 11 papers with code

Challenges in anomaly and change point detection

no code implementations27 Dec 2022 Madalina Olteanu, Fabrice Rossi, Florian Yger

On the one hand, the main concepts needed to understand the vast scientific literature on those subjects are introduced.

Change Point Detection

Is the U-Net Directional-Relationship Aware?

1 code implementation6 Jul 2022 Mateus Riva, Pietro Gori, Florian Yger, Isabelle Bloch

CNNs are often assumed to be capable of using contextual information about distinct objects (such as their directional relations) inside their receptive field.

Multi-winner Approval Voting Goes Epistemic

1 code implementation17 Jan 2022 Tahar Allouche, Jérôme Lang, Florian Yger

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

Non parametric estimation of causal populations in a counterfactual scenario

no code implementations8 Dec 2021 Celine Beji, Florian Yger, Jamal Atif

A Causal Auto-Encoder (CAE), enhanced by a prior dependent on treatment and outcome information, assimilates the latent space to the probability distribution of the target populations.

Truth-tracking via Approval Voting: Size Matters

1 code implementation7 Dec 2021 Tahar Allouche, Jérôme Lang, Florian Yger

Epistemic social choice aims at unveiling a hidden ground truth given votes, which are interpreted as noisy signals about it.

A new Sinkhorn algorithm with Deletion and Insertion operations

no code implementations29 Nov 2021 Luc Brun, Benoit Gaüzère, Sébastien Bougleux, Florian Yger

Conversely, the remaining elements of V2 correspond to the image of the epsilon pseudo element of V1.

Functional connectivity ensemble method to enhance BCI performance (FUCONE)

1 code implementation4 Nov 2021 Marie-Constance Corsi, Sylvain Chevallier, Fabrizio De Vico Fallani, Florian Yger

Functional connectivity is a key approach to investigate oscillatory activities of the brain that provides important insights on the underlying dynamic of neuronal interactions and that is mostly applied for brain activity analysis.

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

no code implementations30 Jul 2021 Lucas Gnecco, Nicolas Boria, Sébastien Bougleux, Florian Yger, David B. Blumenthal

The inference of minimum spanning arborescences within a set of objects is a general problem which translates into numerous application-specific unsupervised learning tasks.

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

1 code implementation16 Jul 2021 Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama

In this paper, we consider the task of predicting $Y$ from $X$ when we have no paired data of them, but we have two separate, independent datasets of $X$ and $Y$ each observed with some mediating variable $U$, that is, we have two datasets $S_X = \{(X_i, U_i)\}$ and $S_Y = \{(U'_j, Y'_j)\}$.

Template-Based Graph Clustering

1 code implementation5 Jul 2021 Mateus Riva, Florian Yger, Pietro Gori, Roberto M. Cesar Jr., Isabelle Bloch

We propose a novel graph clustering method guided by additional information on the underlying structure of the clusters (or communities).

Graph Clustering

Scaling Up Graph Homomorphism Features with Efficient Data Structures

no code implementations ICLR Workshop GTRL 2021 Paul Beaujean, Florian Sikora, Florian Yger

Typical datasets used in graph classification tasks only contain a few thousand graphs which rarely exceed hundreds of nodes.

Graph Classification

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

no code implementations22 Feb 2021 Mateus Riva, Pietro Gori, Florian Yger, Roberto Cesar, Isabelle Bloch

Several relations can be modeled as a morphological dilation of a reference object with a structuring element representing the semantics of the relation, from which the degree of satisfaction of the relation between another object and the reference object can be derived.

Object Recognition

Estimating Individual Treatment Effects through Causal Populations Identification

no code implementations10 Apr 2020 Céline Beji, Michaël Bon, Florian Yger, Jamal Atif

Estimating the Individual Treatment Effect from observational data, defined as the difference between outcomes with and without treatment or intervention, while observing just one of both, is a challenging problems in causal learning.

A unified view on differential privacy and robustness to adversarial examples

no code implementations19 Jun 2019 Rafael Pinot, Florian Yger, Cédric Gouy-Pailler, Jamal Atif

This short note highlights some links between two lines of research within the emerging topic of trustworthy machine learning: differential privacy and robustness to adversarial examples.

Uplift Modeling from Separate Labels

1 code implementation NeurIPS 2018 Ikko Yamane, Florian Yger, Jamal Atif, Masashi Sugiyama

Uplift modeling is aimed at estimating the incremental impact of an action on an individual's behavior, which is useful in various application domains such as targeted marketing (advertisement campaigns) and personalized medicine (medical treatments).


Graph-based Clustering under Differential Privacy

no code implementations10 Mar 2018 Rafael Pinot, Anne Morvan, Florian Yger, Cédric Gouy-Pailler, Jamal Atif

In this paper, we present the first differentially private clustering method for arbitrary-shaped node clusters in a graph.

Geometry-aware stationary subspace analysis

no code implementations25 May 2016 Inbal Horev, Florian Yger, Masashi Sugiyama

The classic SSA method finds a matrix that projects the data onto a stationary subspace by optimizing a cost function based on a matrix divergence.

Supervised LogEuclidean Metric Learning for Symmetric Positive Definite Matrices

no code implementations12 Feb 2015 Florian Yger, Masashi Sugiyama

Metric learning has been shown to be highly effective to improve the performance of nearest neighbor classification.

Electroencephalogram (EEG) General Classification +1

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

no code implementations10 Oct 2014 Florian Yger

This short memo aims at explaining our approach for the challenge IEEE-ISBI on Bone Texture Characterization.

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