Stephane Marchand-Maillet

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University of Geneva

Computing flood probabilities using Twitter: application to the Houston urban area during Harvey

In this paper, we investigate the conversion of a Twitter corpus into ge...
12/07/2020 ∙ by Etienne Brangbour, et al. ∙ 0 ∙ share

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Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders

Despite the evolution of deep-learning-based visual-textual processing s...
08/12/2020 ∙ by Nicola Messina, et al. ∙ 0 ∙ share

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Tuning Ranking in Co-occurrence Networks with General Biased Exchange-based Diffusion on Hyper-bag-graphs

Co-occurence networks can be adequately modeled by hyper-bag-graphs (hb-...
03/16/2020 ∙ by Xavier Ouvrard, et al. ∙ 0 ∙ share

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The HyperBagGraph DataEdron: An Enriched Browsing Experience of Multimedia Datasets

Traditional verbatim browsers give back information in a linear way acco...
05/28/2019 ∙ by Xavier Ouvrard, et al. ∙ 0 ∙ share

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Learning by stochastic serializations

Complex structures are typical in machine learning. Tailoring learning a...
05/27/2019 ∙ by Pablo Strasser, et al. ∙ 0 ∙ share

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Extracting localized information from a Twitter corpus for flood prevention

In this paper, we discuss the collection of a corpus associated to tropi...
03/12/2019 ∙ by Etienne Brangbour, et al. ∙ 0 ∙ share

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Exchange-Based Diffusion in Hb-Graphs: Highlighting Complex Relationships

Most networks tend to show complex and multiple relationships between en...
09/01/2018 ∙ by Xavier Ouvrard, et al. ∙ 0 ∙ share

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Hypergraph Modeling and Visualisation of Complex Co-occurence Networks

Finding inherent or processed links within a dataset allows to discover ...
09/01/2018 ∙ by Xavier Ouvrard, et al. ∙ 0 ∙ share

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On Adjacency and e-Adjacency in General Hypergraphs: Towards a New e-Adjacency Tensor

In graphs, the concept of adjacency is clearly defined: it is a pairwise...
09/01/2018 ∙ by Xavier Ouvrard, et al. ∙ 0 ∙ share

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Adjacency and Tensor Representation in General Hypergraphs.Part 2: Multisets, Hb-graphs and Related e-adjacency Tensors

HyperBagGraphs (hb-graphs as short) extend hypergraphs by allowing the h...
05/30/2018 ∙ by Xavier Ouvrard, et al. ∙ 0 ∙ share

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Structured nonlinear variable selection

We investigate structured sparsity methods for variable selection in reg...
05/16/2018 ∙ by Magda Gregorova, et al. ∙ 0 ∙ share

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Large-scale Nonlinear Variable Selection via Kernel Random Features

We propose a new method for input variable selection in nonlinear regres...
04/19/2018 ∙ by Magda Gregorova, et al. ∙ 0 ∙ share

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On Adjacency and e-adjacency in General Hypergraphs: Towards an e-adjacency Tensor

Adjacency between two vertices in graphs or hypergraphs is a pairwise re...
12/21/2017 ∙ by Xavier Ouvrard, et al. ∙ 0 ∙ share

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Adjacency Matrix and Co-occurrence Tensor of General Hypergraphs: Two Well Separated Notions

Adjacency and co-occurrence are two well separated notions: even if they...
12/21/2017 ∙ by Xavier Ouvrard, et al. ∙ 0 ∙ share

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Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks

We present a new method for forecasting systems of multiple interrelated...
10/02/2017 ∙ by Magda Gregorova, et al. ∙ 0 ∙ share

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Forecasting and Granger Modelling with Non-linear Dynamical Dependencies

Traditional linear methods for forecasting multivariate time series are ...
06/27/2017 ∙ by Magda Gregorova, et al. ∙ 0 ∙ share

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On Hölder projective divergences

We describe a framework to build distances by measuring the tightness of...
01/14/2017 ∙ by Frank Nielsen, et al. ∙ 0 ∙ share

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Learning Leading Indicators for Time Series Predictions

We consider the problem of learning models for forecasting multiple time...
07/07/2015 ∙ by Magda Gregorova, et al. ∙ 0 ∙ share

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Two-Stage Metric Learning

In this paper, we present a novel two-stage metric learning algorithm. W...
05/12/2014 ∙ by Jun Wang, et al. ∙ 0 ∙ share

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Stephane Marchand-Maillet

Featured Co-authors

Jun Wang

Frank Nielsen

Ke Sun

Fei Sha

Alexandros Kalousis

Fabrizio Falchi

Giuseppe Amato

Andrea Esuli

Claudio Gennaro

Magda Gregorova

Xavier Ouvrard

Computing flood probabilities using Twitter: application to the Houston urban area during Harvey

Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders

Tuning Ranking in Co-occurrence Networks with General Biased Exchange-based Diffusion on Hyper-bag-graphs

The HyperBagGraph DataEdron: An Enriched Browsing Experience of Multimedia Datasets

Learning by stochastic serializations

Extracting localized information from a Twitter corpus for flood prevention

Exchange-Based Diffusion in Hb-Graphs: Highlighting Complex Relationships

Hypergraph Modeling and Visualisation of Complex Co-occurence Networks

On Adjacency and e-Adjacency in General Hypergraphs: Towards a New e-Adjacency Tensor

Adjacency and Tensor Representation in General Hypergraphs.Part 2: Multisets, Hb-graphs and Related e-adjacency Tensors

Structured nonlinear variable selection

Large-scale Nonlinear Variable Selection via Kernel Random Features

On Adjacency and e-adjacency in General Hypergraphs: Towards an e-adjacency Tensor

Adjacency Matrix and Co-occurrence Tensor of General Hypergraphs: Two Well Separated Notions

Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks

Forecasting and Granger Modelling with Non-linear Dynamical Dependencies

On Hölder projective divergences

Learning Leading Indicators for Time Series Predictions

Two-Stage Metric Learning