
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...
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Finegrained Visual Textual Alignment for CrossModal Retrieval using Transformer Encoders
Despite the evolution of deeplearningbased visualtextual processing s...
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Tuning Ranking in Cooccurrence Networks with General Biased Exchangebased Diffusion on Hyperbaggraphs
Cooccurence networks can be adequately modeled by hyperbaggraphs (hb...
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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...
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Learning by stochastic serializations
Complex structures are typical in machine learning. Tailoring learning a...
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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...
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ExchangeBased Diffusion in HbGraphs: Highlighting Complex Relationships
Most networks tend to show complex and multiple relationships between en...
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Hypergraph Modeling and Visualisation of Complex Cooccurence Networks
Finding inherent or processed links within a dataset allows to discover ...
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On Adjacency and eAdjacency in General Hypergraphs: Towards a New eAdjacency Tensor
In graphs, the concept of adjacency is clearly defined: it is a pairwise...
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Adjacency and Tensor Representation in General Hypergraphs.Part 2: Multisets, Hbgraphs and Related eadjacency Tensors
HyperBagGraphs (hbgraphs as short) extend hypergraphs by allowing the h...
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Structured nonlinear variable selection
We investigate structured sparsity methods for variable selection in reg...
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Largescale Nonlinear Variable Selection via Kernel Random Features
We propose a new method for input variable selection in nonlinear regres...
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On Adjacency and eadjacency in General Hypergraphs: Towards an eadjacency Tensor
Adjacency between two vertices in graphs or hypergraphs is a pairwise re...
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Adjacency Matrix and Cooccurrence Tensor of General Hypergraphs: Two Well Separated Notions
Adjacency and cooccurrence are two well separated notions: even if they...
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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...
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Forecasting and Granger Modelling with Nonlinear Dynamical Dependencies
Traditional linear methods for forecasting multivariate time series are ...
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On Hölder projective divergences
We describe a framework to build distances by measuring the tightness of...
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Learning Leading Indicators for Time Series Predictions
We consider the problem of learning models for forecasting multiple time...
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TwoStage Metric Learning
In this paper, we present a novel twostage metric learning algorithm. W...
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Stephane MarchandMaillet
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