
-
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...
read it
-
Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders
Despite the evolution of deep-learning-based visual-textual processing s...
read it
-
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-...
read it
-
The HyperBagGraph DataEdron: An Enriched Browsing Experience of Multimedia Datasets
Traditional verbatim browsers give back information in a linear way acco...
read it
-
Learning by stochastic serializations
Complex structures are typical in machine learning. Tailoring learning a...
read it
-
Extracting localized information from a Twitter corpus for flood prevention
In this paper, we discuss the collection of a corpus associated to tropi...
read it
-
Exchange-Based Diffusion in Hb-Graphs: Highlighting Complex Relationships
Most networks tend to show complex and multiple relationships between en...
read it
-
Hypergraph Modeling and Visualisation of Complex Co-occurence Networks
Finding inherent or processed links within a dataset allows to discover ...
read it
-
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...
read it
-
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...
read it
-
Structured nonlinear variable selection
We investigate structured sparsity methods for variable selection in reg...
read it
-
Large-scale Nonlinear Variable Selection via Kernel Random Features
We propose a new method for input variable selection in nonlinear regres...
read it
-
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...
read it
-
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...
read it
-
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...
read it
-
Forecasting and Granger Modelling with Non-linear Dynamical Dependencies
Traditional linear methods for forecasting multivariate time series are ...
read it
-
On Hölder projective divergences
We describe a framework to build distances by measuring the tightness of...
read it
-
Learning Leading Indicators for Time Series Predictions
We consider the problem of learning models for forecasting multiple time...
read it
-
Two-Stage Metric Learning
In this paper, we present a novel two-stage metric learning algorithm. W...
read it