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Jun Wang
360 publications
Ke Sun
83 publications
Frank Nielsen
81 publications
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72 publications
Fabrizio Falchi
39 publications
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33 publications
Alexandros Kalousis
32 publications
Claudio Gennaro
30 publications
Henning Müller
21 publications
Yuan Chen
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Jason Ramapuram
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∙ 06/19/2023

Supervised Auto-Encoding Twin-Bottleneck Hashing

Deep hashing has shown to be a complexity-efficient solution for the App...

0 Yuan Chen, et al. ∙

∙ 01/25/2022

Cold Start Active Learning Strategies in the Context of Imbalanced Classification

We present novel active learning strategies dedicated to providing a sol...

0 Etienne Brangbour, et al. ∙

∙ 01/17/2022

H E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin Eosin regression

Computational pathology is a domain that aims to develop algorithms to a...

0 Niccoló Marini, et al. ∙

∙ 06/01/2021

Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features

Cross-modal retrieval is an important functionality in modern search eng...

0 Nicola Messina, et al. ∙

∙ 12/07/2020

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...

0 Etienne Brangbour, et al. ∙

∙ 08/12/2020

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

Despite the evolution of deep-learning-based visual-textual processing s...

0 Nicola Messina, et al. ∙

∙ 03/16/2020

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-...

0 Xavier Ouvrard, et al. ∙

∙ 05/28/2019

The HyperBagGraph DataEdron: An Enriched Browsing Experience of Multimedia Datasets

Traditional verbatim browsers give back information in a linear way acco...

0 Xavier Ouvrard, et al. ∙

∙ 05/27/2019

Learning by stochastic serializations

Complex structures are typical in machine learning. Tailoring learning a...

0 Pablo Strasser, et al. ∙

∙ 03/12/2019

Extracting localized information from a Twitter corpus for flood prevention

In this paper, we discuss the collection of a corpus associated to tropi...

0 Etienne Brangbour, et al. ∙

∙ 09/01/2018

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

Most networks tend to show complex and multiple relationships between en...

0 Xavier Ouvrard, et al. ∙

∙ 09/01/2018

Hypergraph Modeling and Visualisation of Complex Co-occurence Networks

Finding inherent or processed links within a dataset allows to discover ...

0 Xavier Ouvrard, et al. ∙

∙ 09/01/2018

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...

0 Xavier Ouvrard, et al. ∙

∙ 05/30/2018

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...

0 Xavier Ouvrard, et al. ∙

∙ 05/16/2018

Structured nonlinear variable selection

We investigate structured sparsity methods for variable selection in reg...

0 Magda Gregorova, et al. ∙

∙ 04/19/2018

Large-scale Nonlinear Variable Selection via Kernel Random Features

We propose a new method for input variable selection in nonlinear regres...

0 Magda Gregorova, et al. ∙

∙ 12/21/2017

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...

0 Xavier Ouvrard, et al. ∙

∙ 12/21/2017

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...

0 Xavier Ouvrard, et al. ∙

∙ 10/02/2017

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...

0 Magda Gregorova, et al. ∙

∙ 06/27/2017

Forecasting and Granger Modelling with Non-linear Dynamical Dependencies

Traditional linear methods for forecasting multivariate time series are ...

0 Magda Gregorova, et al. ∙

∙ 01/14/2017

On Hölder projective divergences

We describe a framework to build distances by measuring the tightness of...

0 Frank Nielsen, et al. ∙

∙ 07/07/2015

Learning Leading Indicators for Time Series Predictions

We consider the problem of learning models for forecasting multiple time...

0 Magda Gregorova, et al. ∙

∙ 05/12/2014

Two-Stage Metric Learning

In this paper, we present a novel two-stage metric learning algorithm. W...

0 Jun Wang, et al. ∙

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