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The objectives of the project TREMoLo are: 1. To study and characterize the usages of language registers in written texts. 2. To develop automatic methods to transform texts from its original register to another. 3. To build fundations for generalizing the approach to other stylistic components o
1 / Formalizing the reasoning of rescue process and data needed for the process of localization of victims in the mountains and propose a method suggesting the next question to ask the victim to improve the collection of location indices and thus facilitate decision-making process. 2 / Define metho
Deezer, Spotify, Pandora or Apple Music enrich the listening of music with data such as biography or albums by the same artist, and offer suggestions to listen to other artists or songs "similar" (without similarity explicitly defined). A journalist or a radio presenter often uses the Web and media
Project at a glance Crowdsourcing relies on potentially huge numbers of on-line participants to resolve data acquisition or analysis tasks. It is an exploding area that impacts various domains, ranging from scientific knowledge enrichment to market analysis support. But currently, existing crow
Matrix and tensor factorization methods provide a unifying view for a broad spectrum of techniques in machine learning and signal processing, providing both sensible statistical models for datasets as well as efficient computational procedures framed as decomposition algorithms. So far, algebraic or
Following the evolution of modern computational science, the field of evolutionary optimization is shifting rapidly to the big era where the large-scale nature of applications implies big optimization models, with a large number of decision variables and conflicting objective functions. Big multi-ob
Providing new technologies to access data implies to reconcile, on one hand, the expressivity of formal query languages and, on the other hand, the usability of these tools for the end user. For example, SQL is admitted as a query language in the majority of relational databases, but it suffers from
Today data is being generated at an unprecedented rate. Despite the phenomenal data growth, the human ability to comprehend data remains as limited as before. Therefore, the “Big Data” era is faced with an increasing gap between the growth of data and the human ability to comprehend the data – this
ROOT will develop numerical methods for solving important problems in computer graphics and vision via the optimal mass transport theory. These problems relate to histograms, and can be advantageously written and solved via regressions with loss functions involving optimal transport. These problems
Gaussian Processes are one of the most popular tools in Machine Learning and Statistics. They underly a wide range of techniques for smoothing data, fitting nonlinear classifiers or finding latent variable representations. The role of GPs in Bayesian statistics and Machine Learning is to provide
Building on recent advances in the field, we propose to enlarge the scope of automated rule mining to numerical and existential rules. The resulting constraints could be used to spot errors in the data or even to predict missing pieces in the knowledge. The particular challenge in the context of k
In recent years we have witnessed an explosion of successful applications of deep learning including speech recognition, automatic translation, self-driving cars, computers that can beat professional Go players, and recommender systems. Deep networks designed for these tasks have millions and billi
Fluorescence imaging and microscopy has a prominent role in life science and medical research. It consists of imaging specific cellular and intracellular objects of interest at the diffraction limit (200nm), using wide field as well as confocal microscopy, after tagging them with genetically enginee
Crowdsourcing platforms offer the unprecedented opportunity to connect easily on-demand task providers, or taskers, and on-demand task solvers, or workers, locally or world-wide, for paid or voluntary work, and for various kinds of tasks. By facilitating the accurate search of specific workers, othe
Bayesian methods are a popular class of statistical algorithms for updating scientific beliefs. They turn data into decisions and models, taking into account uncertainty about models and their parameters. This makes Bayesian methods popular among applied scientists such as biologists, physicists, or
The BIG4 project aims at developping new algorithms of statistical reconstruction of fields on grid, such as images or density fields, as well as provide an analysis environment through Web technologies. It will allow to create a synergistic platform and at high resolution to analyze Big Data. It w
We propose to develop algorithms and software for analyzing third generation sequencing data. Third generation is an emerging technology that promises to give a better picture for studying genomes, transcriptomes, metagenomes and metatranscriptomes of all living organisms. It will be key for discove
The PAMELA project aims at developing machine learning theories and algorithms in order to learn local and personalized models from data distributed over networked infrastructures. Our project seeks to provide first answers to modern information systems built by interconnecting many personal devices
Given the huge amount of unstructured data in bibliographic databases, but also the development of open knowledge bases, accessing the knowledge they contain require to have a global view of multiple heterogeneous sources of information. To achieve this purpose, the MIAM project aims at proposing me