International audienceThe many machine learning and data mining techniques produced over the last decades can prove invaluable assets in diverse fields, but choosing the most appropriate for a given application may be very difficult for a non-expert. Our objective is thus to provide modelling assistance using a meta-learning approach based on an evolutionary metaheuristic. We present the intended workflow of such modelling assistant and the expected challenges along our line of work
Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable...
This paper describes the use of meta-learning in the area of data mining. It describes the problems ...
Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient...
International audienceThe many machine learning and data mining techniques produced over the last de...
International audienceMachine learning has proven to be a powerful tool in diverse fields, and is ge...
International audienceDuring the past few years, research in applying machine learning (ML) to desig...
The majority of the algorithms used to solve hard optimization problems today are population metaheu...
The fields of machine meta-learning and hyper-heuristic optimisation have developed mostly independe...
In the last years, organizations and companies in general have found the true potential value of col...
International audienceIn this work, a framework based on maximum likelihood estimation and mutual in...
In: Encyclopedia of Systems Biology, W. Dubitzky, O. Wolkenhauer, K-H Cho, H. Yokota (Eds.), Springe...
Metaheuristic search algorithms look for solutions that either max-imise or minimise a set of object...
This book aims at attracting the interest of researchers and practitioners around the applicability ...
A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Informatio...
Today and always, human progress has been linked, among other aspects, to the capacity of facing pro...
Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable...
This paper describes the use of meta-learning in the area of data mining. It describes the problems ...
Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient...
International audienceThe many machine learning and data mining techniques produced over the last de...
International audienceMachine learning has proven to be a powerful tool in diverse fields, and is ge...
International audienceDuring the past few years, research in applying machine learning (ML) to desig...
The majority of the algorithms used to solve hard optimization problems today are population metaheu...
The fields of machine meta-learning and hyper-heuristic optimisation have developed mostly independe...
In the last years, organizations and companies in general have found the true potential value of col...
International audienceIn this work, a framework based on maximum likelihood estimation and mutual in...
In: Encyclopedia of Systems Biology, W. Dubitzky, O. Wolkenhauer, K-H Cho, H. Yokota (Eds.), Springe...
Metaheuristic search algorithms look for solutions that either max-imise or minimise a set of object...
This book aims at attracting the interest of researchers and practitioners around the applicability ...
A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Informatio...
Today and always, human progress has been linked, among other aspects, to the capacity of facing pro...
Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable...
This paper describes the use of meta-learning in the area of data mining. It describes the problems ...
Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient...
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