Presentation this Friday 11:00 in AA3195
Hi all, This Friday, 10:00 we have a presentation by Christian Gagné from Universite Laval. The room is AA3195. I hope to see many of you there. Title: Evolutionary Computation and Machine Learning for the Engineering of Intelligent Systems Abstract: Evolutionary computation consists in black-box population-based optimization techniques inspired by natural evolution. These metaheuristics are quite successful at solving problems hard to tackle with conventional methods, for example when dealing with strongly non convex multimodal functions, multiple objectives, or solutions represented a complex data structures (e.g., graphs, trees, symbolic expressions). Although evolutionary computation is often considered as a close sibling to machine learning, it is often badly understood and dismissed by researchers in the field, mostly given its ad hoc nature and the impression it lacks strong theoretical foundations. Such considerations are unfortunate, as many criticisms are not taking into account latest developments of the field, nor considering the use of powerful tools provided by evolutionary computation for tackling some of the difficult optimization problems of machine learning. In my talk, I will present the field of evolutionary computation, with a particular emphasis on how it can be used in the context of machine learning. I will also present some methods of evolutionary computing that are relying on machine learning. This will be illustrated by various works done in my group at Université Laval, where we are applying in synergy machine learning and evolutionary computation techniques for solving complex engineering problems. Presenter: Christian Gagné Professeur agrégé Laboratoire de vision et systèmes numériques Département de génie électrique et de génie informatique Université Laval, Québec (Québec), Canada http://vision.gel.ulaval.ca/~cgagne christian.gagne@gel.ulaval.ca
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Title says 11:00, body says 10:00... which one is it? On Tue, Feb 18, 2014 at 3:35 PM, Razvan Pascanu <r.pascanu@gmail.com> wrote:
Hi all,
This Friday, 10:00 we have a presentation by Christian Gagné from Universite Laval. The room is AA3195. I hope to see many of you there.
Title: Evolutionary Computation and Machine Learning for the Engineering of Intelligent Systems
Abstract: Evolutionary computation consists in black-box population-based optimization techniques inspired by natural evolution. These metaheuristics are quite successful at solving problems hard to tackle with conventional methods, for example when dealing with strongly non convex multimodal functions, multiple objectives, or solutions represented a complex data structures (e.g., graphs, trees, symbolic expressions). Although evolutionary computation is often considered as a close sibling to machine learning, it is often badly understood and dismissed by researchers in the field, mostly given its ad hoc nature and the impression it lacks strong theoretical foundations. Such considerations are unfortunate, as many criticisms are not taking into account latest developments of the field, nor considering the use of powerful tools provided by evolutionary computation for tackling some of the difficult optimization problems of machine learning.
In my talk, I will present the field of evolutionary computation, with a particular emphasis on how it can be used in the context of machine learning. I will also present some methods of evolutionary computing that are relying on machine learning. This will be illustrated by various works done in my group at Université Laval, where we are applying in synergy machine learning and evolutionary computation techniques for solving complex engineering problems.
Presenter: Christian Gagné Professeur agrégé
Laboratoire de vision et systèmes numériques Département de génie électrique et de génie informatique Université Laval, Québec (Québec), Canada http://vision.gel.ulaval.ca/~cgagne christian.gagne@gel.ulaval.ca
_______________________________________________ Lisa_labo mailing list Lisa_labo@iro.umontreal.ca https://webmail.iro.umontreal.ca/mailman/listinfo/lisa_labo
Sorry for the typo. The talk is at 11 AM Razvan On Tue, Feb 18, 2014 at 3:35 PM, Razvan Pascanu <r.pascanu@gmail.com> wrote:
Hi all,
This Friday, 10:00 we have a presentation by Christian Gagné from Universite Laval. The room is AA3195. I hope to see many of you there.
Title: Evolutionary Computation and Machine Learning for the Engineering of Intelligent Systems
Abstract: Evolutionary computation consists in black-box population-based optimization techniques inspired by natural evolution. These metaheuristics are quite successful at solving problems hard to tackle with conventional methods, for example when dealing with strongly non convex multimodal functions, multiple objectives, or solutions represented a complex data structures (e.g., graphs, trees, symbolic expressions). Although evolutionary computation is often considered as a close sibling to machine learning, it is often badly understood and dismissed by researchers in the field, mostly given its ad hoc nature and the impression it lacks strong theoretical foundations. Such considerations are unfortunate, as many criticisms are not taking into account latest developments of the field, nor considering the use of powerful tools provided by evolutionary computation for tackling some of the difficult optimization problems of machine learning.
In my talk, I will present the field of evolutionary computation, with a particular emphasis on how it can be used in the context of machine learning. I will also present some methods of evolutionary computing that are relying on machine learning. This will be illustrated by various works done in my group at Université Laval, where we are applying in synergy machine learning and evolutionary computation techniques for solving complex engineering problems.
Presenter: Christian Gagné Professeur agrégé
Laboratoire de vision et systèmes numériques Département de génie électrique et de génie informatique Université Laval, Québec (Québec), Canada http://vision.gel.ulaval.ca/~cgagne christian.gagne@gel.ulaval.ca
Razvan: Your subject said the talk is at 11am but your e-mail said 10am. Our speaker arrives around 10h30, so it should really be 11am. I checked and the room is reserved for 11am. TO ALL: THE TALK IS AT 11AM. -- Yoshua On Tue, Feb 18, 2014 at 3:35 PM, Razvan Pascanu <r.pascanu@gmail.com> wrote:
Hi all,
This Friday, 10:00 we have a presentation by Christian Gagné from Universite Laval. The room is AA3195. I hope to see many of you there.
Title: Evolutionary Computation and Machine Learning for the Engineering of Intelligent Systems
Abstract: Evolutionary computation consists in black-box population-based optimization techniques inspired by natural evolution. These metaheuristics are quite successful at solving problems hard to tackle with conventional methods, for example when dealing with strongly non convex multimodal functions, multiple objectives, or solutions represented a complex data structures (e.g., graphs, trees, symbolic expressions). Although evolutionary computation is often considered as a close sibling to machine learning, it is often badly understood and dismissed by researchers in the field, mostly given its ad hoc nature and the impression it lacks strong theoretical foundations. Such considerations are unfortunate, as many criticisms are not taking into account latest developments of the field, nor considering the use of powerful tools provided by evolutionary computation for tackling some of the difficult optimization problems of machine learning.
In my talk, I will present the field of evolutionary computation, with a particular emphasis on how it can be used in the context of machine learning. I will also present some methods of evolutionary computing that are relying on machine learning. This will be illustrated by various works done in my group at Université Laval, where we are applying in synergy machine learning and evolutionary computation techniques for solving complex engineering problems.
Presenter: Christian Gagné Professeur agrégé
Laboratoire de vision et systèmes numériques Département de génie électrique et de génie informatique Université Laval, Québec (Québec), Canada http://vision.gel.ulaval.ca/~cgagne christian.gagne@gel.ulaval.ca
_______________________________________________ Lisa_labo mailing list Lisa_labo@iro.umontreal.ca https://webmail.iro.umontreal.ca/mailman/listinfo/lisa_labo
The talk and visit is going to be Friday March 21st. -- Yoshua On Tue, Feb 18, 2014 at 3:35 PM, Razvan Pascanu <r.pascanu@gmail.com> wrote:
Hi all,
This Friday, 10:00 we have a presentation by Christian Gagné from Universite Laval. The room is AA3195. I hope to see many of you there.
Title: Evolutionary Computation and Machine Learning for the Engineering of Intelligent Systems
Abstract: Evolutionary computation consists in black-box population-based optimization techniques inspired by natural evolution. These metaheuristics are quite successful at solving problems hard to tackle with conventional methods, for example when dealing with strongly non convex multimodal functions, multiple objectives, or solutions represented a complex data structures (e.g., graphs, trees, symbolic expressions). Although evolutionary computation is often considered as a close sibling to machine learning, it is often badly understood and dismissed by researchers in the field, mostly given its ad hoc nature and the impression it lacks strong theoretical foundations. Such considerations are unfortunate, as many criticisms are not taking into account latest developments of the field, nor considering the use of powerful tools provided by evolutionary computation for tackling some of the difficult optimization problems of machine learning.
In my talk, I will present the field of evolutionary computation, with a particular emphasis on how it can be used in the context of machine learning. I will also present some methods of evolutionary computing that are relying on machine learning. This will be illustrated by various works done in my group at Université Laval, where we are applying in synergy machine learning and evolutionary computation techniques for solving complex engineering problems.
Presenter: Christian Gagné Professeur agrégé
Laboratoire de vision et systèmes numériques Département de génie électrique et de génie informatique Université Laval, Québec (Québec), Canada http://vision.gel.ulaval.ca/~cgagne christian.gagne@gel.ulaval.ca
_______________________________________________ Lisa_labo mailing list Lisa_labo@iro.umontreal.ca https://webmail.iro.umontreal.ca/mailman/listinfo/lisa_labo
participants (3)
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David Krueger -
Razvan Pascanu -
Yoshua Bengio