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Séances de séminaire

Séminaire Algo - Mathias Weller

Mathias Weller

Tree Containment With Soft Polytomies

Bâtiment Lavoisier, salle LAV108

The Tree Containment problem has many important applications in the study of evolutionary history. Given a phylogenetic network N and a phylogenetic tree T whose leaves are labeled by a set of taxa, it asks if N...[details]

Séminaire A3SI+LRT - Jean-Francois Baffier

Jean-Francois Baffier (Tokyo Institute of Technology)

Study of compressed stack algorithms in limited memory environment

Room 260 (ESIEE PARIS)

Abstract: The need to run algorithms on limited-memory devices motivated our consideration for data structure in the settings where there is only a limit...[details]

Séminaire A3SI - Alexei Efros

Alexei Efros (UC Berkeley)

Self-supervision, Meta-supervision, Curiosity: Making Computers Study Harder

Seminar room B412 of the IMAGINE group (ENPC - Bat. Coriolis)

Abstract: Computer vision has made impressive gains through the use of deep learning models, trained with large-scale labeled data....[details]

Séminaire Algo - Boris Bukh

Boris Bukh (Carnegie Mellon University)

Mini-survey of additive combinatorics

Bâtiment Lavoisier, salle LAV108

Abstract: Additive combinatorics studies how sets behave under the basicarithmetic operations (addition, multiplication). The far-rangingapplicability of additive combinatorics throughou...[details]

Séminaire A3SI - François Malgouyres

François Malgouyres (Institut de Mathématiques de Toulouse)

Multilinear compressive sensing and an application to convolutional linear networks

Seminar room B412 of the IMAGINE group (ENPC - Bat. Coriolis)

Abstract: We study a deep linear network expressed under the form of a matrix factorization...[details]

Séminaire A3SI - Jyoti Maggu

Jyoti Maggu (IIIT Delhi)

Supervised Transform Learning

Room 210 (ESIEE PARIS).

Abstract: Representation learning techniques have gained popularity over the years. Machine Learning community is well aware of several representation learning tools, viz. AutoEncoders, Deep belief networks, Convo...[details]