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Looking for a Missing Signal
Leon Bottou

We know how to spot object in images, but we must learn on more images than a human can see in a lifetime. We know how to translate text (somehow), but we must learn it on more text than a human can read in a lifetime. We know how to learn playing Atari games, but we must learn it by playing more games than any teenager can endure. The list is long. We can of course try to pin this inefficiently to some properties of our algorithms. However, we can also take the point of view that there is possibly a lot of signal in natural data that we simply do not exploit. I will report on two works in this direction. The first one establishes that something as simple as a collection of static images contains nontrivial information about the causal relations between the objects they represent. The second one, time permitting, shows how an attempt to discover such a structure in observational data led to a clear improvement of Generative Adversarial Networks.

Author Information

Leon Bottou (Facebook AI Research)

Léon Bottou received a Diplôme from l'Ecole Polytechnique, Paris in 1987, a Magistère en Mathématiques Fondamentales et Appliquées et Informatiques from Ecole Normale Supérieure, Paris in 1988, and a PhD in Computer Science from Université de Paris-Sud in 1991. He joined AT&T Bell Labs from 1991 to 1992 and AT&T Labs from 1995 to 2002. Between 1992 and 1995 he was chairman of Neuristique in Paris, a small company pioneering machine learning for data mining applications. He has been with NEC Labs America in Princeton since 2002. Léon's primary research interest is machine learning. His contributions to this field address theory, algorithms and large scale applications. Léon's secondary research interest is data compression and coding. His best known contribution in this field is the DjVu document compression technology (http://www.djvu.org.) Léon published over 70 papers and is serving on the boards of JMLR and IEEE TPAMI. He also serves on the scientific advisory board of Kxen Inc .

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