I am a research scientist with broad interests in machine learning and artificial intelligence. My work on large scale learning and stochastic gradient algorithms has received attention in the recent years. I am also known for the DjVu document compression system. I joined Facebook AI Research in March 2015.
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Announcing version 2.0 of my Stochastic Gradient Descent package. This release provides implementations of the Stochastic Gradient Descent and Averaged Stochastic Gradient Descent algorithms for Linear SVMs and CRFs. The latter sometimes shows vastly superior performance. See the SGD package pages for details.
Ronan's masterpiece, "Natural Language Processing (Almost) from Scratch", has been published in JMLR. This paper describes how to use a unified neural network architecture to solve a collection of natural language processing tasks with near state-of-the-art accuracies and ridiculously fast processing speed. A couple thousand lines of C code processes english sentence at more than 10000 words per second and outputs part-of-speech tags, named entity tags, chunk boundaries, semantic role labeling tags, and, in the latest version, syntactic parse trees. Download SENNA!
Learning Semantics, Nips 2011 Workshop, Saturday December 17, 2011. Melia Sierra Nevada & Melia Sol y Nieve, Sierra Nevada, Spain.
This workshop is organized in collaboration with Antoine Bordes, Jason Weston, Ronan Collobert. This event should be very interesing: I believe that recent machine learning advances indicate new connections between machine learning and machine reasoning and lead to new opportunties for learning the semantics of the world.
Over the last couple of years, I progressively formulated an unusual idea about the connection between machine learning and machine reasoning. I have discussed this idea with many friends and I even gave a seminar in Montreal in 2008. It is described in this technical report.