[Seminar 1] "Collective computation and learning in nonlinear networks" by Dr. Slotine

Dear all,

Neural Computation Unit (Doya Unit) would like to invite you to a seminar as follows.

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Date: Tuesday, January 15
Time: 15:00-16:00
Venue: Seminar Room 503 - Lab1 Bldg.

Speaker: Prof. Jean Jacques Slotine
Massachusetts Institute of Technology

Title: Collective computation and learning in nonlinear networks

Abstract:  The human brain largely outperforms robotic algorithms in most tasks, using computational elements 7 orders of magnitude slower than their artificial counterparts. Similarly, current large scale machine learning algorithms require millions of examples and close proximity to power plants, compared to the brain's few examples and 20W consumption. We show that nonlinear systems tools, such as contraction analysis and virtual dynamical systems, yield simple but highly non-intuitive insights about collective computation in networks, and in particular the role of sparsity, and that they also suggest systematic mechanisms to build progressively more refined networks and novel algorithms through stable accumulation of functional building blocks and motifs. Imposing contraction and physics-based constraints may yield orders of magnitude improvements in computational efficiency in adaptive robotics and general machine learning. We discuss specifically contraction analysis of networks of natural gradient learners, asynchronous distributed adaptation, multiple time-scale primal-dual optimization, and linearization-free simultaneous localization and mapping.

Biolgraphy: Professor Jean-Jacques Slotine is Professor of Mechanical Engineering and Information Sciences, Professor of Brain and Cognitive Sciences, and Director of the Nonlinear Systems Laboratory. He received his Ph.D. from the Massachusetts Institute of Technology in 1983, at age 23. After working at Bell Labs in the computer research department, he joined the faculty at MIT in 1984. Professor Slotine teaches and conducts research in the areas of dynamic systems, robotics, control theory, computational neuroscience, and systems biology.
Research in Professor Slotine’s laboratory focuses on developing rigorous but practical tools for nonlinear systems analysis and control. These have included key advances and experimental demonstrations in the contexts of sliding control, adaptive nonlinear control, adaptive robotics, machine learning, and contraction analysis of nonlinear dynamical systems.
Professor Slotine is the co-author of two popular graduate textbooks, “Robot Analysis and Control” (Asada and Slotine, Wiley, 1986), and “Applied Nonlinear Control” (Slotine and Li, Prentice-Hall, 1991) and is one of the most cited researcher in both systems science and robotics. He was a member of the French National Science Council from 1997 to 2002, and a member of Singapore’s A*STAR SigN Advisory Board from 2007 t0 2010. He is currently a member of the Scientific Advisory Board of the Italian Institute of Technology. He has held Invited Professor positions at College de France, Ecole Polytechnique, Ecole Normale Superieure, Universita di Roma La Sapienza, and ETH Zurich.
Professor Slotine is the recipient of the 2016 Rufus Oldenburger Medal.
 

Prof. Slotine will also give a talk on Wednesday 16th from 15:00 – 16:00 at meeting room C016 Lab1 Bldg.
Please visit HERE for more information regarding the second seminar.

We hope to see many of you at the seminar.

Sincerely,
Kikuko Matsuo
Neural Computation Unit