Events

Oct26

Highway Traffic Operations under Reliability and Security Failures

290 Hearst Memorial Mining Building
  • Saurabh Amin, MIT
MIT's Saurabh Amin will present Highway Traffic Operations under Reliability and Security Failures on October 26, 2018 at 4 p.m. in 290 Hearst Memorial Mining Building. Join us for cookies and beverages at 3:30 p.m.
Oct31

Rigidity and tolerance for perturbed lattices

1011 Evans Hall
  • Yuval Peres, Microsoft Research
Consider a perturbed lattice {v+Y_v} obtained by adding IID d-dimensional Gaussian variables {Y_v} to the lattice points in Z^d. Suppose that one point, say Y_0, is removed from this perturbed lattice; is it possible for an observer, who sees just the remaining points, to detect that a point is missing?
Oct31

Berkeley ACM A.M. Turing Laureate Lecture: The Land Sharks are on the Squawk Box with Michael Stonebraker

Banatao Auditorium Sutardja Dai Hall
  • Michael Stonebraker, M.I.T.
This Turing Award talk intermixes a bicycle ride across America during the summer of 1988 with the design, construction and commercialization of Postgres during the late 80’s and early ‘90’s. Striking parallels are observed, leading to a discussion of what it takes to build a new DBMS. Also, indicated are the roles that perseverance and serendipity played in both endeavors. Bio: Michael...
Nov02

Ultrafast Manipulation of Topological Phases in WTe2 Nanolayers: Nano Seminar Series

390 Hearst Memorial Mining Building
  • Prof. Aaron Lindenberg, Stanford Univ., Materials Science & Engineering
Manipulation of topological invariants in quantum materials plays a key role in topological switching applications and can stabilize emergent topological phases in otherwise trivial materials. Lattice strain has been proposed as one means of tuning these topological invariants. However, conventional means of applying strain are not extendable to controllable time-varying protocols. In particular,...
Nov02

Are New Vehicle Emissions Standards Effective and Efficient?

290 Hearst Memorial Mining Building
  • James Sallee, UC Berkeley
UC Berkeley's James Sallee will present Are New Vehicle Emissions Standards Effective and Efficient? on November 2, 2018 at 4 p.m. in 290 Hearst Memorial Mining Building. Join us for cookies and beverages at 3:30 p.m.
Nov05

CMU Health Care Analytics and IT Master's Degree

212 Cory Hall
Interested in taking your CS or EECS training to the next level in an industry in need of analytic innovators? The Master of Science in Health Care Analytics & Information Technology offered by the Heinz College of Carnegie Mellon will provide you with a #1 education in analytics and IT management to not only understand the complex business models of today’s health care systems, but also use...
Nov05

Sketching Big Data

Banatao Auditorium Sutardja Dai Hall
  • Jelani Nelson, Harvard Universty
A "sketch" is a data structure supporting some pre-specified set of queries and updates to a database while consuming space substantially (often exponentially) less than the information theoretic minimum required to store everything seen, and thus can also be seen as some form of functional compression. The advantages of sketching include less memory consumption, faster algorithms, and reduced...
Nov06

Tales from the front lines of wrangling earth science data: Berkeley Distinguished Lectures in Data Science

190 Doe Library
  • Deb Agarwal, Senior Scientist, Lawrence Berkeley National Laboratory, LBNL
Building the data capabilities and products needed to help enable understanding of watershed dynamics, tropical forests, carbon flux, and soil carbon. are just a few of the areas where we are working. This talk will describe the role inter-disciplinary data science is playing in helping to address these challenges. Many challenges encountered are not addressed by the tools available today. The...
Nov07

Why Deep Learning Works: Traditional and Heavy-Tailed Implicit Self-Regularization in Deep Neural Networks

1011 Evans Hall
  • Michael W. Mahoney, UC Berkeley
Random Matrix Theory (RMT) is applied to analyze the weight matrices of Deep Neural Networks (DNNs), including both production quality, pre-trained models and smaller models trained from scratch. Empirical and theoretical results clearly indicate that the DNN training process itself implicitly implements a form of self-regularization, implicitly sculpting a more regularized energy or penalty...
Nov09

'Nano' Implies Nonlinear Dynamics

390 Hearst Memorial Mining Building
  • R Stanley Williams, HP Labs
One thing that we who have worked in the nano area for the past 20 years keep claiming is that new properties and opportunities arise from materials crafted at the nanometer scale. One of the major changes is that the response of materials to stimuli becomes increasingly nonlinear, and that leads to a completely new set of dynamical properties. I will show how a single nanoscale device can be...