September 2020
Mobility Forum: The Social Consequences Of Mobility Systems
Sandy Pentland
online
To build a dynamic community among the mobility and transportation researchers, the MIT Mobility Initiative (MMI) is organizing the "Mobility Forum: Frontier of Mobility Research,” a weekly seminar series showcasing the MIT scholarship. Register for Zoom info.
Find out more »Mobility Forum: Introducing the MIT Mobility Initiative
Jinhua Zhao
online
To build a dynamic community among the mobility and transportation researchers, the MIT Mobility Initiative (MMI) is organizing the "Mobility Forum: Frontier of Mobility Research,” a weekly seminar series showcasing the MIT scholarship. Register for Zoom info.
Find out more »August 2020
Applied Data Science Bootcamp Panel Discussion
online
Join the launch of the "Applied Data Science Bootcamp", a 12-week online bootcamp taught live by MIT IDSS faculty. IDSS professor Devavrat Shah and collaborators from Great Learning, an online education service provider and IDSS alliance member, will share insights on one of the fastest-growing domains in the digital economy, Data Science, and how it will play a critical part in shaping our future. Register now to be a part of the discussion: http://bit.ly/ADSB_Launch
Find out more »July 2020
Joint Webinar – Become a Master in Data Science
Presented by UTEC / IDSS
online
Join us on Thursday, July 16th at 12pm UYT (11am EDT) to learn more about this blended learning Master's program offered by Uruguay's Technological University (UTEC), with the academic support of IDSS. Registration for this webinar is strongly encouraged. To register, please email ds@datascience.edu.uy Learn more about the educational partnership between UTEC and IDSS.
Find out more »Aporta Advanced Program in Data Science & Global Skills webinar
Presented by Aporta / IDSS
Learn more about Aporta's Advanced Program in Data Science & Global Skills at this webinar! IDSS supports Aporta's learners in Peru through the MITx MicroMasters Program in Statistics and Data Science.
Find out more »May 2020
Data Science and Big Data Analytics: Making Data-Driven Decisions
online
Developed by 11 MIT faculty members at IDSS, this seven-week course is specially designed for data scientists, business analysts, engineers and technical managers looking to learn strategies to harness data. Offered by MIT xPRO. Course begins May 4, 2020.
Find out more »Naive Feature Selection: Sparsity in Naive Bayes
Alexandre d'Aspremont (ENS, CNRS)
online
Abstract: Due to its linear complexity, naive Bayes classification remains an attractive supervised learning method, especially in very large-scale settings. We propose a sparse version of naive Bayes, which can be used for feature selection. This leads to a combinatorial maximum-likelihood problem, for which we provide an exact solution in the case of binary data, or a bound in the multinomial case. We prove that our bound becomes tight as the marginal contribution of additional features decreases. Both binary and…
Find out more »April 2020
How to Trap a Gradient Flow
Sébastien Bubeck (Microsoft Research)
online
Abstract: In 1993, Stephen A. Vavasis proved that in any finite dimension, there exists a faster method than gradient descent to find stationary points of smooth non-convex functions. In dimension 2 he proved that 1/eps gradient queries are enough, and that 1/sqrt(eps) queries are necessary. We close this gap by providing an algorithm based on a new local-to-global phenomenon for smooth non-convex functions. Some higher dimensional results will also be discussed. I will also present an extension of the 1/sqrt(eps)…
Find out more »On Using Graph Distances to Estimate Euclidean and Related Distances
Ery Arias-Castro (University of California, San Diego)
online
Abstract: Graph distances have proven quite useful in machine learning/statistics, particularly in the estimation of Euclidean or geodesic distances. The talk will include a partial review of the literature, and then present more recent developments on the estimation of curvature-constrained distances on a surface, as well as on the estimation of Euclidean distances based on an unweighted and noisy neighborhood graph. – About the Speaker: Ery Arias-Castro received his Ph.D. in Statistics from Stanford University in 2004. He then took…
Find out more »Matrix Concentration for Products
Jonathan Niles-Weed (NYU)
online
Abstract: We develop nonasymptotic concentration bounds for products of independent random matrices. Such products arise in the study of stochastic algorithms, linear dynamical systems, and random walks on groups. Our bounds exactly match those available for scalar random variables and continue the program, initiated by Ahlswede-Winter and Tropp, of extending familiar concentration bounds to the noncommutative setting. Our proof technique relies on geometric properties of the Schatten trace class. Joint work with D. Huang, J. A. Tropp, and R. Ward.…
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