Events

Events

Views Navigation

Event Views Navigation

Calendar of Events

S Sun

M Mon

T Tue

W Wed

T Thu

F Fri

S Sat

0 events,

0 events,

0 events,

0 events,

0 events,

0 events,

0 events,

0 events,

0 events,

1 event,

IDSS Distinguished Seminars

0 events,

0 events,

1 event,

Statistics and Data Science Seminar Jonathan Niles-Weed (New York University)

0 events,

0 events,

1 event,

IDSS Distinguished Seminars David Blei (Columbia University)

0 events,

0 events,

0 events,

1 event,

Statistics and Data Science Seminar Ery Arias-Castro (University of California, San Diego)

0 events,

0 events,

0 events,

0 events,

0 events,

0 events,

1 event,

0 events,

0 events,

0 events,

0 events,

0 events,

0 events,

1 event,

Naive Feature Selection: Sparsity in Naive Bayes

0 events,

IDSS Distinguished Seminars

[POSTPONED] Guido Imbens – The Applied Econometrics Professor and Professor of Economics, Graduate School of Business, Stanford University

E18-304

*Please note: this event has been POSTPONED until Fall 2020* See MIT’s COVID-19 policies for more details.   About the author: Prof. Guido Imbens’ primary field of interest is Econometrics. Research topics in which he is interested include: causality, program evaluation, identification, Bayesian methods, semi-parametric methods, instrumental variables. Guido Imbens does research in econometrics and statistics.…

Find out more »

Statistics and Data Science Seminar

Matrix Concentration for Products

Jonathan Niles-Weed (New York University)
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…

Find out more »

IDSS Distinguished Seminars

[POSTPONED] The Blessings of Multiple Causes

David Blei (Columbia University)
E18-304

  *Please note: this event has been POSTPONED until Fall 2020* See MIT’s COVID-19 policies for more details. Title: The Blessings of Multiple Causes Abstract: Causal inference from observational data is a vital problem, but it comes with strong assumptions. Most methods require that we observe all confounders, variables that affect both the causal variables…

Find out more »

Statistics and Data Science Seminar

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…

Find out more »

Statistics and Data Science Seminar

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…

Find out more »

Online events

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,…

Find out more »


MIT Statistics + Data Science Center
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139-4307
617-253-1764