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Statistical and Computational Tradeoffs
Computational limitations of statistical problems have largely been ignored or simply overcome by ad hoc relaxations techniques. -
Online Learning
In this line of research, we develop strategies to optimize utility in dynamic environments in an optimal and efficient fashion. -
Causal inference and applications to learning gene regulatory networks
Causal inference: Geometry of conditional independence structures for 3-node directed Gaussian graphical models.
News
Data Science and Big Data Analytics: Making Data-Driven Decisions
MIT xPro and IDSS offers an eight-week online course beginning October 23.
Monitoring network traffic more efficiently
Programming language plus simple circuit design could let routers report on their own operation.
Study: Preschoolers learn from math games — to a point
A study co-authored by Professor Esther Duflo finds games for pre-schoolers can improve conceptual math skills, however, the gains may not carry ...
Upcoming
Fri
22
Walking within growing domains: recurrence versus transience
September 22 @ 11:00 am - 12:00 pm
Fri
29
Optimal lower bounds for universal relation, and for samplers and finding duplicates in streams
September 29 @ 11:00 am - 12:00 pm
Oct
02
2017 Charles River Lectures on Probability and Related Topics
October 2 @ 9:30 am - 5:30 pm
Oct
06
Stochastics and Statistics Seminar
October 6 @ 11:00 am - 12:00 pm
Oct
13
Stochastics and Statistics Seminar
October 13 @ 11:00 am - 12:00 pm