Computational limitations of statistical problems have largely been ignored or simply overcome by ad hoc relaxations techniques.
Causal inference: Geometry of conditional independence structures for 3-node directed Gaussian graphical models.
Learning problems that involve combinatorial objects are ubiquitous - they include the prediction of graphs, assignments, rankings, trees, groups of discrete labels or preferred sets of a user; the expression of prior structural knowledge for regularization, the identification of sets of important variables, or inference in discrete probabilistic models.
The Statistics and Data Science Center is an MIT-wide focal point for advancing research and education programs related to statistics and data science. The Center was created in 2015 with the goal of formalizing and consolidating efforts in statistics at MIT. The Center’s academic mission is to host and develop new academic programs, from a minor to a PhD in statistics and data science.
This August it was announced that CSAIL principal investigator and MIT professor Stefanie Jegelka will receive funding for her research on geomet...
In an interview with a WTTW's Chicago Tonight, Professor Devavrat Shah explains why a 14 coin flip winning streak for the Chicago Bears make sens...
Congratulations to Professors Shah and Rigollet!