Philippe Rigollet

0:44:02

SDSCon 2024 - Philippe Rigollett

1:01:15

Distinguished Seminar in Optimization and Data: Philippe Rigollet (MIT)

0:48:48

The emergence of clusters in self-attention dynamics

0:58:08

'Optimal Transport for Statistics and Machine Learning' Prof. Philippe Rigollet, MIT

1:49:29

Day One: Panel - Statistics & Computation

0:59:03

The Sample Complexity of Multi-Reference Alignment - Philippe Rigollet

0:29:56

Geometric Aspects of Sampling and Optimization

0:01:37

Data Science and Big Data Analytics: Making Data-Driven Decisions

1:31:57

IMS Medallion Lecture: 'Statistical Optimal Transport”, Philippe Rigollet

1:17:12

19. Principal Component Analysis

1:18:05

17. Bayesian Statistics

1:16:53

20. Principal Component Analysis (cont.)

1:18:03

1. Introduction to Statistics

1:15:29

15. Regression (cont.)

0:59:15

Statistical and Computational aspects of Wasserstein Barycenters - P. Rigollet @ MAD+ (8 Apr 2020)

1:22:37

3. Parametric Inference

1:13:59

14. Regression (cont.)

1:17:57

4. Parametric Inference (cont.) and Maximum Likelihood Estimation

1:17:09

2. Introduction to Statistics (cont.)

1:02:06

'Matrix Concentration for Products'

1:00:32

On Using Graph Distances to Estimate Euclidean and Related Distances

1:16:02

13. Regression

0:17:53

Online learning in repeated auctions

0:07:59

Estimation Rates for Sparse Linear Cyclic Causal Models