# Tutorials

**Recent Progress in High-Dimensional Learning**Simons Institute Tutorial, August 2020

Part 1:**Tensor Decompositions and Their Applications**

Part 2:**Robust Estimation in Parameter Learning**

Part 3:**Supervised Learning with Massart Noise**

Part 4:**Provable Algorithms for Inverse Problems in Physics?**

**Sum-of-Squares, with a View Towards Average-case Complexity**Kavli Institute Tutorial, January 2019

**Sum-of-Squares Proofs**, with Pablo ParriloSimons Institute Tutorial, August 2017

**Robustness Meets Algorithms (and Vice-Versa)**NUS Distinguished Lecture, January 2019

**HALG 2018 Invited Survey**, June 2018

**ICML 2017 Invited Tutorial**, August 2017

**Algorithmic Aspects of Inference****IHP Special Program Tutorial**, January 2016

**Tensor Decompositions and Their Applications**Learning at Scale (MADALGO), August 2014

**Extended Formulations and Information Complexity**Dagstuhl Tutorial, March 2014

**Polynomial Methods in Learning and Statistics****UAI 2013 Tutorial**, July 2013

**Institute for Advanced Study Members' Seminar**, March 2012

# Talks

**Learning with Massart Noise, and Connections to Fairness****Northwestern Quarterly Theory Workshop**, June 2020

CSAIL-MSR Trustworthy and Robust AI Workshop, June 2020

**Robustly Recovering a Signal, Under a Group Action**Stanford Theory Seminar, October 2019

ONR Program Review, October 2019

**Learning Gaussian Graphical Models without Condition Number Bounds**ICERM Workshop on Data Science, May 2019

Oberwolfach Workshop on High-Dimensional Statistics, May 2019

**Learning Restricted Boltzmann Machines**UT Austin Theory Seminar, March 2019

MIT MIFODS Workshop, January 2019

**The Paulsen Problem Made Simple**ICERM Workshop on Computational Algebra, May 2019

**Approximate Counting and the Lovasz Local Lemma**Harvard Probability and Random Matrix Theory Seminar, December 2017

Princeton Theory Lunch, December 2017

TTI CS Colloquium, October 2017

STOC 2017, June 2017

Institute for Advanced Study CSDM Seminar, March 2017

**Robustness Meets Algorithms**UPenn Theory Seminar, November 2019

Stanford Statistics Seminar, October 2019

MIT Applied Math Colloquium, September 2018

SWAT Invited Talk, June 2018

Princeton Center for Theoretical Science Workshop, May 2018

NYU Math and Data Seminar, April 2018

Simons Math+X Symposium at Rice, January 2018

**JASON Fall Meeting**, November 2017

Yale Statistics Seminar, October 2017

Summer Research Institute at EPFL, June 2017

Northeastern Theory Seminar, April 2017

MIT Stochastics and Statistics Seminar, March 2017

Simons Institute, November 2016

**Southern California Theory Day**, November 2016

Georgia Tech ARC Colloquium, October 2016

**Planted Clique, Sum-of-Squares and Pseudo-Calibration**Institute for Mathematics and Applications, May 2016

Simons Institute, May 2016

**How Robust are Thresholds for Community Detection?**CSAIL-MSR Trustworthy and Robust AI Workshop, January 2019

MIT MIFODS Workshop, June 2018

**Northwestern Quarterly Theory Workshop**, May 2017

MIT Statistics and Data Science Day, April 2017

**Beyond Matrix Completion**Princeton PACM Colloquium, March 2016

**FSTTCS 2015 Invited Talk**, December 2015

Harvard Big Data Conference, August 2015

European Meeting of Statisticians, July 2015

**New England Machine Learning Day**, May 2015

MIT Stochastics and Statistics Seminar, April 2015

NYU Theory Seminar, April 2015

Harvard Probability and Random Matrix Theory Seminar, March 2015

University of Chicago Theory Seminar, March 2015

**Simple, Efficient and Neural Algorithms for Sparse Coding**Simons Institute, March 2015

ITA 2015, February 2015

Workshop on Algorithmic Challenges in Machine Learning (UCSD), January 2015

Symposium on Learning, Algorithms and Complexity (IISc), January 2015

Workshop on Learning Theory (FOCM), December 2014

**Super-resolution, Extremal Functions and the Condition Number of Vandermonde Matrices**BIRS Workshop on Analytic Techniques in TCS, August 2018

STOC 2015, June 2015

MSR/MIT Reading Group, November 2014

Workshop on Sparse Fourier Transform (FOCS), October 2014

**New Algorithms for Dictionary Learning**Learning at Scale (MADALGO), August 2014

Curves and Surfaces, July 2014

Mathematical Foundations of Learning Theory, July 2014

COLT 2014, July 2014

Workshop on Overcoming Intractability in Unsupervised Learning (STOC), May 2014

**A Polynomial Time Algorithm for Lossy Population Recovery**Simons Institute, September 2014

Duke Algorithms Seminar, August 2014

ICERM Workshop on Spectral Methods, May 2014

ITA 2014, February 2014

FOCS 2013, October 2013

TCS+ Seminar, September 2013 (video)

Princeton Discrete Math Seminar, April 2013

Princeton Theory Lunch, April 2013

**An Information Complexity Approach to Extended Formulations**Simons Institute, April 2015

MIT TOC Colloquium, September 2013

STOC 2012, June 2013

**NYC Theory Day**, May 2013

Columbia Discrete Math Seminar, April 2013

**ARC Theory Day**, April 2013

Center for Computational Intractability Meeting, December 2012

**New Algorithms for Nonnegative Matrix Factorization and Beyond**Harvard CS Colloquium, October 2014

Learning at Scale (MADALGO), August 2014

UW CS Colloquium, November 2013

UT Austin CS Colloquium, April 2013

UCSD CS Colloquium, April 2013

Carnegie Mellon CS/MLD Colloquium, March 2013

Cornell CS Colloquium, March 2013

Princeton CS/PACM Colloquium, March 2013

MIT Applied Math Special Seminar, February 2013

Columbia IEOR/CS Colloquium, February 2013

MSR Silicon Valley Theory Seminar, February 2013

IBM TJ Watson Theory Seminar, February 2013

Caltech CMS Colloquium, January 2013

MSR New England Theory Seminar, January 2013

**An Almost Optimal Algorithm for Computing Nonnegative Rank****ISSAC 2015 Tutorial**, July 2015

SODA 2013, January 2013

**Learning Topic Models -- Going Beyond SVD**FOCS 2012, October 2012

**Computing a Nonnegative Matrix Factorization -- Provably**Cornell Theory Seminar, October 2012

IBM TJ Watson Theory Lunch, August 2012

Google Research NYC Theory Seminar, June 2012

Carnegie Mellon Theory Seminar, December 2011

University of Texas, Austin Theory Seminar, November 2011

**Finding Structure in Big Data**(popular talk)**Institute for Advanced Study Board of Trustees Meeting**, May 2012

**Nearly Complete Graphs Decomposable into Large Induced Matchings**STOC 2012, May 2012

Princeton Theory Lunch, April 2012

**Vertex Sparsification: An Introduction, Connections and Applications****WorKer 2015 Tutorial**, June 2015

Part I: Institute for Advanced Study, November 8th 2011

Part II: Institute for Advanced Study, November 15th 2011

**Pareto Optimal Solutions for Smoothed Analysts**Princeton Discrete Math Seminar, March 2012

Rutgers Discrete Math Seminar, February 2012

University of California, Berkeley Theory Seminar, September 2011

Workshop on Beyond Worst Case Analysis (Stanford), September 2011

STOC 2011, June 2011

**Vertex Sparsification and Oblivious Reductions**Columbia CS Colloquium, February 2012

Columbia Discrete Math Seminar, November 2011

DIMACS Theory Seminar, October 2011

UCLA CS Colloquium, March 2011

TTI CS Colloquium, March 2011

Stanford CS Colloquium, February 2011

USC CS Colloquium, January 2011

Georgia Tech ARC Colloquium, January 2011

Microsoft Research Silicon Valley Theory Seminar, January 2011

MIT Operations Research Seminar, December 2010

University of Washington Theory Seminar, December 2010

**Learning Mixtures of Gaussians**(video)International Workshop on Statistical Learning, June 2013

UCSD Theory Seminar, April 2013

Center for Computational Intractability Meeting, September 2011

Microsoft Research New England Theory Seminar, January 2011

Institute for Advanced Study CSDM Seminar, January 2011

Microsoft Research Redmond Theory Lunch, December 2010

Yale Statistics Seminar, November 2010

Carnegie Mellon Theory Seminar, September 2010

Microsoft Research Silicon Valley Theory Seminar, August 2010

IBM TJ Watson Theory Lunch, May 2010

**Capacitated Metric Labeling**SODA 2011, January 2011

**Extensions and Limits to Vertex Sparsification**STOC 2010, June 2010

**Approximation Algorithms for Multicommodity-Type Problems**Carnegie Mellon Theory Lunch, September 2010

China Theory Week, September 2010

Cornell Theory Seminar, February 2010

Princeton Theory Lunch, December 2009

University of California, Berkeley Theory Seminar, November 2009

Stanford Algorithms Seminar, November 2009

FOCS 2009, October 2009

MIT Combinatorics Seminar, September 2009

ATT Research Theory Seminar, May 2009

Bell Labs Theory Seminar, May 2009

**Some Results on Greedy Embeddings in Metric Spaces**Microsoft Research Redmond Theory Seminar, March 2009

FOCS 2008, October 2008