- Foundations
of Data Driven Algorithm Design
- Foundations of Machine Learning Reunion, Simons Institute. June 2018.

- Sample and Computationally
Efficient Active Learning Algorithms
- Information Theory and Applications Workshop. February 2018. [Video]
- NIPS Workshop Learning with Limited Labeled Data. December 2017 (this version).

- Foundations
of Data Driven Combinatorial Algorithm Selection
- NIPS Workshop on Discrete Structures in Machine Learning. December 2017.

- Learning Submodular
Functions with Applications to Multi-Agent Systems.
- Keynote Lecture at the 14th International Conference on Autonomous Agents and Multiagent System (AAMAS). May 2015.

- Learning Submodular
Functions.
- Berkeley EECS Department Colloquium Series. May 2015. [Video]

- Distributed Machine
Learning.
- IMA Workshop on Resource Trade-offs: Computation, Communication, and Information. May 2016.
- CORE Seminar. Univeristy of Washington. May 2016.
- Harvard CS Colloquium. November 2015. [Video]
- Dimacs Workshop on Big Data Through the Lens of Sublinear Algorithms. August 2015. [Video]
- Workshop on Massively Parallel Computation at FCRC. June 2015.

- Modern Aspects of
Unsupervised Learning
- 3rd International Workshop on Similarity-Based Pattern Analysis and Recognition. October 2015.

- Foundations for Learning in
The Age of Big Data
- Keynote talk at China Theory Week 2015.
- Workshop on Algorithmic Challenges in Machine Learning. January 2015.
- TTIC Colloquium,Toyota Technological Institute at Chicago. January 2014.
- CMU ML Special Seminar. November 2013.

- Clustering Perturbation
Resilient Instances
- Learning Theory Workshop at the DALI Meeting. April 2015.

- Modern
Machine Learning: New Challenges and Connections
- CMU SCS Special Seminar. February 2014.
- Georgia Scientic Computing Symposium. February 2014.

- Finding Endogenously
Formed Communities
- Workshop on Networks with Community Structure, Eurandom. January 2014.
- SODA 2013.

- Active Statistical
Query Model: Noise Tolerant and Differentially Private
Algorithms .
- Simons Workshop on Big Data and Differential Privacy. December 2013 [Video].
- Workshop for Women in Machine Learning. December 2013.

- Interactive Machine Learning, STOC 2013 Workshop on New (Theoretical) Challenges in Machine Learning.

- The Power of
Localization for Active and Passive Learning of Linear
Separators with Noise .
- IMA Workshop on Convexity and Optimization: Theory and Applications. [Video]
- Online Algorithms and Learning Workshop. Lorentz Center. November 2014.
- CATS Seminar, University of Maryland. September 2013 (see this version).

- Active and Passive Learning
of Linear Separators [Video].
- Allerton Conference on Communication, Control, and Computing, October 2013.
- COLT 2013.
- Information Theory and Applications Workshop 2013.

- Incorporating Unlabeled Data and Interaction in the Learning Process, Workshop on Provable Bounds in Machine Learning 2012.

- Distributed
Learning, Communication Complexity, and Privacy
- Simons Workshop on Parallel and Distributed Algorithms for Inference and Optimization. October 2013. [Video].
- COLT 2012 (see this version).

- Robust Interactive Learning, COLT 2012. [Video].

- Learning
Valuation Functions.
- PRiML Seminar, University of Pennsylvania. April 2013.
- Harvard University, Economics and Computer Science Seminar. January 2013.
- COLT 2012 (see this version). [Video]
- Microsoft Research New England, August 2011.
- Learning Theory Workshop at FOCM, July 2011.
- Workshop on Innovations in Algorithmic Game Theory, May 2011. [Video]

- Beyond Worst-Case Analysis in Machine Learning: Learning with Data Dependent Concept Spaces, Workshop on Beyond Worst-Case Analysis. 2011. [Video].

- Learning Submodular
Functions
- Theory Seminar, University of Chicago. January 2014.
- STOC 2011.
- The Annual Event of the ARC Center Georgia Institute of Technology. April 2011.
- The 5th Bertinoro Workshop on Random(ized) Graphs and Algorithms. May 2010
- SIAM Conference on Discrete Mathematics. June 2010.
- NIPS 2009 Workshop on Discrete Optimization in Machine Learning. December 2009.

- Robust Hierarchical
Clustering
- NIPS 2010 Workshop on Robust Statistical Learning.
- COLT 2010.

- Sample Complexity of
Active Learning
- NIPS 2009 Workshop on Adaptive Sensing, Active Learning and Experimental Design: Theory, Methods and Applications.

- Approximate Clustering
Without the Approximation [Video].
- Microsoft Research Redmond, July 2010.
- IBM Research Yorktown, December 2009.
- INFORMS, October 2009.
- Barriers in Computational Complexity Workshop, August 2009.
- SODA 2009 (see this version).

- Improved Equilibria via
Public Service Advertising
- INFORMS, October 2009.
- Toyota Technological Institute at Chicago (TTI-C). August 2009.
- SODA 2009.

- Clustering with Interactive Feedback , ALT 2008.

- New Theoretical Frameworks for Machine Learning, Thesis Defense, August 2008.

- A Theory of Learning and Clustering via Similarity Functions, China Theory Week, September 2007.

- Item Pricing for Revenue Maximization in Combinatorial Auctions, Dagsthul Workshop on Computational Social Systems and the Internet, July 2007.

- Margin Based Active Learning, COLT 2007.

- Thesis Proposal, CMU, May 2007.

- Mechanism Design, Machine
Learning and Pricing Problems
- Second Bertinoro Workshop on Algorithmic Game Theory (AGATE 2006).
- University of California at San Diego, October 2006.

- On Learning with Similarity
Functions
- Mathematical Foundations of Learning Theory Conference, May 2006.
- ICML 2006.

- Approximation Algorithms
and Online Mechanisms for Item Pricing, EC
2006.

- Mechanism Design via Machine
Learning
- FOCS 2005.
- NIPS 2005 Workshop on Value of Information in Inference, Learning and Decision-Making.

- An Augmented PAC Model
for Semi-Supervised Learning
- Toyota Technological Institute at Chicago (TTI-C), August 2005.
- COLT 2005.
- IBM Research T.J. Watson, June 2005.
- Microsoft Research Silicon Valley, May 2005.
- NIPS 2004 Workshop on (Ab)Use of Bounds.
- Mathematical Foundations of Learning Theory Conference, June 2004.

- Sponsored Search Auctions
Design via Machine Learning, ACM-EC 2005 Workshop on
Sponsored Search Auctions.

- Co-Training and Expansion:
Towards Bridging Theory and Practice, NIPS
2004.

- On Kernels, Margins, and
Low-dimensional Mappings
- IBM Research T.J. Watson, July 2005.
- CMU Theory Lunch, March 2004.