Summer 2017: MMLS at TTIC/UChicago. "On the Complexity of Learning from Label Proportions." slides

Spring 2017: ASA ML at Uptake. "Contextual Bandit Algorithms for Internet Scale Applications." slides

Spring 2017: ITA. "Inferring Likely Social Networks from Ordered Connectivity Information." slides

Fall 2016: UIC Data Science. "Algorithms for Interactive Machine Learning." slides

Fall 2016: UIC IDS. "Statistical Algorithms and the Planted Clique Problem." slides

Spring 2016: ITA. "Recovering Social Networks by Observing Votes." slides

Fall 2015: Northwestern. "Statistical Algorithms and the Planted Clique Problem." slides

Summer 2015: TTI-C. "Sampling Strategies for Feature-Efficient and Active Learning." slides

Spring 2015: Georgetown. "Weights and Measures: Fast and Active Prediction in the Era of Big Data." slides

Spring 2015: Emory. "Interactive Learning Across Domains." slides

Spring 2015: ITA. "Pessimistic Active Learning Using Robust Bias-Award Prediction." slides

Fall 2014: University of Arizona. "Statistical Algorithms and the Planted Clique Problem." slides

Fall 2014: GraphEx. "On Finding Planted Cliques in Random Graphs." slides

Summer 2014: Yahoo! Labs. "Boosting Approaches to Learning on a Feature Budget." slides

Spring 2014: Emory MathCS. "Weights and Measures: Prediction in the Era of Big Data." slides

Spring 2014: ITA. "Training-Time Optimization of a Budgeted Booster." slides

Spring/Summer 2014: ISAIM, AAAI. "On Boosting Sparse Parities." slides

Fall 2013: MSR-NYC. "On the Resilience of Biparite Networks." slides

Fall 2013: UIC Math. "On Finding Planted Cliques and Solving Random Linear Equations." slides

Spring 2013: CASSC Plenery Talk. "Bandit Algorithms for Internet-Scale Applications." slides

Spring 2013: TTI. "New Algorithms for Contextual Bandits." slides

Summer 2012: Stony Brook, MSR-NYC. "Statistical Algorithms and the Planted Clique Problem" slides

Spring/Summer/Fall 2012: CMU, Google Research, UAlberta, UIC. "New Algorithms for Contextual Bandits." slides

Spring 2012: UIC MSCS. "The Complexity of Statistical Algorithms." slides

Spring 2012: Sandia Labs, Bell Labs, William and Mary, MIT-LL. "From Queries to Bandits: Learning by Interacting." slides

Fall 2011: ALT. "On Noise-Tolerant Learning of Sparse Parities and Related Problems." slides

Fall 2011: UPenn, Yale, Georgia Tech. "The Complexity of Statistical Algorithms." (updated) slides

Summer 2011: ICML. "Boosting on a Budget: Sampling for Feature-Efficient Prediction." slides

Spring 2011: AISTATS. "Contextual Bandit Algorithms with Supervised Learning Guarantees." slides

Fall 2010: ALT. "Lower Bounds on Learning Random Structures with Statistical Queries." slides

Fall 2010: ALT. "Inferring Social Networks from Outbreaks." slides

Summer 2010: Ben Gurion Univ., Yahoo! Research, Georgia Tech. "New Algorithms for Contextual Bandits." slides

Summer 2010: ICML/COLT Budgeted Learning Workshop. "Boosting on a Feature Budget." slides

Spring 2010: ARC at Georgia Tech. "Active Learning of Interaction Networks." slides

Spring 2010: Santa Fe Institute. "Learning Social Networks, Actively and Passively." slides

Spring 2010: IBM TJ Watson. "Learning Analog Circuits, Graphical Models, and Social Networks by Injecting Values." slides

Fall 2009: ALT. "Learning Finite Automata Using Label Queries." slides

Summer 2009: Thesis Defense. "Active Learning of Interaction Networks." slides

Fall 2008: ALT. "Optimally Learning Social Networks with Activations and Suppressions." slides

Summer 2008: COLT. "Learning Acyclic Probabilistic Circuits Using Test Paths." slides

Spring 2008: Yahoo! Research NY. "Learning Hidden Circuits and (Social) Networks by Injecting Values." slides

Fall 2007: Machine Learning Lunch at UMass Amherst. "Learning Hidden Graphs and Circuits with Query Access." slides

Summer 2007: COLT. "Learning Large-Alphabet and Analog Circuits with Value Injection Queries." slides

Fall 2006: Yale. "Learning Graphs with Queries."slides

Summer/Fall 2006: ICML, Princeton Univ., NYAS, Yale. "How Boosting the Margin Can Also Boost Classifier Complexity." slides

Fall 2013: UMS Planary Talk. "Three Great Ideas in Computing." slides

Spring 2013: UIC. "Introduction to Boosting" on work mostly by Freund and Schapire. slides

Spring 2007: Yale. "Hardness Results for Learning DNF" on papers by Alekhnovich, Braverman, Feldman, Klivans and Pitassi. slides

Spring 2007: Yale. "Boosting the Margin" on 4 papers authored among Freund, Schapire, Bartlett, Lee, Breiman, and Reyzin. slides

Spring 2006: Yale. "Go is PSPACE Hard" by Lichtenstein and Sipser. slides