News Archive
 I am giving a keynote talk at the CSIRO MARS 2021  Machine Learning and Artificial Intelligence Conference (Jun 2021).
 I am a panelist at the Deep Learning and Security Workshop at the IEEE Security and Privacy Conference (May 2021).
 I am giving a talk at the Machine Learning Department at CMU (May 2021).
 I am giving a talk at the CCSP Seminar at University of Maryland (Apr 2021).
 I am giving a seminar at the Statistics Department at CMU (Mar 2021).
 I am giving a talk at the AI Seminar at the University of Alberta (Mar 202021).
 I am giving a Distinguished Lecture at the YINS Seminar at Yale (Mar 2021).
 I am giving a talk at the MIT LIDS Virtual Seminar (Feb 2021).
 I am giving a Keynote Talk at the Google Differential Privacy Workshop (Feb 2021).
 I am giving a talk at the UCLA Department Seminar (Jan 2021).
 I am giving a talk at Google Research (Sep 2020).
 I am giving a talk at the PrimlPIFODS Seminar at UPenn (Sep 2020).
 I am giving a talk at the Technion's Summer School on Computer Security (Sep 2020).
 I am giving a talk at the SILO Seminar at Univ of Wisconsin, Madison (Sep 2020).
 I am giving a talk at the Workshop on Adversarial Learning Methods for ML and DM at KDD (Aug 2020).
 I am giving a talk at the Montreal ML Opt Seminar (Aug 2020).
 I am giving a lecture on Adversarial Machine Learning at AI4All (Aug 2020).
 I am giving a talk at Baidu Research (Jun 2020).
 I am giving a talk at the Nasa Formal Methods Workshop on AI Safety (May 2020).[Slides]
 I am giving a Distinguished Lecture at Duke University, Department of Biostatistics (Feb 2020).
 I am speaking at the Keller Collquium in Caltech (Jan 2020).
 I am giving a talk at the Science meets Engineering of Deep Learning Workshop at NeurIPS 2019 (Dec 2019).
 I am giving a talk at the Trustworthy AI Symposium in Columbia University (Oct 2019).
 I am giving a talk at the AI Seminar at MIT (Oct 2019).
 I am giving a talk at NorthEastern University (Oct 2019).
 I am giving a Keynote Talk at the TTI Chicago Workshop on Recent Trends in Classification and Clustering. (Sep 2019)
 I am coorganizing a Workshop on Privacy in Machine Learning at NeurIPS 2019.
 Talk at the Simons Workshop on Information Theoretic Privacy (Mar 2019).
 I gave a talk at the NeurIPS 2018 Workshop on Deep Learning Theory and another at the NeurIPS Workshop on Privacy in Machine Learning (Dec 2018).
 Talk at the ICML 2018 Workshop on Deep Generative Models (Jul 2018).
 Two papers accepted to ICML 2018! Arxiv links here and here.
 New paper on actively learning from observational data now up on arxiv.
 New paper on spectral learning for DNA methylation data now up on arxiv.
 Talk at the NIPS Workshop on Nearest Neighbors for Modern Applications with Massive Data (Dec 2017).
 Talk at Southern California Theory Day (2017).
 Our paper on GANs got th
e Honorable Mention for Best Poster Award at the Southern California ML Symposium 2017.
 Tutorial at NIPS 2017 along with Anand Sarwate on differentially private machine learning.
 New paper on Bayesian Posterior Sampling with Renyi DP now up on arxiv.
 Two papers accepted to NIPS 2017!
 New paper on using machine learning to localize type errors now on arxiv.
 Paper accepted to OOPSLA 2017!
 New paper on composition of inferential privacy mechanisms now on arxiv.
 New paper on a theoretical analysis of adversarial learning now on arxiv.
 New paper on approximation and convergence properties of Generative Adversarial Networks now on arxiv.
 Paper accepted to ICML 2017!
 Two papers accepted to SIGMOD 2017!
 Google Faculty Research Award, 2017. Thanks, Google!
 Paper accepted to AISTATS 2017!
 I am a Tutorials CoChair for ICML 2017.
 Keynote talk at the 11th Annual Machine Learning Symposium at the New York Academy of Sciences (Mar 2017).
 I am an Area Chair for ICML 2017 and UAI 2017, and a PC Member for COLT 2017.
 I am the Publications Chair for COLT 2017.
 Talk at the Simons Workshop on Interactive Learning (Feb 2017).
 Paper accepted to NIPS 2016!
 Talk at the Simons Workshop on Uncertainty and Computation (Oct 2016).
 Upcoming talk at the Simons Workshop on Learning, Algorithm Design and Beyond WorstCase Analysis (Nov 2016).
 Talk at the Dagstuhl Workshop on Foundations on Unsupervised Learning (Sep 2016).
 Talk at the Google Learning, Privacy and Mobile Data Workshop (Sep 2016).
 I am an Area Chair for AISTATS 2017.
 I am organizing a Women in Machine Learning Theory (WiMLT) lunch at COLT 2016.
 Talk at the ICML Workshop on Theory and Practice of Differential Privacy (Jun 2016).
 Talk at the Wisconsin SaTC Workshop (Jun 2016).
 Paper accepted to UAI 2016!
 Paper accepted to COLT 2016!
 New preprint on differentially private Bayesian Learning now or arxiv.
 New preprint on online learning with abstentions now on arxiv.
 New preprint on privacypreserving statistics on correlated data now on arxiv.
 Keynote talk at AISTATS (May 2016).
 I am an Area Chair for ICML 2016, UAI 2016 and NIPS 2016, and a PC member for COLT 2016.
 Three papers accepted to NIPS 2015!
 I have been elected a Steering Committee Member for COLT.
 Talk at the Nexus of Information and Computation Theories Workshop at IHP Paris (Mar 2016).
 Talk at Imperial College, London, Oxford University and Gatsby, UCL (Mar 2016).
 I am coorganizing a NIPS 2015 Workshop on NonConvex Optimization for Machine Learning .
 Talk at the NIPS 2015 Workshop on Learning and Privacy with Incomplete Data and Weak Supervision.
 Talk at the Stochastic Methods in Game Theory Workshop at NUS Singapore (Nov 2015).
 I am an Area Chair for AISTATS 2016.
 New preprint on spectral learning for comparative epigenomics now available on arxiv.
 New preprint on active
learning now available on arxiv.
 Paper accepted to HCOMP 2015.

New preprint on feature learning via crowdsourcing now available on arxiv.
 Talk at UW MSR Summer Institute on Stochastic Processes, Learning and Optimization (Aug 2015).
 Paper accepted to IEEE Transactions on Information Theory.
 I am the PC CoChair for ALT 2015.
 Shachar Lovett and I are organizing a Workshop on Algorithmic Challenges in Machine Learning at UCSD.
 Slides for my tutorial with Anand Sarwate on Differential Privacy and Machine Learning at GlobalSIP/WIFS are now online! The tutorial is based on our survey on the same topic.
 Tutorial with Anand Sarwate on Differential Privacy and Machine Learning at WIFS 2014.
 Talk at Simons Workshop on Information Theory, Learning and Big Data (Mar 2015).
 Paper accepted to AISTATS 2015.
 I am an Area Chair for UAI 2015.
 New preprint on learning and privacy now available on arxiv.
 Talk at UT Austin (Feb 2015).
 Talk at Google Research (Feb 2015).
 Talk at the Algorithmic Challenges in Machine Learning Workshop (Jan 2015).
 Talk at Microsoft Research New York City (Nov 2014).
 Talk at Harvard University (Oct 2014).
 Talk at NorthEastern University (Oct 2014).
 Talk at Boston University (Oct 2014).
 Three papers accepted to NIPS 2014.
 New preprint on privacypreserving learning now available on arxiv.
 New preprint on nearest neighbor classification now available on arxiv.
 New preprint on active learning now available on arxiv.