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 Priml-PIFODS 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 co-organizing 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 Co-Chair 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 Worst-Case 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 (WiML-T) 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 pre-print on differentially private Bayesian Learning now or arxiv.
• New pre-print on online learning with abstentions now on arxiv.
• New pre-print on privacy-preserving 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 co-organizing a NIPS 2015 Workshop on Non-Convex 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 pre-print on spectral learning for comparative epigenomics now available on arxiv.
  
• New pre-print on active learning now available on arxiv.
  
• Paper accepted to HCOMP 2015.
  
• New pre-print on feature learning via crowd-sourcing 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 Co-Chair 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 pre-print 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 pre-print on privacy-preserving learning now available on arxiv.
• New pre-print on nearest neighbor classification now available on arxiv.
• New pre-print on active learning now available on arxiv.