New York, NY 10027  Prof. Blei and his group develop novel models and methods for exploring, understanding, and making predictions from the massive data sets that pervade many fields. Commento e attualizzazione | Gianfranco Ravasi | download | Z-Library. Yixin Wang, Dhanya Sridhar, David Blei. Supervisor: David Blei and Simon Tavar e Research Intern, Google Brain, Mountain View, CA May 2019{August 2019 Supervisor: George Tucker and Chelsea Finn Research Intern, Quantlab Financial LLC, Houston, TX June 2017{August 2017 Supervisor: Joe Masters Data Science Intern, HP Lab, Austin, TX June 2016{August 2016 Supervisor: Lakshminarayan Choudur “Text-based Ideal Points” (with David Blei and Keyon Vafa) OTHER ACADEMIC PUBLICATIONS: “Labor Market Institutions in the Gilded Age of American Economic History” (with Noam Yuchtman) -In Oxford Handbook of American Economic History, edited by Lou Cain, … fit (word) Note: if you choose really high n-grams, the feature space dimension can explode ! Supervisor: David Blei and Simon Tavar e Research Intern, Google Brain, Mountain View, CA May 2019{August 2019 Supervisor: George Tucker and Chelsea Finn Research Intern, Quantlab Financial LLC, Houston, TX June 2017{August 2017 Supervisor: Joe Masters Data Science Intern, HP Lab, Austin, TX June 2016{August 2016 Supervisor: Lakshminarayan Choudur Articles Cited by Co-authors. David M. Blei 3 8. 2017. Machine Learning Statistics Probabilistic topic models Bayesian nonparametrics Approximate posterior inference. David Blei. Some other info about me here. The thrusts are (a) scalable inference and (b) model checking. Accepted to Machine Learning. Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data: David Blei, Robert Donnelly, Francisco Ruiz, Tobias Schmidt Proceedings of the National Academy of Sciences. Hosted by Prof. David M. Blei 2015 – 2016 (Competitive) Ph.D. Advisors: George Hripcsak and David Blei Harvard. Distinguished invited lectures 2019 J. James Woods Lecture Series, Butler University. [11] A sparse sampling algorithm for near-optimal planning in large Markov decision processes. Advisor: Hanna Wallach. Honorable mention, Marr Prize for Best Student Paper, Twenty-Sixth Annual Conference of the Cognitive Science Society, 2004, for “Using physical theories to infer hidden causal … Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis. In Submission. Michael Kearns, Yishay Mansour and Andrew Y. Ng. In addition to working on topic models, Blei and his group have created generic algorithms for scaling a wide class of statistical models to massive data sets. Prof. Blei and his group develop novel models and methods for exploring, understanding, and making predictions from the massive data sets that pervade many fields. Journal of Machine Learning Research, 3:993-1022, 2003. 20. Francisco Ruiz, David Blei: Annals of Applied Statistics (forthcoming), 2019. I am interested in applying machine learning methods to uncover patterns in large data sets. I am open to applicants interested in many kinds of applications and from any field. • Working with Prof. David M. Blei and Prof. Zoubin Ghahramani • Research topics: Probabilistic models for econometrics (shopping and location data) and electronic health records. David B. Dunson Arts and Sciences Distinguished Professor of Statistical Science My research focuses on developing new tools for probabilistic learning from complex data - methods development is directly motivated by challenging applications in ecology/biodiversity, neuroscience, environmental health, criminal justice/fairness, and more. 2008 David M. Blei 2015 – 2016 ( Competitive ) Ph.D blei_cv.pdf David Blei, L.... Domeniconi ), SIAM About Alexander M. Rush, David M. Blei is a fellow of the ACM 55... 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