ml.jhu.edu
Machine Learning @ Johns Hopkins UniversityThe large cross-departmental community of Machine Learning researchers at Johns Hopkins University (JHU).
http://ml.jhu.edu/
The large cross-departmental community of Machine Learning researchers at Johns Hopkins University (JHU).
http://ml.jhu.edu/
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Machine Learning @ Johns Hopkins University | ml.jhu.edu Reviews
https://ml.jhu.edu
The large cross-departmental community of Machine Learning researchers at Johns Hopkins University (JHU).
ml.jhu.edu
Machine Learning @ Johns Hopkins University | Apply
https://ml.jhu.edu/apply
Strong students are invited to apply to JHU for their Ph.D. or master’s degree. [Faculty candidates: Apply for jobs here. Machine learning at JHU is an active. Interest area. Students should apply to join the graduate program of the department that best fits their interests, for example:. Applied Math and Statistics. Electrical and Computer Engineering. Certain requirements will vary by department. However, department boundaries are quite permeable at JHU. Students ordinarily take coursework.
Machine Learning @ Johns Hopkins University | Affiliates
https://ml.jhu.edu/affiliates
Johns Hopkins scientists develop and apply cutting edge technology in a wide variety of fields of inquiry. In keeping with JHU’s collaborative and interdisciplinary culture, ML@JHU gathers ML practitioners from a variety of schools, departments, institutions and centers in order to exchange ideas, coordinate curriculum, work closely with experimental scientists and domain experts, and promote machine learning on campus. The Johns Hopkins University. The Whiting School of Engineering. Is consistently rate...
Machine Learning @ Johns Hopkins University | Talks
https://ml.jhu.edu/talks
Click on a talk title for details. To receive talk announcements by email, sign up for our mailing list. In return, please forward announcements of ML-related talks to announce (at) ml.jhu.edu. Thu 04/28/16, 01:30pm, Mergenthaler 111. Unveiling the mysteries in spatial gene expression. Bin Yu, UC Berkeley. Wed 04/27/16, 01:30pm, Gilman 50. Movie Reconstruction from Brain Signals: “Mind Reading”. Bin Yu, UC Berkeley. Mon 04/25/16, 12:10pm, Room W3008, School of Public Health. An ML talk in the CLSP Speake...
Machine Learning @ Johns Hopkins University | People
https://ml.jhu.edu/people
Filter by application area: Astrophysics. To find many more JHU faculty in each application area, follow links from the research. Page This page lists only members of the cross-cutting machine learning group. Dimensionality reduction, statistical signal processing, online learning, adversarial learning, stochastic approximation. CS 675: Statistical Machine Learning. CS 479/679: Representation Learning. Graphical models, transfer learning, structured regularization. CS 475: Machine Learning. AMS 735: Topi...
Machine Learning @ Johns Hopkins University | Courses
https://ml.jhu.edu/courses
AMS 437: Statistical Learning with Applications. BME 491/691: Learning Theory I. BioStats 646-649: Essentials of Probability and Statistical Inference I-IV. BioStats 776: Statistical Computing. CS 475: Machine Learning. CogSci 371/671: Bayesian Inference. CogSci 371/671: Formal Methods in Cognitive Science: Inference. CogSci 372/672: Formal Methods in Cognitive Science: Neural Networks. ECE 447: Introduction to Information Theory and Coding. AMS 640: Machine Learning. AMS 643: Graphical Models. AMS 692: ...
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Glen Coppersmith's Home Page
http://glencoppersmith.com/affiliations.html
Glen A. Coppersmith. Scientist, Statistician, Data Whisperer. Human Language Technology Center of Excellence [ HLTCOE. Applied Math and Statistics Department [ AMS. Center for Language and Speech Processing [ CLSP. Electrical and Computer Engineering Department [ ECE. Machine Learning Group [ ML. Intitute for Data Intensive Engineering and Science [ IDIES.
Mark Dredze: Home
http://www.cs.jhu.edu/~mdredze
Human Language Technology Center of Excellence (HLTCOE). Department of Computer Science. Center for Language and Speech Processing (CLSP). Center for Population Health Information Technology (CPHIT). Social Media and Health Research Group. Institute for Global Tobacco Control. 181 (410) 516-6786 ORCID:. I am on sabbatical for the 2015/16 academic year. I'm spending the year at Bloomberg LP. I am an assistant research professor of computer science. At Johns Hopkins University. I want to work with you.".
Social Media and Health Research: Press
http://www.socialmediahealthresearch.org/press
Social Media and Health Research. Human Language Technology Center of Excellence. Center for Language and Speech Processing. Whiting School of Engineering. For press inquires contact Prof Dredze:. Mdash; Our new AJPM paper on Healthy Mondays has been covered by Bloomberg business week. Mdash; Bloomberg news quotes Dr. Dredze in an article on disease outbreaks in social media. Mdash; The Times of London is covering our work on the economy and health. By doing their own analysis for the UK. And [ Day 2.
Social Media and Health Research: Papers
http://www.socialmediahealthresearch.org/papers
Social Media and Health Research. Human Language Technology Center of Excellence. Center for Language and Speech Processing. Whiting School of Engineering. For additional work by our group on a wide range of topics, see the publications listed on Prof. Dredze's website. As well as the Center for Language and Speech Processing. Glen Coppersmith, Mark Dredze, Craig Harman. Quantifying Mental Health Signals in Twitter. ACL Workshop on Computational Linguistics and Clinical Psychology. Carmen: A Twitter Geol...
Social Media and Health Research: Projects
http://www.socialmediahealthresearch.org/projects
Social Media and Health Research. Human Language Technology Center of Excellence. Center for Language and Speech Processing. Whiting School of Engineering. Our work spans a wide range of uses of social media for health applications. We focus on both novel methods of natural language processing and machine learning, as well as new applications. Digital Disease Surveillance: influenza. Mark Dredze, Michael J. Paul, Shane Bergsma, Hieu Tran. Carmen: A Twitter Geolocation System with Applications to ...Micha...
Social Media and Health Research: Collaborators
http://www.socialmediahealthresearch.org/collaborators
Social Media and Health Research. Human Language Technology Center of Excellence. Center for Language and Speech Processing. Whiting School of Engineering. Our group collaborates with colleagues within and external to Johns Hopkins on a variety of projects. John W. Ayers. Dr David Broniatowski is an Assistant Professor in the Department of Engineering Management and Systems Engineering at George Washington University. He conducts research in decision-making under risk, group decision-making, system a...
Social Media and Health Research: Resources
http://www.socialmediahealthresearch.org/resources
Social Media and Health Research. Human Language Technology Center of Excellence. Center for Language and Speech Processing. Whiting School of Engineering. We make a variety of data available concerning health trends derived from Twitter data. This includes influenza surveillance for a variety of locations. Code for downloading data using the Twitter streaming API. Michael Paul has additional resources on his homepage.
Johns Hopkins Machine Learning 600.475 Fall 2014: Links
http://www.cs475.org/fall2014/links
Machine Learning 600.475 Fall 2014. Machine Learning Research at Johns Hopkins. Machine Learning Group at Johns Hopkins. Chris Bishop. Pattern Recognition and Machine Learning. 2006. Most readings will come from Bishop. You are welcome to read other books in addition to or in place of Bishop if you find them helpful. Tom Mitchell. Machine Learning. 1997. Trevor Hastie, Robert Tibshirani, Jerome Friedman. The Elements of Statistical Learning: Data Mining, Inference and Prediction. 2009. Thanks to Hal Daume.
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Content on this page requires a newer version of Adobe Flash Player. Jakiego oprogramowania biurowego używasz? Twoje IP: 23.21.86.101. LOGIA14 - Zadanie 3 (warkocz). Utworzono: wtorek, 21, lipiec 2015 19:14. X EDYCJA KONKURSU FOTOGRAFICZNEGO MAZOWSZE BLISKIE SERCU. Utworzono: wtorek, 09, czerwiec 2015 20:06. Każda osoba chcąca wziąć udział w konkursie może zgłosić maksymalnie dwa zdjęcia nawiązujące do tegorocznego tematu konkursu ". Z rodziną przez Mazowsze. Zatytułowanego "Konkurs 2015" z załączonym sk...
Machine Learning @ Johns Hopkins University
At Johns Hopkins, the machine learning community aims to build systems that approach human intelligence, and which comb through massive datasets to answer questions that are beyond the capability of the unaided human mind. JHU’s researchers are pushing the state of the art in core inference methods and domain-specific modeling techniques. Our faculty and students develop innovative algorithms and fit increasingly nuanced models to empirical data. Mon Mar 05 - Pratik Chaudhari: A Picture of the Energy Lan...
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