Machine Learning Club at the Computational Biology Center (MSKCC)
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Seminar Series at Memorial Sloan-Kettering Cancer Center
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Takes place: every other Thursday @ 3pm in Zuckerman Research Center ZRC 679/681
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Description: This seminar series generally concerns the area of machine learning, with a certain focus on biological applications in mind (in particular genomics). The biweekly meetings alternate between invited talks given by external speakers and contributed talks by group members of the Rätsch lab.
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Organization and Program Chairs: Julia Vogt, Kjong-Van Lehmann and Gunnar Rätsch.
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Administratation: Kadeem Ho Sang.
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DatePresenterTopicAffiliationNotesRelated Links
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5/14/2015Meghana Kshirsagar (invited)Combine and Conquer: multitask learning for jointly modeling diseases at
the molecular level
Carnegie Mellon UniversityGuest Speaker
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4/30/2015Sandhya Prabhakaran (invited)Machine Learning Methods for HIV/AIDS Diagnostics and Therapy PlanningColumbia UniversityGuest Speaker
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4/16/2015Theofanis Karaletsos (contributed)Prioritizing the Crowd: Representation Learning On StringsMemorial Sloan-Kettering Cancer Center
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3/24/2015Max von Kleist (invited)Optimal Markov control theory to control HIV infectionFreie Universität BerlinGuest Speaker
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3/12/2015Sandhya Prabhakaran (invited)Columbia UniversityGuest Speaker
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2/19/2015Stepahnie Hyland (contributed)Word Embeddings with a Medical SlantMemorial Sloan-Kettering Cancer Center
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2/5/2015Melanie F. Pradier (contributed)Bayesian Non-Parametrics for Biomedical ApplicationMemorial Sloan-Kettering Cancer Center
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1/15/2015Javier Zazo (invited)Convex Optimization, Game Theory and Variational Inequality TheoryTechnical University of MadridGuest Speaker
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12/4/2014Zhiqiang Tan (invited)Mixture sampling, stochastic approximation, and weighted histogram analysis methodRutgers, The State University of New Jersey Guest Speaker
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11/14/2014Jennifer Listgarten (invited)Efficient and Powerful Methods for Genome and Epigenome-Wide Association StudiesMicrosoft ResearchGuest Speakerhttp://research.microsoft.com/en-us/um/people/jennl/
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10/30/2014Aika Terada (invited)Statistical significance for detecting combinatorial causal factors of diseasesAISTGuest Speaker
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10/9/2014David Sontag (invited)Semi-supervised learning of phenotypes and disease progression modelsNew York University Guest Speaker
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9/11/2014Richard Stein (contributed)Inferring microbial interaction networks and susceptibilities to external
perturbations from longitudinal metagenomic data
Memorial Sloan-Kettering Cancer Center
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8/21/2014Heiko Strathmann (invited)Kernel Adaptive Metropolis-HastingsUCL LondonGuest Speaker
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8/14/2014Kyle Beauchamp (contributed)Statistically optimal analysis of samples from multiple equilibrium statesMemorial Sloan-Kettering Cancer Center
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7/31/2014Kana Shimizu (contributed)All pairs similarity search for short reads and its application to
detection of breakpoint reads in cancer genome
Memorial Sloan-Kettering Cancer Center
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7/3/2014Raphael Pelossof (contributed)Learning the recognition code for transcription factor and RNA-binding protein families from high-throughput binding assaysMemorial Sloan-Kettering Cancer Center
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6/12/2014Bobby Bowman (contributed)Deconvolving RNA-Seq Data to Determine Constituent Cell TypesMemorial Sloan-Kettering Cancer Center
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5/22/2014Yuheng Lu (contributed)CCCP: The Concave-Convex Procedure and applications in solving SVM variants.Memorial Sloan-Kettering Cancer Center
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4/30/2014Yuan Qi (invited)From correlated biomarker selection to supervised association study and to multi-aspect Bayesian analysisPurdue UniversityGuest Speaker
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4/24/2014Bert Kappen (invited)Explaining missing heritability with Gaussian Process regressionRadboud University NijmegenGuest Speaker
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2/19/2014Christoph Lampert (invited)Learning with Asymmetric InformationInstitute of Science and Technology AustriaGuest Speaker
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2/13/2014Kjong Lehmann (contributed)Statistical Testing and Mixed Effect Models in Statistical Genetics Part 2Memorial Sloan-Kettering Cancer Center
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12/12/2013David Lopez (invited)Using Randomness to Discover Patterns in the Large-Scale.MPI Intelligent Systtems and University of CambridgeGuest Speakerhttp://media.nips.cc/nipsbooks/nipspapers/paper_files/nips26/14.pdf
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10/24/2013Fernando Perez-Cruz (invited)Bayesian nonparametric comorbidity analysis of psychiatric disordersAmazon
Department of Signal Theory and Communication at University Carlos III
Guest Speaker
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10/16/2013Marius Kloft (contributed)Introduction to Information TheoryMemorial Sloan-Kettering Cancer CenterVideo Lecture by David Mckayhttp://videolectures.net/mackay_course_01/
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10/1/2013Thomas Fuchs (invited)In the Midst of a Revolution: How Computational Pathology Thrives on Big DataCalifornia Institue of technology and Jet Propulsion LaboratoryGuest Speaker
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9/26/2013Kjong Lehmann (contributed)Introduction to Mixed Model AnalysisMemorial Sloan-Kettering Cancer CenterGWAS Special Meeting
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9/10/2013Theo Karaletsos (contributed)Generative vs. Dsicriminative - An introduction to Generative ModelsMemorial Sloan-Kettering Cancer Center
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8/16/2013Julia Vogt (contributed)Supervised and Unsupervised Transfer Learning & Recovering Networks from Distance DataMemorial Sloan-Kettering Cancer Centerhttp://jmlr.org/proceedings/papers/v25/prabhakaran12/prabhakaran12.pdf
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8/12/2013Manfred Warmuth (invited)Loss Function DesignUC Santa CruzGuest Speaker
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6/20/2013Marius Kloft (contributed)An Introduction to Statistical Learning TheoryMemorial Sloan-Kettering Cancer CenterTutorial
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6/6/2013David Sontag (invited)Method-of-Moment Algorithms for Learning Bayesian Networks (Continued)New York UniversityGuest Speaker
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5/23/2013David Sontag (invited)Method-of-Moment Algorithms for Learning Bayesian NetworksNew York UniversityGuest Speaker
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5/16/2013Marius Kloft & Gunnar Rätsch (contributed)Regression AlgorithmsMemorial Sloan-Kettering Cancer CenterDiscussion on "Regression" from Mehyar Mohri's "Foundation of Machine Learning"
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4/18/2013Theo Karaletsos (invited)Generative Models for Biological Image AnalysisMax Planck Institute for Intelligent SystemsTalk via Skype
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3/26/2013Xinghua Lou (contributed)Machine Learning in Histopathology Image AnalysisMemorial Sloan-Kettering Cancer CenterTutorial
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3/14/2013Marius Kloft (contributed)Gaussian Processes in Machine LearningMemorial Sloan-Kettering Cancer CenterGuided Discussion on Gaussian Processes in machine Learning by Carl Edward Ramussenhttp://www.cs.ubc.ca/~hutter/EARG.shtml/earg/papers05/rasmussen_gps_in_ml.pdf
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2/28/2013Marius Kloft (contributed)Gaussain ProcessesStanford UniversityVideo Lecture by Karl Rasmussenhttp://videolectures.net/mlss2012_cunningham_gaussian_processes/
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2/14/2013Marius Kloft (contributed)Gaussian ProcessesUniversity of CambridgeVideo Lecture by David McKay
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