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Searching Results for ND6.17-28.13:
Data Collection, 2013-06-17, Bin Yu  (University of California, Berkeley)
Exploratory Data Analysis (EDA), 2013-06-17, Bin Yu  (University of California, Berkeley)
Linear Regression, 2013-06-18, Bin Yu  (University of California, Berkeley)
Generalized Linear Models, 2013-06-18, Bin Yu  (University of California, Berkeley)
Regularization: Model Selection and Lasso, 2013-06-19, Bin Yu  (University of California, Berkeley)
Structured Sparsity, 2013-06-19, Bin Yu  (University of California, Berkeley)
Bayesian Linear Model, 2013-06-20, David Madigan  (Columbia University)
Graphical Model (Theory Latent Models), 2013-06-20, David Madigan  (Columbia University)
Graphical Model Applications: Localization in Wireless Networks and Vaccine Response Modeling, 2013-06-21, David Madigan  (Columbia University)
Counter-factual Concepts, 2013-06-21, David Madigan  (Columbia University)
Randomized Algorithms for Scalable Data Analysis, 2013-06-21, Alexander Johannes Smola  (Carnegie Mellon University)
Randomized Algorithms for Scalable Data Analysis, 2013-06-21, Alexander Johannes Smola  (Carnegie Mellon University)
Optimization for Sparse Estimation, 2013-06-22, Julien Mairal  (INRIA)
More Structured Sparsity, 2013-06-22, Julien Mairal  (INRIA)
Boosting and Low-rank, 2013-06-24, Bin Yu  (University of California, Berkeley)
Ridge and SVM, 2013-06-24, Bin Yu  (University of California, Berkeley)
V4 Modeling, 2013-06-25, Bin Yu  (University of California, Berkeley)
Ggobi Multivariate Data, 2013-06-25, Mark H. Hansen  (Columbia University)
Massive Parallelization to Learn from Massive Data, 2013-06-25, Marc A. Suchard  (University of California, Los Angeles (UCLA))
Hands-on High-performance Statistical Computing Techniques, 2013-06-25, Marc A. Suchard  (University of California, Los Angeles (UCLA))
Lecture, 2013-06-25, Mark H. Hansen  (Columbia University)
Sparse Modeling Theory, 2013-06-26, Bin Yu  (University of California, Berkeley)
Model Averaging (mcmc), 2013-06-26, Mark H. Hansen  (Columbia University)
Lecture, 2013-06-26, Mark H. Hansen  (Columbia University)
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