Tentative Class Schedule
| Lec | Date (mm-dd) | Paper | Details | Presenter |
|---|---|---|---|---|
| 01. | Jan 22 | Course Overview | Arindam Banerjee | |
| 02. | Jan 27 | Class Canceled | Polar Vortex | |
| 03. | Jan 29 | Robert Tibshirani Regression Shrinkage and Selection via the Lasso Journal of the Royal Statistical Society: Series B (Methodological), 58:1, 1996. |
Arindam Banerjee Slides |
|
| 04. | Feb 03 | Optimization Review First order methods, Stochastic/Online Optimization, Mirror Descent Duality, KKT Conditions |
Arindam Banerjee Slides 1 Slides 2 |
|
| 05. | Feb 05 | Opt 1 | John Duchi, Shai Shalev-Shwartz, Yoram Singer, and Ambuj Tewari Composite Objective Mirror Descent Conference on Learning Theory (COLT), 2010 |
Mojtaba Kadkhodaie Elyaderani Slides |
| 06. | Feb 10 | Opt 2 | Anatoli Juditsky and Arkadi Nemirovski First-Order Methods for Nonsmooth Convex Large-Scale Optimization, I: General Purpose Methods Optimization for Machine Learning, 2011 |
Maziar Sanjabi Boroujeni Slides |
| 07. | Feb 12 | Spt 1 | Martin J. Wainwright Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using L1-Constrained Quadratic Programming (Lasso) IEEE Transactions on Information Theory, 55:5, 2183-2202, 2009 |
Morteza Mardani Slides |
| 08. | Feb 17 | Spt 2 | Peter J. Bickel, Ya'acov Ritov, and Alexandre Tsybakov Simultaneous analysis of Lasso and Dantzig Selector The Annals of Statistics, 37:4, 1705-1732, 2009 |
Neil Dhingra Slides |
| 09. | Feb 19 | Opt 3 | John Duchi, Elad Hazan, and Yoram Singer Adaptive Subgradient Methods for Online Learning and Stochastic Optimization Journal of Machine Learning Research, 12, 2121-2159, 2011 |
Farideh Fazayeli Slides |
| 10. | Feb 24 | Opt 4 | Huahua Wang and Arindam Banerjee Online Alternating Direction Method International Conference on Machine Learning (ICML), 2012 |
Morteza Mardani Slides |
| 11. | Feb 26 | Spt 3 | Sahand N. Negahban, Pradeep Ravikumar, Martin J. Wainwright, and
Bin Yu A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers Statistical Science, 27:4, 538--557, 2012 |
Neil Dhingra Slides |
| 12. | Mar 03 | Spt 4 | Venkat Chandrasekaran, Benjamin Recht, Pablo A. Parrilo, and
Alan S. Willsky The Convex Geometry of Linear Inverse Problems Foundations of Computational Mathematics, 12, 805-849, 2012 |
Farideh Fazayeli Slides |
| 13. | Mar 05 | Spt 5 | Yaniv Plan and Roman Vershynin Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach IEEE Transactions on Information Theory, 59:1, 482-494, 2013 |
Kuo-Shih Tseng Slides |
| 14. | Mar 10 | Opt 5 | John Duchi, Alekh Agarwal, and Martin Wainwright Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling IEEE Transactions on Automatic Control, 57:3, 592-606, 2012 |
Mojtaba Kadkhodaie Elyaderani Slides |
| 15. | Mar 12 | Opt 7 | Sebastian Bubeck and Nicolo Cesa-Bianchi Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems Foundations and Trends in Machine Learning, 5:1, 1-122, 2012 |
Konstantina Christakopoulou Slides |
| Mar 17 | Spring Break | |||
| Mar 19 | Spring Break | |||
| 16. | Mar 24 | Spt 6 | Garvesh Raskutti, Martin J. Wainwright, and Bin Yu Restricted eigenvalue properties for correlated Gaussian designs Journal of Machine Learning Research, 11, 2241-2259, 2010 |
Vidyashankar Sivakumar Slides |
| 17. | Mar 26 | Spt 7 | Mark Rudelson and Shuheng Zhou Reconstruction from anisotropic random measurements IEEE Transactions on Information Theory, 59:6, 3434-3447, 2013 |
Vidyashankar Sivakumar Slides |
| 18. | Mar 31 | Opt 8 | Lei Yuan, Jun Liu, and Jieping Ye Efficient Methods for Overlapping Group Lasso IEEE Transactions on Pattern Analysis and Machine Intelligence, 35:9, 2104-2116, 2013 |
Xingguo Li Slides |
| 19. | Apr 02 | Opt 9 | Andreas Argyriou, Rina Foygel, and Nathan Srebro Sparse Prediction with the k-Support Norm NIPS, 2012 |
Kuo-Shih Tseng Slides |
| 20. | Apr 07 | Opt 10 | (a) Ambuj Tewari, Pradeep Ravikumar, and Inderjit Dhillon Greedy Algorithms for Structurally Constrained High Dimensional Problems NIPS, 2011 (b) Martin Jaggi Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization ICML, 2013 |
Konstantina Christakopoulou Slides |
| 21. | Apr 09 | StL 1 | Pradeep Ravikumar, Martin J. Wainwright, Garvesh Raskutti, and
Bin Yu High-dimensional covariance estimation by minimizing l1-penalized log-determinant divergence Electronic Journal of Statistics, 5, 935-980, 2011 |
Maziar Sanjabi Boroujeni Slides |
| 22. | Apr 14 | StL 2 | Tony Cai, Weidong Liu and Xi Luo A Constrained L1 Minimization Approach to Sparse Precision Matrix Estimation Journal of American Statistical Association, 106:494, 594-607, 2011 |
Xingguo Li Slides |
| 23. | Apr 16 | StL 3 | (a) Han Liu, Fang Han, Ming Yuan, John Lafferty, and Larry
Wasserman High Dimensional Semiparametric Gaussian Copula Graphical Models The Annals of Statistics, 40:4, 2293-2326, 2012 (b) Lingzhou Xue and Hui Zou Regularized Rank-Based Estimation of High-Dimensional Nonparanormal Graphical Models The Annals of Statistics, 40:5, 2541-2571, 2012 |
Abhirup Mallik Slides |
| 24. | Apr 21 | Properties of optimizations used in large sparse precision matrix estimation | Guest Lecture: Adam Rothman Slides |
|
| 25. | Apr 28 | StL 4 | Pradeep Ravikumar, Martin J. Wainwright and John Lafferty High-Dimensional Ising Model Selection using L1-regularized Logistic Regression The Annals of Statistics, 38:3, 1287-1319, 2010 |
Abhirup Mallik Slides |
| 26. | April 30 | Project Presentations |
o) Fazayeli-Christakopoulou o) Boroujeni-Elyaderani |
|
| 27. | May 05 | Project Presentations | o) Sivakumar o) Li o) Mardani |
|
| 28. | May 07 | Project Presentations | o) Mallik o) Dhingra |