======== Optimization Reading Group ======== This student-run reading group meets weekly to discuss methods and applications of optimization. ===== References ===== Here is a list of resources which group members have recommended. [[http://web.stanford.edu/class/ee364a/videos.html|Boyd's Convex Optimization Video Lectures]] [[http://web.stanford.edu/~hastie/StatLearnSparsity/| Hastie, Tibshirani & Wainwright Statistical Learning with sparsity]] Primarily about Lasso and its generalizations from a statistical perspective. [[http://www.offconvex.org/| Off the Convex Path]] A blog with reflections on the methods of convex optimization. [[http://blogs.princeton.edu/imabandit/| I'm a Bandit]] A blog on Probability, Optimization, and Statistics. The "Complexities of Optimization" course notes on this site are a great introduction to research-level optimization. ===== Schedule ===== ==== Fall 2017 ==== For Fall 2017, the seminar is held on Tuesdays from 1:10-2:00p in MSB 3240 ** Dates:** * 10/3: Organizational Meeting * 10/10: Robert: [[https://projecteuclid.org/euclid.aoms/1177729586| A Stochastic Approximation Method]] and {{::optimization_seminar:stochapproxpres.pdf| Slides}} * 10/17: Will * 10/24: Kirill * 10/31: Ji * 11/7: Yunshen * 11/21: Mikhail * 11/28: David W. * 12/5: Robert (special time of 12-1 pm, in room 2240) * 12/12: (Finals Week) ==== Previous Quarters ==== ** Spring 2017:** * 4/7: No seminar ([[http://appliedmath.ucmerced.edu/graduate/siam/conference2017|SIAM regional meeting]]) * 4/14: Robert: [[https://projecteuclid.org/download/pdf_1/euclid.aos/1176345872|Total-Variation Penalized Density Estimation]] * 4/21: Jiawei: [[http://www.springer.com/us/book/9783319276021|Dual Feasible Functions for Integer Programming]] * 4/28: Will: {{::conic_duality_talk.pdf|Three Excursions around Conic Duality}} (Relevant material: [[http://www.seas.ucla.edu/~vandenbe//lectures/conic.pdf|Conic Optimization]] and [[http://www.seas.ucla.edu/~vandenbe//lectures/symmetric.pdf|Symmetric Cones]], by L. Vandenberghe) * 5/5: Gabe [[https://arxiv.org/pdf/1312.5602.pdf|Reinforcement Learning]] * 5/12: No seminar ([[https://sites.google.com/view/bayopt17/|BayOpt conference]]) * 5/19: David H: [[http://coral.ise.lehigh.edu/usmex2016//files/2016/04/talks/morton.pdf|Graph Clustering]] * 5/26: Yunshen: Constrained Eigenvalue Problems [[http://www.sciencedirect.com/science/article/pii/0024379589904941|Ref 1]][[http://www.sciencedirect.com/science/article/pii/S0024379599002049|Ref 2]][[http://archive.ymsc.tsinghua.edu.cn/pacm_download/278/8727-CGLTR03122017.pdf|Ref 3]][[https://www.cs.cornell.edu/people/tj/publications/joachims_03a.pdf|Ref 4]] * 6/2: Ji: Saddle points in non-convex optimization [[https://arxiv.org/abs/1703.00887|Ref 1]][[https://arxiv.org/abs/1602.04915|Ref 2]][[https://arxiv.org/abs/1704.00708|Ref 3]] * 6/8: David W: [[https://dsweber2.files.wordpress.com/2016/03/qual_proposal_david_weber.pdf|Practice qual]] ** Winter 2017:** * 1/19: Roundtable talks * 1/26: Julio: [[http://faculty.nps.edu/joroyset/docs/ambiguity_11.pdf|Royset, Johannes O., and Roger JB Wets. "Variational Theory for Optimization under Stochastic Ambiguity." (2016).]] * 2/2: David H: [[https://arxiv.org/abs/1510.06421|Park, J. and Boyd, S. "Concave Quadratic Cuts for Mixed-Integer Quadratic Problems." (2015).]] * 2/9: David W: See the text by [[http://web.stanford.edu/~hastie/StatLearnSparsity/|Hastie et al]]. Also see [[https://web.stanford.edu/~hastie/glmnet/glmnet_alpha.html| Website for GLMNet package]]. * 2/17 (3p): Robert [[http://link.springer.com/article/10.1007/BF01581204|Douglas-Rachford Splitting in the Context of Proximal Point Algorithms]] * 2/23: Ji: [[https://arxiv.org/abs/1605.07272|Rong Ge, Jason D. Lee, and Tengyu Ma. "Matrix Completion has No Spurious Local Minimum"]] * 3/2: Will: [[http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.205.7345&rep=rep1&type=pdf|Eriksson, Olsson, Kahl. "Normalized Cuts Revisited: A Reformulation for Segmentation with Linear Grouping Constraints"]] * 3/10 (3p): Yiqun: [[http://web.stanford.edu/~hastie/StatLearnSparsity/| Hastie, Tibshirani & Wainwright Statistical Learning with sparsity]] * 3/16: Mikhail: [[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=paTAXiIAAAAJ&cstart=640&pagesize=100&sortby=pubdate&citation_for_view=paTAXiIAAAAJ:rTD5ala9j4wC|Multi-Objective Optimization Using Evolutionary Algorithms]]