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large-scale machine learning and convex optimization francis bach inria - ecole normale supérieure paris france eurandom - march 2014 slides available at wwwdiensfr~fbachgradsto_eurandompdf…
non-convex optimization for machine learning1 prateek jain microsoft research india [email protected] purushottam kar iit kanpur [email protected] december 22,…
non-convex optimization for machine learning: design, analysis, and understanding tengyu ma a dissertation presented to the faculty of princeton university in candidacy for…
slide 1 convex sets (chapter 2 of convex programming) keyur desai advanced machine learning seminar michigan state university slide 2 why understand convex sets? slide 3…
convex analysis of submodular set functions for machine learningthesis by peter stobbe for the degree of the connections between convexity and submodularity are explored,
non-convex optimization for machine learning prateek jain microsoft research india outline • optimization for machine learning • non-convex optimization • convergence…
ar x iv :1 40 5 49 80 v1 m at h o c 2 0 m ay 2 01 4 theory of convex optimization for machine learning sébastien bubeck 1 1 department of operations research and financial…
a path following algorithm for the graph matching problem mikhail zaslavskiy, francis bach, and jean-philippe vert abstract—we propose a convex-concave programming approach…
convex optimization lieven vandenberghe university of california, los angeles tutorial lectures, machine learning summer school university of cambridge, september 3-4, 2009…
convex analysis for minimizing and learning submodular set functions thesis by peter stobbe in partial fulfillment of the requirements for the degree of doctor of philosophy…
a path following algorithm for the graph matching problem mikhail zaslavskiy francis bach and jean-philippe vert abstract—we propose a convex-concave programming approach…
statistical machine learning and convex optimization francis bach inria - ecole normale supérieure paris france École normale s u p É r i e u r e statmathappli 2017 fréjus…
history trends proximal gradient descent three applications optimization for machine learning with a focus on proximal gradient descent algorithm quanming yao department…
large-scale machine learning and convex optimization francis bach inria - ecole normale supérieure, paris, france École normale s u p É r i e u r e hausdorff institute,…
ar x iv :1 11 1. 64 53 v1 cs .l g 2 8 n ov 2 01 1 learning with submodular functions: a convex optimization perspective francis bach 1 1 inria - sierra project-team, laboratoire…
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convex analysis for minimizing and learning submodular set functions thesis by peter stobbe in partial fulfillment of the requirements for the degree of doctor of philosophy…
journal of machine learning research 13 2012 3539-3583 submitted 410 revised 412 published 1212 regularized bundle methods for convex and non-convex risks trinh-minh-tri…
november 9, 2016 draft new optimization methods for modern machine learning sashank j. reddi november 2016 school of computer science carnegie mellon university pittsburgh,…
1 convex sets, in this section, we introduce one of the most important ideas in economic modelling, in the theory of optimization and, indeed in much of modern analysis and