Convex Optimization 凸优化2020春季学期

mind

Convex Optimization 凸优化2020春季学期




课程目录：
├──Books  
|   ├──bv_cvxbook.pdf  7.97M
|   └──First-order Methods in.pdf  7.45M
├──HW  
|   └──CVX2020HW1.zip  93.43kb
├──Lecture_notes2019Spring  
|   └──Lecture_notes2019Spring.zip  367.78M
├──Project  
|   ├──[1]6G  
|   |   ├──[6G_TWC20]Intelligent Reflecting Surface Enhanced Wireless.pdf  1.82M
|   |   └──[6G_TWC20]Weighted Sum-Rate Maximization for.pdf  890.92kb
|   ├──[2]edgeML  
|   |   ├──[JMLR20]Fast and Communication Efficient Framework for Distributed Machine Learning.pdf  2.25M
|   |   ├──[JSAIT20]Stochastic Gradient Coding for Straggler.pdf  1.09M
|   |   ├──[Martin_arXiv20]An algorithmic framework for fast federated optimization.pdf  2.20M
|   |   └──[TSP20]High-Dimensional Stochastic Gradient Quantization for Communication.pdf  1.36M
|   ├──[3]LearnOpt  
|   |   ├──[ICLR17_Li]learning_to_optimize.pdf  908.78kb
|   |   ├──[JMLR16]Active Learning for Multi-Objective Optimization.pdf  1.55M
|   |   ├──[JSAC20]Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement.pdf  3.51M
|   |   ├──[PAMI20_Xu]ADMM-CSNet.pdf  5.82M
|   |   ├──[TSP19_Eisen]Learning Optimal Resource Allocations.pdf  950.98kb
|   |   └──[TSP20]Learning Proximal Operator Methods .pdf  2.12M
|   ├──[4]Optimization  
|   |   ├──[MP17]DC for sparsity optimization problems.pdf  1.09M
|   |   └──[SIAM13]Low-Rank Matrix Completion by Riemannian Optimization.pdf  1.10M
|   ├──latex_template.zip  158.05kb
|   ├──project_cvx.pdf  112.26kb
|   └──Ref for Project(Up-to-date).pdf  72.21kb
├──[01]Introduction  
|   ├──Introduction1.MP4  388.45M
|   ├──Introduction2.MP4  236.68M
|   ├──Introduction3.MP4  138.31M
|   ├──Introduction4.MP4  191.72M
|   ├──Introduction_Spring2020.pdf  3.28M
|   └──Introduction_Spring2020_note.pdf  3.78M
├──[02]ConvexSet  
|   ├──Convex Set.pdf  479.63kb
|   ├──Convex Set_note.pdf  5.03M
|   ├──CVXSet1.MP4  86.71M
|   ├──CVXSet2.MP4  299.63M
|   ├──CVXSet3.MP4  278.38M
|   └──CVXSet4.MP4  483.62M
├──[03]convexfunctions  
|   ├──convexfunctions.pdf  320.90kb
|   ├──convexfunctions01.MP4  340.64M
|   ├──convexfunctions02.MP4  338.99M
|   ├──convexfunctions03.MP4  376.73M
|   └──convexfunctions_note.pdf  6.13M
├──[04]convexproblems  
|   ├──convexproblems.pdf  606.46kb
|   ├──convexproblems01.MP4  424.23M
|   ├──convexproblems02.MP4  789.75M
|   ├──convexproblems03.MP4  587.33M
|   ├──convexproblems04.MP4  424.81M
|   └──convexproblems_note.pdf  14.30M
├──[05]Lagrangeduality  
|   ├──Lagrangeduality.pdf  206.16kb
|   ├──Lagrangeduality01.MP4  229.95M
|   ├──Lagrangeduality02.MP4  130.94M
|   ├──Lagrangeduality03.MP4  572.77M
|   └──Lagrangeduality_note.pdf  4.51M
├──[06]DCP  
|   ├──CVXDCP.MP4  368.66M
|   ├──CVXDCP.pdf  598.06kb
|   └──CVXDCP_note.pdf  1.29M
├──[07]grad_descent_unconstrained  
|   ├──grad_descent_unconstrained-note.pdf  47.98M
|   ├──grad_descent_unconstrained.pdf  4.35M
|   ├──grad_descent_unconstrained01.MP4  381.22M
|   ├──grad_descent_unconstrained02.MP4  570.76M
|   ├──grad_descent_unconstrained03.MP4  360.24M
|   └──StrongConvexSmooth.pdf  339.66kb
├──[08]grad_descent_constrained  
|   ├──grad_descent_constrained-note.pdf  26.60M
|   ├──grad_descent_constrained.pdf  2.99M
|   ├──grad_descent_constrained01.MP4  210.04M
|   ├──grad_descent_constrained02.MP4  246.69M
|   └──grad_descent_constrained03.MP4  140.84M
├──[09]subgradient_methods  
|   ├──subgradient_methods-note.pdf  14.87M
|   ├──subgradient_methods.pdf  3.00M
|   ├──subgradient_methods01.MP4  280.69M
|   ├──subgradient_methods02.MP4  303.34M
|   └──subgradient_methods03.MP4  181.10M
├──[10]mirror_descent  
|   ├──mirror_descent-note.pdf  223.55M
|   ├──mirror_descent.pdf  9.88M
|   ├──mirror_descent01.MP4  493.71M
|   └──mirror_descent02.MP4  300.62M
├──[11]proximal_gradient  
|   ├──proximal_gradient-note.pdf  33.35M
|   ├──proximal_gradient.pdf  32.35M
|   ├──proximal_gradient01.MP4  409.32M
|   └──proximal_gradient02.MP4  217.20M
├──[12]accelerated_gradient  
|   ├──accelerated_gradient-note.pdf  15.45M
|   ├──accelerated_gradient.pdf  4.00M
|   ├──accelerated_gradient01.MP4  353.48M
|   └──accelerated_gradient02.MP4  284.79M
├──[13]smoothing  
|   ├──smoothing-note.pdf  5.47M
|   ├──smoothing.MP4  396.42M
|   └──smoothing.pdf  1.50M
├──[14]dual_method  
|   ├──dual_method-note.pdf  3.86M
|   ├──dual_method.pdf  1.73M
|   ├──dual_method01.MP4  264.94M
|   └──dual_method02.MP4  365.17M
├──[15]ADMM  
|   ├──ADMM-note.pdf  2.40M
|   ├──ADMM.pdf  743.23kb
|   ├──ADMM01.MP4  99.62M
|   └──ADMM02.MP4  438.89M
├──[16]stochastic_gradient  
|   ├──stochastic_gradient-note.pdf  5.27M
|   ├──stochastic_gradient.pdf  2.19M
|   ├──stochastic_gradient01.MP4  170.83M
|   └──stochastic_gradient02.MP4  227.16M
├──[17]quasi_Newton  
|   ├──quasi_Newton-note.pdf  10.48M
|   ├──quasi_Newton.pdf  3.92M
|   ├──quasi_Newton01.MP4  134.53M
|   └──quasi_Newton02.MP4  177.18M
├──[18]Applications  
|   ├──[1]wireless_networks_I.pdf  3.58M
|   ├──[1]wireless_networks_II.pdf  2.77M
|   ├──[2]edgeAI.pdf  9.25M
|   └──[3]RIS_Yuanming.pdf  2.83M
├──Syllabus.pdf  75.84kb
└──凸优化2020_学习指南.pdf  71.46kb

游客，如果您要查看本帖隐藏内容请回复