Alternatives and similar repositories for Big-Data-Optimization-Course:

Users that are interested in Big-Data-Optimization-Course are comparing it to the libraries listed below

• niaohe / Convex-Optimization-Course
  Repository for my convex optimization course.
  ☆53Updated 4 years ago
• mstaib / mmd-dro-code
  Accompanying code for our NeurIPS 2019 paper
  ☆12Updated 5 years ago
• cshjin / awesome-nonconvex-optimization
  A collection of papers and readings for non-convex optimization
  ☆31Updated 6 years ago
• djrusso / Dynamic-Optimization-Course
  Website for a doctoral course on Dynamic Optimization
  ☆19Updated last year
• daniellevy / fast-dro
  PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets
  ☆59Updated 2 years ago
• jj-zhu / kdro
  Code for the paper: Kernel Distributionally Robust Optimization
  ☆13Updated 4 years ago
• udellgroup / orie7191
  Materials for ORIE 7191: Topics in Optimization for Machine Learning
  ☆44Updated 5 years ago
• martius-lab / CombOptNet
  Source code for the Paper: CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints}
  ☆72Updated 2 years ago
• bwilder0 / aaai_melding_code
  Code the AAAI 2019 paper "Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization"
  ☆31Updated 4 years ago
• gerrili1996 / DRLR_NIPS2019_exp
  The MATLAB source code
  ☆15Updated 5 years ago
• wotaoyin / LargeScaleBookSlides
  ☆24Updated 2 years ago
• facebookresearch / amortized-optimization-tutorial
  Tutorial on amortized optimization for learning to optimize over continuous domains
  ☆240Updated last month
• fbach2000 / Learning_Theory_from_First_Principles
  Python & Matlab code for the figures from the book "Learning Theory from First Principles" by Francis Bach
  ☆101Updated last year
• benchopt / benchmark_bilevel
  Benchmark for bi-level optimization solvers
  ☆44Updated 4 months ago
• kanguyn / Machine-Learning-Under-Optimization-Lens-Fall2018
  Work from class 15.095 Machine Learning Under a Modern Optimization Lens at MIT taught by Dimitris Bertsimas and Martin Copenhaver
  ☆40Updated 6 years ago
• tengyuma / cs229m_notes
  ☆222Updated 2 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆43Updated last year
• ntienvu / KnownOptimum_BO
  Release code for ICML2020 Knowing The What But Not The Where in Bayesian Optimization
  ☆15Updated 2 years ago
• daizhongxiang / Bayesian-Optimization-Meets-Bayesian-Optimal-Stopping
  Bayesian Optimization Meets Bayesian Optimal Stopping
  ☆31Updated 4 years ago
• ymalitsky / adaptive_GD
  Adaptive gradient descent without descent
  ☆47Updated 3 years ago
• sail-sg / optim4rl
  Optim4RL is a Jax framework of learning to optimize for reinforcement learning.
  ☆25Updated 4 months ago
• facebookresearch / LANCER
  Repo for the paper "Landscape Surrogate Learning Decision Losses for Mathematical Optimization Under Partial Information"
  ☆36Updated last year
• pmichel31415 / P-DRO
  Code for the papers "Modeling the Second Player in Distributionally Robust Optimization" and "Distributionally Robust Models with Paramet…
  ☆27Updated 3 years ago
• OptMLGroup / SQN
  Sampled Quasi-Newton Methods for Deep Learning
  ☆21Updated 4 years ago
• martinResearch / PySparseLP
  python algorithms to solve sparse linear programming problems
  ☆28Updated last year
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆31Updated 3 years ago
• grasool / Gaussian-Processes
  Introduction to Gaussian Processes
  ☆29Updated 6 years ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆52Updated 4 years ago
• LongPham7 / Distributionally-Robust-Optimization
  Experiments with distributionally robust optimization (DRO) for deep neural networks
  ☆37Updated 5 years ago
• akuhren / selective_gp
  Code accompanying the paper "Probabilistic Selection of Inducing Points in Sparse Gaussian Processes".
  ☆24Updated 2 years ago