PyTorch-based End-to-End Predict-then-Optimize Tool

Contents:

  • Introduction
  • Installation
  • Tutorial
  • Module
    • pyepo.data
    • pyepo.model
    • pyepo.twostage
    • pyepo.func
    • pyepo.metric
  • Reference
  • API Reference
PyTorch-based End-to-End Predict-then-Optimize Tool
  • Module
  • View page source

Module

  • pyepo.data
  • pyepo.model
  • pyepo.twostage
  • pyepo.func
    • Surrogate Loss
      • Smart Predict-then-Optimize Loss+ (SPO+)
      • Perturbation Gradient Loss (PG)
    • Black-box Methods
      • Differentiable Black-box Optimizer (DBB)
      • Negative Identity Backpropagation (NID)
    • Perturbed Methods
      • Differentiable Perturbed Optimizer (DPO)
      • Perturbed Fenchel-Young Loss (PYFL)
      • Implicit Maximum Likelihood Estimator (I-MLE)
      • Adaptive Implicit Maximum Likelihood Estimator (AI-MLE)
    • Contrastive Methods
      • Noise Contrastive Estimation (NCE)
      • Contrastive Maximum A Posterior Estimation (CMAP)
    • Learning-to-Rank Methods
      • Pointwise Learning-to-Rank (LTR)
      • Pairwise Learning-to-Rank (LTR)
      • Listwise Learning-to-Rank (LTR)
  • pyepo.metric
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© Copyright 2021, Bo Tang.

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