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
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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