Optimizing Value-at-Risk and Conditional Value-at-Risk of Black Box Functions with Lacing Values (LV)

Last update: Nov 11, 2021

Related tags

Deep Learning BayesOpt-LV

Overview

BayesOpt-LV

Optimizing Value-at-Risk and Conditional Value-at-Risk of Black Box Functions with Lacing Values (LV)

About

This repository contains the source code for

ICML'21 paper: Value-at-Risk Optimization with Gaussian Processes
NeurIPS'21 paper: Optimizing Conditional Value-At-Risk of Black-Box Functions

Requirements

numpy
scipy
tensorflow 1.14.0
tensorflow-probability 0.7.0
gpflow 1.5.1

Instructions

The examples of running scripts are in running_scripts folder. The optimization results are stored in a folder named with the objective function in running_scripts. Objective functions are found in functions.py.

Owner

GitHub Repository

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