Code to train RL agents along with Adversarial distrubance agents
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Updated
Mar 21, 2017 - Python
Code to train RL agents along with Adversarial distrubance agents
Оптимизация долгосрочного портфеля акций
Deep Neural Network architecture as a predictive optimal controller for {HVAC+Solar cell + battery} disturbance afflicted system vs classic Model Predictive Control
Experiments with distributionally robust optimization (DRO) for deep neural networks
Robust optimization for power markets
Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms [NeurIPS 2020]
robust optimization
Hyperparameter tuning using a robust simulation optimization framework
Official implementation for the NeurIPS 2020 paper Neural Non-Rigid Tracking.
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper
Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
Art of finding minimum. Python implementations from scratch.
This project implements methods for solving Uncapcaitated Facility Location(UFLP) nominally and under spatial demand uncertainty.
One-week side project to play around stochastic optimization (how to take *good* decisions under uncertainty)
Geometric median (GM) is a classical method in statistics for achieving a robust estimation of the uncorrupted data; under gross corruption, it achieves the optimal breakdown point of 0.5. However, its computational complexity makes it infeasible for robustifying stochastic gradient descent (SGD) for high-dimensional optimization problems. In th…
Modeling robust optimization problems in Pyomo
Coping with Label Shift via Distributionally Robust Optimisation
This repo contains code and visualisation for "Robust moving target defence against false data injection attacks in power grids"
Python Library for Robustness Monitoring and Adversarial Debugging of NLP models
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