Scheduling BilinearRewards

Overview

Scheduling_BilinearRewards

Requirement

Python 3 >=3.5

Structure

  • main.py
    This file includes the main function.

    • For getting the results in Figure 1, please set variables for synthetic data in the main function as follows:
      I=10, J=2, T=700, d=2, mu_inv=1, rho_tot=1, n_tot=8, gamma=1.2, repeat=10, util_arriv=False, load=False, com=True, fix=False.
    • For getting the results in Figure 7, please set variables for real data in the main function as follows:
      I=5, J=12, d=4, T=1100, gamma=1.2, repeat=10, ext=False, prep=False, load=False, com=True.
  • Preprocess.py
    This file includes the code for extracting and preprocessing real data. It is required to put your own google cloud key in this file to extract the public dataset described in https://github.com/google/cluster-data. Otherwise, you can use the dataset in the 'data' file extracted from the public dataset by deactivating extraction in main.py (i.e. ext=False).

  • Environment.py
    This file includes the code for generating an environment (synthetic world or real world) of a queueing system with the bilinear reward structure.

  • Algorithm.py
    This file includes the code for scheduling algorithms.

  • Oracle.py
    This file includes the code for running the oracle policy.

How to run this code

Please run this command:

  • For synthetic data:
    python3 main.py syn

  • For real data:
    python3 main.py real

Owner
junghun.kim
junghun.kim
Repository for RNNs using TensorFlow and Keras - LSTM and GRU Implementation from Scratch - Simple Classification and Regression Problem using RNNs

RNN 01- RNN_Classification Simple RNN training for classification task of 3 signal: Sine, Square, Triangle. 02- RNN_Regression Simple RNN training for

Nahid Ebrahimian 13 Dec 13, 2022
NeuralForecast is a Python library for time series forecasting with deep learning models

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate m

Nixtla 1.1k Jan 03, 2023
Style transfer between images was performed using the VGG19 model

Style transfer between images was performed using the VGG19 model. The necessary codes, libraries and all other information of this project are available below

Onur yılmaz 2 May 09, 2022
A New Open-Source Off-road Environment for Benchmark Generalization of Autonomous Driving

A New Open-Source Off-road Environment for Benchmark Generalization of Autonomous Driving Isaac Han, Dong-Hyeok Park, and Kyung-Joong Kim IEEE Access

13 Dec 27, 2022
HINet: Half Instance Normalization Network for Image Restoration

HINet: Half Instance Normalization Network for Image Restoration Liangyu Chen, Xin Lu, Jie Zhang, Xiaojie Chu, Chengpeng Chen Paper: https://arxiv.org

303 Dec 31, 2022
Speed-Test - You can check your intenet speed using this tool

Speed-Test Tool By Hez_X AVAILABLE ON : Termux & Kali linux & Ubuntu (Linux E

Hez-X 3 Feb 17, 2022
YOLOX_AUDIO is an audio event detection model based on YOLOX

YOLOX_AUDIO is an audio event detection model based on YOLOX, an anchor-free version of YOLO. This repo is an implementated by PyTorch. Main goal of YOLOX_AUDIO is to detect and classify pre-defined

intflow Inc. 77 Dec 19, 2022
Conditional Generative Adversarial Networks (CGAN) for Mobility Data Fusion

This code implements the paper, Kim et al. (2021). Imputing Qualitative Attributes for Trip Chains Extracted from Smart Card Data Using a Conditional Generative Adversarial Network. Transportation Re

Eui-Jin Kim 2 Feb 03, 2022
PPO Lagrangian in JAX

PPO Lagrangian in JAX This repository implements PPO in JAX. Implementation is tested on the safety-gym benchmark. Usage Install dependencies using th

Karush Suri 2 Sep 14, 2022
Deep Learning for Morphological Profiling

Deep Learning for Morphological Profiling An end-to-end implementation of a ML System for morphological profiling using self-supervised learning to di

Danielh Carranza 0 Jan 20, 2022
PyTorch implementations of neural network models for keyword spotting

Honk: CNNs for Keyword Spotting Honk is a PyTorch reimplementation of Google's TensorFlow convolutional neural networks for keyword spotting, which ac

Castorini 475 Dec 15, 2022
PyTorch implementation of HDN(Homography Decomposition Networks) for planar object tracking

Homography Decomposition Networks for Planar Object Tracking This project is the offical PyTorch implementation of HDN(Homography Decomposition Networ

CaptainHook 48 Dec 15, 2022
A PyTorch implementation of Sharpness-Aware Minimization for Efficiently Improving Generalization

sam.pytorch A PyTorch implementation of Sharpness-Aware Minimization for Efficiently Improving Generalization ( Foret+2020) Paper, Official implementa

Ryuichiro Hataya 102 Dec 28, 2022
Session-aware Item-combination Recommendation with Transformer Network

Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA

Tzu-Heng Lin 6 Mar 10, 2022
CS506-Spring2022 - Code and Slides for Boston University CS 506

CS 506 - Computational Tools for Data Science Code, slides, and notes for Boston

Lance Galletti 17 May 06, 2022
Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation

Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision Training Efficiency We show the training efficiency of our DSLP model b

Chenyang Huang 36 Oct 31, 2022
Official implementation of the paper DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows

DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows Official implementation of the paper DeFlow: Learning Complex Im

Valentin Wolf 86 Nov 16, 2022
Camera ready code repo for the NeuRIPS 2021 paper: "Impression learning: Online representation learning with synaptic plasticity".

Impression-Learning-Camera-Ready Camera ready code repo for the NeuRIPS 2021 paper: "Impression learning: Online representation learning with synaptic

2 Feb 09, 2022
Attentive Implicit Representation Networks (AIR-Nets)

Attentive Implicit Representation Networks (AIR-Nets) Preprint | Supplementary | Accepted at the International Conference on 3D Vision (3DV) teaser.mo

29 Dec 07, 2022