This is the official repository of the paper Stocastic bandits with groups of similar arms (NeurIPS 2021). It contains the code that was used to compute the figures and experiments of the paper.

Overview

Experiments

How to reproduce experimental results of Stochastic bandits with groups of similar arms submitted paper ?

Section 5 of the paper

To reproduce all of the empirical results (and more) of the section 5 (Experiments) of the submitted paper, it is enough to run the regret_experiment.ipynb notebook.

Appendix D of the paper

To reproduce all of the empirical results (and more) of the appendix D (Experiments) of the submitted paper, you may run the regret_experiment.ipynb notebook as well as the dispatching_experiment.ipynb notebook.

How to?

To run the jupyter notebooks, you may use the jupyter software (https://jupyter.org/) or use an online plateform such as google Colab (https://colab.research.google.com/)

Which versions

The code has run on google Colab on Friday 4th, June without problem. The stability of the package that were used (numpy, matplotlib, itertools (built-in), datetime (built-in)) makes it very likely to run correctly before the next major updates of one of those packages.

Otherwise, the code has been tested locally on a machine with the following versions : python 3.9.5 numpy 1.20.3 matplotlib 3.4.1

Where to look at?

The algorithms.py file contains all the algorithms that were used in the experiments of this paper. All the sequential algorithms depends on SequentiAlg, a class that is defined in the Forban module.

In the Forban module, a class for Bandit configurations is also defined.

Owner
Fabien
PhD student in Reinforcement Learning.
Fabien
Self Governing Neural Networks (SGNN): the Projection Layer

Self Governing Neural Networks (SGNN): the Projection Layer A SGNN's word projections preprocessing pipeline in scikit-learn In this notebook, we'll u

Guillaume Chevalier 22 Nov 06, 2022
An end-to-end library for editing and rendering motion of 3D characters with deep learning [SIGGRAPH 2020]

Deep-motion-editing This library provides fundamental and advanced functions to work with 3D character animation in deep learning with Pytorch. The co

1.2k Dec 29, 2022
tinykernel - A minimal Python kernel so you can run Python in your Python

tinykernel - A minimal Python kernel so you can run Python in your Python

fast.ai 37 Dec 02, 2022
Code for "Reconstructing 3D Human Pose by Watching Humans in the Mirror", CVPR 2021 oral

Reconstructing 3D Human Pose by Watching Humans in the Mirror Qi Fang*, Qing Shuai*, Junting Dong, Hujun Bao, Xiaowei Zhou CVPR 2021 Oral The videos a

ZJU3DV 178 Dec 13, 2022
On Generating Extended Summaries of Long Documents

ExtendedSumm This repository contains the implementation details and datasets used in On Generating Extended Summaries of Long Documents paper at the

Georgetown Information Retrieval Lab 76 Sep 05, 2022
Extract MNIST handwritten digits dataset binary file into bmp images

MNIST-dataset-extractor Extract MNIST handwritten digits dataset binary file into bmp images More info at http://yann.lecun.com/exdb/mnist/ Dependenci

Omar Mostafa 6 May 24, 2021
Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.

Conformal time-series forecasting Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021. If you use our code in yo

Kamilė Stankevičiūtė 36 Nov 21, 2022
This repo is the official implementation of "L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization".

L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated p

Jiaqi Gu 9 Jul 14, 2022
Official repo for AutoInt: Automatic Integration for Fast Neural Volume Rendering in CVPR 2021

AutoInt: Automatic Integration for Fast Neural Volume Rendering CVPR 2021 Project Page | Video | Paper PyTorch implementation of automatic integration

Stanford Computational Imaging Lab 149 Dec 22, 2022
Code for ECIR'20 paper Diagnosing BERT with Retrieval Heuristics

Bert Axioms This is the repository with the code for the Paper Diagnosing BERT with Retrieval Heuristics Required Data In order to run this code, you

Arthur Câmara 5 Jan 21, 2022
Super Resolution for images using deep learning.

Neural Enhance Example #1 — Old Station: view comparison in 24-bit HD, original photo CC-BY-SA @siv-athens. As seen on TV! What if you could increase

Alex J. Champandard 11.7k Dec 29, 2022
《Deep Single Portrait Image Relighting》(ICCV 2019)

Ratio Image Based Rendering for Deep Single-Image Portrait Relighting [Project Page] This is part of the Deep Portrait Relighting project. If you find

62 Dec 21, 2022
https://sites.google.com/cornell.edu/recsys2021tutorial

Counterfactual Learning and Evaluation for Recommender Systems (RecSys'21 Tutorial) Materials for "Counterfactual Learning and Evaluation for Recommen

yuta-saito 45 Nov 10, 2022
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"

Scripts for "Current best-practices in single-cell RNA-seq: a tutorial" This repository is complementary to the publication: M.D. Luecken, F.J. Theis,

Theis Lab 968 Dec 28, 2022
The goal of the exercises below is to evaluate the candidate knowledge and problem solving expertise regarding the main development focuses for the iFood ML Platform team: MLOps and Feature Store development.

The goal of the exercises below is to evaluate the candidate knowledge and problem solving expertise regarding the main development focuses for the iFood ML Platform team: MLOps and Feature Store dev

George Rocha 0 Feb 03, 2022
PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices.

PyTorch-LIT PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices. With

Amin Rezaei 157 Dec 11, 2022
Code for a seq2seq architecture with Bahdanau attention designed to map stereotactic EEG data from human brains to spectrograms, using the PyTorch Lightning.

stereoEEG2speech We provide code for a seq2seq architecture with Bahdanau attention designed to map stereotactic EEG data from human brains to spectro

15 Nov 11, 2022
[ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization

F8Net Fixed-Point 8-bit Only Multiplication for Network Quantization (ICLR 2022 Oral) OpenReview | arXiv | PDF | Model Zoo | BibTex PyTorch implementa

Snap Research 76 Dec 13, 2022
The offcial repository for 'CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos', SIGIR2022

CharacterBERT-DR The offcial repository for CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos, Sh

ielab 11 Nov 15, 2022
Optimizes image files by converting them to webp while also updating all references.

About Optimizes images by (re-)saving them as webp. For every file it replaced it automatically updates all references. Works on single files as well

Watermelon Wolverine 18 Dec 23, 2022