This is the code repository for the paper "Identification of the Generalized Condorcet Winner in Multi-dueling Bandits" (NeurIPS 2021).

Overview

Code Repository for the Paper

"Identification of the Generalized Condorcet Winner in Multi-dueling Bandits"

   (To appear in: Proceedings of NeurIPS2021)

The code is written in Python 3.7.

You can cite our paper as follows:

@inproceedings{Haddenhorst2021,
  title={Identification of the Generalized Condorcet Winner in Multi-dueling Bandits},
  author={Haddenhorst, Bj{\"o}rn and Bengs, Viktor and H{\"u}llermeier, Eyke},
  booktitle = {Proceedings of Advances in Neural Information Processing Systems 34 (NeurIPS 2021)},
  year={2021},
}

Requirements

To install requirements:

pip install -r requirements.txt

Evaluation

  • (A) To obtain the evaluation results of the algorithms, uncomment the corresponding code in "Neurips2021_experiments.py" and execute it.
  • (B) To repeat the empirical comparison of the two lower bounds (Prop. 4.1 and Thm 5.2) for the single bandit case (m=k), simply execute "NeurIPS_LB_comparison.py".

Results

  • After repeating all experiments in (A), the results shown in the tables are written saved the following files
TABLE(S) FILE
2 Experiment_PW_m5.txt
3,6,7 Experiment1_m5_gamma_005.txt
3,6,7 Experiment1_m10_gamma_005.txt
4 Experiment_PW_m10.txt
5 Experiment_PW_PWData.txt
6,7 Experiment1_m15_gamma_005.txt
6,7 Experiment1_m20_gamma_005.txt
8 Experiment_DKWT_vs_algo5_v1.txt
9 Experiment_DKWT_vs_algo5_v2.txt
  • The results for (B) are only shown in the terminal and not saved to any file.

In case of any questions, please contact Björn Haddenhorst ([email protected]).

Owner
Since 2019: PhD student of Prof. Eyke Hüllermeier at Paderborn University
An LSTM for time-series classification

Update 10-April-2017 And now it works with Python3 and Tensorflow 1.1.0 Update 02-Jan-2017 I updated this repo. Now it works with Tensorflow 0.12. In

Rob Romijnders 391 Dec 27, 2022
:fire: 2D and 3D Face alignment library build using pytorch

Face Recognition Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D an

Adrian Bulat 6k Dec 31, 2022
Some methods for comparing network representations in deep learning and neuroscience.

Generalized Shape Metrics on Neural Representations In neuroscience and in deep learning, quantifying the (dis)similarity of neural representations ac

Alex Williams 45 Dec 27, 2022
Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)

NDQ: Learning Nearly Decomposable Value Functions with Communication Minimization Note This codebase accompanies paper Learning Nearly Decomposable Va

Tonghan Wang 69 Nov 26, 2022
Learning from Synthetic Humans, CVPR 2017

Learning from Synthetic Humans (SURREAL) Gül Varol, Javier Romero, Xavier Martin, Naureen Mahmood, Michael J. Black, Ivan Laptev and Cordelia Schmid,

Gul Varol 538 Dec 18, 2022
OpenCV, MediaPipe Pose Estimation, Affine Transform for Icon Overlay

Yoga Pose Identification and Icon Matching Project Goal Detect yoga poses performed by a user and overlay a corresponding icon image. Running the main

Anna Garverick 1 Dec 03, 2021
Points2Surf: Learning Implicit Surfaces from Point Clouds (ECCV 2020 Spotlight)

Points2Surf: Learning Implicit Surfaces from Point Clouds (ECCV 2020 Spotlight)

Philipp Erler 329 Jan 06, 2023
The repository offers the official implementation of our BMVC 2021 paper in PyTorch.

CrossMLP Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation Bin Ren1, Hao Tang2, Nicu Sebe1. 1University of Trento, Italy, 2ETH, Switzerla

Bingoren 16 Jul 27, 2022
Code for the paper "Reinforcement Learning as One Big Sequence Modeling Problem"

Trajectory Transformer Code release for Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are in envir

Michael Janner 269 Jan 05, 2023
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.

Experiments How to reproduce experimental results of Stochastic bandits with groups of similar arms submitted paper ? Section 5 of the paper To reprod

Fabien 0 Oct 25, 2021
Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight)

[NeurIPS 2021 Spotlight] HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning [Paper] This is Official PyTorch implementatio

42 Nov 01, 2022
A static analysis library for computing graph representations of Python programs suitable for use with graph neural networks.

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

Google Research 258 Dec 29, 2022
Incremental Cross-Domain Adaptation for Robust Retinopathy Screening via Bayesian Deep Learning

Incremental Cross-Domain Adaptation for Robust Retinopathy Screening via Bayesian Deep Learning Update (September 18th, 2021) A supporting document de

Taimur Hassan 1 Mar 16, 2022
Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR

Codebase for "INVASE: Instance-wise Variable Selection" Authors: Jinsung Yoon, James Jordon, Mihaela van der Schaar Paper: Jinsung Yoon, James Jordon,

Jinsung Yoon 50 Nov 11, 2022
The implementation of the algorithm in the paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.

DS3L This is the code for paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020. Setups The code is implem

Guolz 36 Oct 19, 2022
《Truly shift-invariant convolutional neural networks》(2021)

Truly shift-invariant convolutional neural networks [Paper] Authors: Anadi Chaman and Ivan Dokmanić Convolutional neural networks were always assumed

Anadi Chaman 46 Dec 19, 2022
An abstraction layer for mathematical optimization solvers.

MathOptInterface Documentation Build Status Social An abstraction layer for mathematical optimization solvers. Replaces MathProgBase. Citing MathOptIn

JuMP-dev 284 Jan 04, 2023
Official Repository for the ICCV 2021 paper "PixelSynth: Generating a 3D-Consistent Experience from a Single Image"

PixelSynth: Generating a 3D-Consistent Experience from a Single Image (ICCV 2021) Chris Rockwell, David F. Fouhey, and Justin Johnson [Project Website

Chris Rockwell 95 Nov 22, 2022
Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)

Diffusion Probabilistic Models for 3D Point Cloud Generation [Paper] [Code] The official code repository for our CVPR 2021 paper "Diffusion Probabilis

Shitong Luo 323 Jan 05, 2023
Dados coletados e programas desenvolvidos no processo de iniciação científica

Iniciacao_cientifica_FAPESP_2020-14845-6 Dados coletados e programas desenvolvidos no processo de iniciação científica Os arquivos .py são os programa

1 Jan 10, 2022