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]).

You might also like...
PyTorch implementation for our NeurIPS 2021 Spotlight paper
PyTorch implementation for our NeurIPS 2021 Spotlight paper "Long Short-Term Transformer for Online Action Detection".

Long Short-Term Transformer for Online Action Detection Introduction This is a PyTorch implementation for our NeurIPS 2021 Spotlight paper "Long Short

Official implementation of NeurIPS'2021 paper TransformerFusion
Official implementation of NeurIPS'2021 paper TransformerFusion

TransformerFusion: Monocular RGB Scene Reconstruction using Transformers Project Page | Paper | Video TransformerFusion: Monocular RGB Scene Reconstru

This repo includes our code for evaluating and improving transferability in domain generalization (NeurIPS 2021)

Transferability for domain generalization This repo is for evaluating and improving transferability in domain generalization (NeurIPS 2021), based on

Code for MarioNette: Self-Supervised Sprite Learning, in NeurIPS 2021
Code for MarioNette: Self-Supervised Sprite Learning, in NeurIPS 2021

MarioNette | Webpage | Paper | Video MarioNette: Self-Supervised Sprite Learning Dmitriy Smirnov, Michaël Gharbi, Matthew Fisher, Vitor Guizilini, Ale

Code for Parameter Prediction for Unseen Deep Architectures (NeurIPS 2021)
Code for Parameter Prediction for Unseen Deep Architectures (NeurIPS 2021)

Parameter Prediction for Unseen Deep Architectures (NeurIPS 2021) authors: Boris Knyazev, Michal Drozdzal, Graham Taylor, Adriana Romero-Soriano Overv

Official code for On Path Integration of Grid Cells: Group Representation and Isotropic Scaling (NeurIPS 2021)
Official code for On Path Integration of Grid Cells: Group Representation and Isotropic Scaling (NeurIPS 2021)

On Path Integration of Grid Cells: Group Representation and Isotropic Scaling This repo contains the official implementation for the paper On Path Int

Code for
Code for "Adversarial Attack Generation Empowered by Min-Max Optimization", NeurIPS 2021

Min-Max Adversarial Attacks [Paper] [arXiv] [Video] [Slide] Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang, Tianyun Zha

[NeurIPS 2021] Code for Unsupervised Learning of Compositional Energy Concepts

Unsupervised Learning of Compositional Energy Concepts This is the pytorch code for the paper Unsupervised Learning of Compositional Energy Concepts.

Code repo for
Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).

RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc

Owner
Since 2019: PhD student of Prof. Eyke Hüllermeier at Paderborn University
null
Code to reproduce the experiments from our NeurIPS 2021 paper " The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective"

Code To run: python runner.py new --save <SAVE_NAME> --data <PATH_TO_DATA_DIR> --dataset <DATASET> --model <model_name> [options] --n 1000 - train - t

Geoff Pleiss 5 Dec 12, 2022
Companion code for the paper "An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence" (NeurIPS 2021)

ReLU-GP Residual (RGPR) This repository contains code for reproducing the following NeurIPS 2021 paper: @inproceedings{kristiadi2021infinite, title=

Agustinus Kristiadi 4 Dec 26, 2021
Code for our NeurIPS 2021 paper 'Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation'

Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation (NeurIPS 2021) Code for our NeurIPS 2021 paper 'Exploiting the Intri

Shiqi Yang 53 Dec 25, 2022
Source code of NeurIPS 2021 Paper ''Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration''

CaGCN This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration". Paper L

null 6 Dec 19, 2022
Code for NeurIPS 2021 paper: Invariant Causal Imitation Learning for Generalizable Policies

Invariant Causal Imitation Learning for Generalizable Policies Ioana Bica, Daniel Jarrett, Mihaela van der Schaar Neural Information Processing System

Ioana Bica 17 Dec 1, 2022
This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels].

CGPN This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels]. Req

null 10 Sep 12, 2022
Official implementation of NeurIPS 2021 paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"

Official implementation of NeurIPS 2021 paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"

Ng Kam Woh 71 Dec 22, 2022
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"

CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We

Hui Wu 19 Oct 21, 2022
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

null 76 Jan 3, 2023
The official implementation of NeurIPS 2021 paper: Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks

The official implementation of NeurIPS 2021 paper: Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks

machen 11 Nov 27, 2022