ECLARE: Extreme Classification with Label Graph Correlations

Overview

ECLARE

ECLARE: Extreme Classification with Label Graph Correlations

@InProceedings{Mittal21b,
	author       = "Mittal, A. and Sachdeva, N. and Agrawal, S. and Agarwal, S. and Kar, P. and Varma, M.",
	title        = "ECLARE: Extreme classification with label graph correlations",
	booktitle    = "Proceedings of The ACM International World Wide Web Conference",
	month = "April",
	year = "2021",
	}

SETUP WORKSPACE

mkdir -p ${HOME}/scratch/XC/data 
mkdir -p ${HOME}/scratch/XC/programs

SETUP ECLARE

cd ${HOME}/scratch/XC/programs
git clone https://github.com/Extreme-classification/ECLARE.git
conda create -f ECLARE/eclare_env.yml
conda activate eclare
git clone https://github.com/kunaldahiya/pyxclib.git
cd pyxclib
python setup.py install
cd ../ECLARE

DOWNLOAD DATASET

cd ${HOME}/scratch/XC/data
gdown --id <dataset id>
unzip *.zip
dataset dataset id
LF-AmazonTitles-131K 1VlfcdJKJA99223fLEawRmrXhXpwjwJKn
LF-WikiSeeAlsoTitles-131K 1edWtizAFBbUzxo9Z2wipGSEA9bfy5mdX
LF-AmazonTitles-1.3M 1Davc6BIfoTIAS3mP1mUY5EGcGr2zN2pO

RUNNING ECLARE

cd ${HOME}/scratch/XC/programs/ECLARE
chmod +x run_ECLARE.sh
./run_ECLARE.sh <gpu_id> <ECLARE TYPE> <dataset> <folder name>
e.g.
./run_ECLARE.sh 0 ECLARE LF-AmazonTitles-131K ECLARE_RUN

YOU MAY ALSO LIKE

Owner
Extreme Classification
Extreme Classification
USAD - UnSupervised Anomaly Detection on multivariate time series

USAD - UnSupervised Anomaly Detection on multivariate time series Scripts and utility programs for implementing the USAD architecture. Implementation

116 Jan 04, 2023
Processed, version controlled history of Minecraft's generated data and assets

mcmeta Processed, version controlled history of Minecraft's generated data and assets Repository structure Each of the following branches has a commit

Misode 75 Dec 28, 2022
Pseudo-mask Matters in Weakly-supervised Semantic Segmentation

Pseudo-mask Matters in Weakly-supervised Semantic Segmentation By Yi Li, Zhanghui Kuang, Liyang Liu, Yimin Chen, Wayne Zhang SenseTime, Tsinghua Unive

33 Oct 14, 2022
The world's largest toxicity dataset.

The Toxicity Dataset by Surge AI Saving the internet is fun. Combing through thousands of online comments to build a toxicity dataset isn't. That's wh

Surge AI 134 Dec 19, 2022
🌈 PyTorch Implementation for EMNLP'21 Findings "Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer"

SGLKT-VisDial Pytorch Implementation for the paper: Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer Gi-Cheon Kang, Junseok P

Gi-Cheon Kang 9 Jul 05, 2022
Full Stack Deep Learning Labs

Full Stack Deep Learning Labs Welcome! Project developed during lab sessions of the Full Stack Deep Learning Bootcamp. We will build a handwriting rec

Full Stack Deep Learning 1.2k Dec 31, 2022
Discord bot-CTFD-Thread-Parser - Discord bot CTFD-Thread-Parser

Discord bot CTFD-Thread-Parser Description: This tools is used to create automat

15 Mar 22, 2022
Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks

LMMNN Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks This is the working dire

Giora Simchoni 10 Nov 02, 2022
An off-line judger supporting distributed problem repositories

Thaw δΈ­ζ–‡ | English Thaw is an off-line judger supporting distributed problem repositories. Everyone can use Thaw release problems with license on GitHu

countercurrent_time 2 Jan 09, 2022
A minimal implementation of Gaussian process regression in PyTorch

pytorch-minimal-gaussian-process In search of truth, simplicity is needed. There exist heavy-weighted libraries, but as you know, we need to go bare b

Sangwoong Yoon 38 Nov 25, 2022
The official PyTorch code for NeurIPS 2021 ML4AD Paper, "Does Thermal data make the detection systems more reliable?"

MultiModal-Collaborative (MMC) Learning Framework for integrating RGB and Thermal spectral modalities This is the official code for NeurIPS 2021 Machi

NeurAI 12 Nov 02, 2022
An example project demonstrating how the Autonomous Learning Library can be used to build new reinforcement learning agents.

About This repository shows how Autonomous Learning Library can be used to build new reinforcement learning agents. In particular, it contains a model

Chris Nota 5 Aug 30, 2022
offical implement of our Lifelong Person Re-Identification via Adaptive Knowledge Accumulation in CVPR2021

LifelongReID Offical implementation of our Lifelong Person Re-Identification via Adaptive Knowledge Accumulation in CVPR2021 by Nan Pu, Wei Chen, Yu L

PeterPu 76 Dec 08, 2022
EGNN - Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

EGNN - Pytorch Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch. May be eventually used for Alphafold2 replication. This

Phil Wang 259 Jan 04, 2023
A collection of resources and papers on Diffusion Models, a darkhorse in the field of Generative Models

This repository contains a collection of resources and papers on Diffusion Models and Score-based Models. If there are any missing valuable resources

5.1k Jan 08, 2023
Harmonious Textual Layout Generation over Natural Images via Deep Aesthetics Learning

Harmonious Textual Layout Generation over Natural Images via Deep Aesthetics Learning Code for the paper Harmonious Textual Layout Generation over Nat

7 Aug 09, 2022
Github Traffic Insights as Prometheus metrics.

github-traffic Github Traffic collects your repository's traffic data and exposes it as Prometheus metrics. Grafana dashboard that displays the metric

Grafana Labs 34 Oct 27, 2022
AlgoVision - A Framework for Differentiable Algorithms and Algorithmic Supervision

NeurIPS 2021 Paper "Learning with Algorithmic Supervision via Continuous Relaxations"

Felix Petersen 76 Jan 01, 2023
Efficient electromagnetic solver based on rigorous coupled-wave analysis for 3D and 2D multi-layered structures with in-plane periodicity

Efficient electromagnetic solver based on rigorous coupled-wave analysis for 3D and 2D multi-layered structures with in-plane periodicity, such as gratings, photonic-crystal slabs, metasurfaces, surf

Alex Song 17 Dec 19, 2022
Out-of-Distribution Generalization of Chest X-ray Using Risk Extrapolation

OoD_Gen-Chest_Xray Out-of-Distribution Generalization of Chest X-ray Using Risk Extrapolation Requirements (Installations) Install the following libra

Enoch Tetteh 2 Oct 01, 2022