Paper Code：A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection

wangxb

Last update: Dec 8, 2022

Related tags

Deep Learning SaWDE

Overview

1. SaWDE.m is the main function

2. DataPartition.m is used to randomly partition the original data into training sets and test sets with a ratio of 7 : 3.

3. CSGSTest.m is used to test the performance of each strategy.

Code for the paper One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation, CVPR 2021.

One Thing One Click One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation (CVPR2021) Code for the paper One Thi

44 Dec 12, 2022

This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Computational Linguistics: ACL 2021.

XL-Sum This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Lang

190 Jan 3, 2023

Genetic feature selection module for scikit-learn

sklearn-genetic Genetic feature selection module for scikit-learn Genetic algorithms mimic the process of natural selection to search for optimal valu

260 Dec 14, 2022

Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561

Meta-Solver for Neural Ordinary Differential Equations Towards robust neural ODEs using parametrized solvers. Main idea Each Runge-Kutta (RK) solver w

25 Aug 12, 2021

Code for our paper Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation

CorDA Code for our paper Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation Prerequisite Please create and activate the follo

60 Nov 30, 2022

An official implementation of the paper Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers

Sequence Feature Alignment (SFA) By Wen Wang, Yang Cao, Jing Zhang, Fengxiang He, Zheng-jun Zha, Yonggang Wen, and Dacheng Tao This repository is an o

79 Dec 24, 2022

GEA - Code for Guided Evolution for Neural Architecture Search

Efficient Guided Evolution for Neural Architecture Search Usage Create a conda e

6 Jan 3, 2023

The implementation of the CVPR2021 paper "Structure-Aware Face Clustering on a Large-Scale Graph with 10^7 Nodes"

STAR-FC This code is the implementation for the CVPR 2021 paper "Structure-Aware Face Clustering on a Large-Scale Graph with 10^7 Nodes" 🌟 🌟 . 🎓 Re

87 Dec 28, 2022

Official Implement of CVPR 2021 paper “Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting”

RGBT Crowd Counting Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin. "Cross-Modal Collaborative Representation Learning and a L

37 Dec 8, 2022

Owner

wangxb

Data Mining & Machine Learning : ) Knowledge in Data

GitHub

An Efficient Training Approach for Very Large Scale Face Recognition or F²C for simplicity.

Fast Face Classification (F²C) This is the code of our paper An Efficient Training Approach for Very Large Scale Face Recognition or F²C for simplicit

33 Jun 27, 2021

PyTorch Implementation for AAAI'21 "Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection"

UMS for Multi-turn Response Selection Implements the model described in the following paper Do Response Selection Models Really Know What's Next? Utte

47 Nov 22, 2022

Implementation of "Selection via Proxy: Efficient Data Selection for Deep Learning" from ICLR 2020.

Selection via Proxy: Efficient Data Selection for Deep Learning This repository contains a refactored implementation of "Selection via Proxy: Efficien

70 Nov 16, 2022

The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".

Cutoff: A Simple Data Augmentation Approach for Natural Language This repository contains source code necessary to reproduce the results presented in

49 Dec 22, 2022

This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.

212 Dec 25, 2022

This is the official pytorch implementation of Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation(TESKD)

Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation (TESKD) By Zheng Li[1,4], Xiang Li[2], Lingfeng Yang[2,4], Jian Yang[2], Zh

9 Sep 26, 2022

Paper Code：A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection

Related tags

Overview

1. SaWDE.m is the main function

2. DataPartition.m is used to randomly partition the original data into training sets and test sets with a ratio of 7 : 3.

3. CSGSTest.m is used to test the performance of each strategy.

You might also like...

Code for the paper One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation, CVPR 2021.

This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Computational Linguistics: ACL 2021.

Genetic feature selection module for scikit-learn

Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561

Code for our paper Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation

An official implementation of the paper Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers

GEA - Code for Guided Evolution for Neural Architecture Search

The implementation of the CVPR2021 paper "Structure-Aware Face Clustering on a Large-Scale Graph with 10^7 Nodes"

Official Implement of CVPR 2021 paper “Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting”

Owner

wangxb

An Efficient Training Approach for Very Large Scale Face Recognition or F²C for simplicity.

PyTorch Implementation for AAAI'21 "Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection"

Implementation of "Selection via Proxy: Efficient Data Selection for Deep Learning" from ICLR 2020.

The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".

This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.

This is the official pytorch implementation of Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation(TESKD)

Code for the paper Task Agnostic Morphology Evolution.

UniLM AI - Large-scale Self-supervised Pre-training across Tasks, Languages, and Modalities

Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation (ICCV2021)

Code for paper: Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks