A curated list of awesome Active Learning

Overview

Awesome Active Learning Awesome

🤩 A curated list of awesome Active Learning ! 🤩

Background

(image source: Settles, Burr)

What is Active Learning?

Active learning is a special case of machine learning in which a learning algorithm can interactively query a oracle (or some other information source) to label new data points with the desired outputs.

(image source: Settles, Burr)

There are situations in which unlabeled data is abundant but manual labeling is expensive. In such a scenario, learning algorithms can actively query the oracle for labels. This type of iterative supervised learning is called active learning. Since the learner chooses the examples, the number of examples to learn a concept can often be much lower than the number required in normal supervised learning. With this approach, there is a risk that the algorithm is overwhelmed by uninformative examples. Recent developments are dedicated to multi-label active learning, hybrid active learning and active learning in a single-pass (on-line) context, combining concepts from the field of machine learning (e.g. conflict and ignorance) with adaptive, incremental learning policies in the field of online machine learning.

(source: Wikipedia)

Contributing

If you find the awesome paper/code/book/tutorial or have some suggestions, please feel free to pull requests or contact [email protected] to add papers using the following Markdown format:

Year | Paper Name | Conference | [Paper](link) | [Code](link) | Tags | Notes |

Thanks for your valuable contribution to the research community. 😃

Table of Contents

Books

Surveys

Papers

Tags

Sur.: survey | Cri.: critics | Pool.: pool-based sampling | Str.: stream-based sampling | Syn.: membership query synthesize | Meta.: meta learning | SSL.: semi-supervised learning | RL.: reinforcement learning | FS.: few-shot learning | SS.: self-supervised |

Before 2017

Year Title Conf Paper Code Tags Notes
1994 Improving Generalization with Active Learning Machine Learning paper
2007 Discriminative Batch Mode Active Learning NIPS paper
2008 Active Learning with Direct Query Construction KDD paper
2008 An Analysis of Active Learning Strategies for Sequence Labeling Tasks EMNLP paper
2008 Hierarchical Sampling for Active Learning ICML paper
2010 Active Instance Sampling via Matrix Partition NIPS paper
2011 Ask Me Better Questions: Active Learning Queries Based on Rule Induction KDD paper
2011 Active Learning from Crowds ICML paper
2011 Bayesian Active Learning for Classification and Preference Learning CoRR paper
2011 Active Learning Using On-line Algorithms KDD paper
2012 Bayesian Optimal Active Search and Surveying ICML paper
2012 Batch Active Learning via Coordinated Matching ICML paper
2013 Active Learning for Multi-Objective Optimization ICML paper
2013 Active Learning for Probabilistic Hypotheses Usingthe Maximum Gibbs Error Criterion NIPS paper
2014 Active Semi-Supervised Learning Using Sampling Theory for Graph Signals KDD paper
2014 Beyond Disagreement-based Agnostic Active Learning NIPS paper
2016 Cost-Effective Active Learning for Deep Image Classification TCSVT paper
2016 Active Image Segmentation Propagation CVPR paper

2017

Title Conf Paper Code Tags Notes
Active Decision Boundary Annotation with Deep Generative Models ICCV paper
Active One-shot Learning CoRR paper code Str. RL. FS.
A Meta-Learning Approach to One-Step Active-Learning [email protected]/ECML paper Pool. Meta.
Generative Adversarial Active Learning arXiv paper Pool. Syn.
Active Learning from Peers NIPS paper
Learning Active Learning from Data NIPS paper code Pool.
Learning Algorithms for Active Learning ICML paper
Deep Bayesian Active Learning with Image Data ICML paper code Pool.

2018

Title Conf Paper Code Tags Notes
The Power of Ensembles for Active Learning in Image Classification CVPR paper
Adversarial Learning for Semi-Supervised Semantic Segmentation BMVC paper code Pool. SSL.
A Variance Maximization Criterion for Active Learning Pattern Recognition paper
Meta-Learning Transferable Active Learning Policies by Deep Reinforcement Learning ICLR-WS paper Pool. Meta. RL.
Active Learning for Convolutional Neural Networks: A Core-Set Approach ICLR paper
Adversarial Active Learning for Sequence Labeling and Generation IJCAI paper
Meta-Learning for Batch Mode Active Learning ICLR-WS paper

2019

Title Conf Paper Code Tags Notes
ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation CVPR paper Pool.
Bayesian Generative Active Deep Learning ICML paper code Pool. Semi.
Variational Adversarial Active Learning ICCV paper code Pool. SSL.
Integrating Bayesian and Discriminative Sparse Kernel Machines for Multi-class Active Learning NeurIPS paper
Active Learning via Membership Query Synthesisfor Semi-supervised Sentence Classification CoNLL paper
Discriminative Active Learning arXiv paper
Semantic Redundancies in Image-Classification Datasets: The 10% You Don’t Need arXiv paper
Bayesian Batch Active Learning as Sparse Subset Approximation NIPS paper
Learning Loss for Active Learning CVPR paper code Pool.
Rapid Performance Gain through Active Model Reuse IJCAI paper
Parting with Illusions about Deep Active Learning arXiv paper Cri.
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning NIPS paper

2020

Title Conf Paper Code Tags Notes
Reinforced active learning for image segmentation ICLR paper code Pool. RL.
[BADGE] Batch Active learning by Diverse Gradient Embeddings ICLR paper code Pool.
Adversarial Sampling for Active Learning WACV paper Pool.
Online Active Learning of Reject Option Classifiers AAAI paper
Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision CVPR paper
Deep Reinforcement Active Learning for Medical Image Classification MICCAI paper Pool. RL.
State-Relabeling Adversarial Active Learning CVPR paper code Pool.
Towards Robust and Reproducible Active Learning Using Neural Networks arXiv paper Cri.
Consistency-Based Semi-supervised Active Learning: Towards Minimizing Labeling Cost ECCV paper Pool. SSL.

2021

Title Conf Paper Code Tags Notes
MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning arXiv paper Pool. Meta. RL.
Can Active Learning Preemptively Mitigate Fairness Issues ICLR-RAI paper code Pool. Thinking fairness issues
Sequential Graph Convolutional Network for Active Learning CVPR paper code Pool.
Task-Aware Variational Adversarial Active Learning CVPR paper code Pool.
Effective Evaluation of Deep Active Learning on Image Classification Tasks arXiv paper Cri.
Semi-Supervised Active Learning for Semi-Supervised Models: Exploit Adversarial Examples With Graph-Based Virtual Labels ICCV paper Pool. SSL.
Contrastive Coding for Active Learning under Class Distribution Mismatch ICCV paper code Pool. Defines a good question
Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering ACL-IJCNLP paper code Pool. Thinking about outliers
LADA: Look-Ahead Data Acquisition via Augmentation for Active Learning NeurIPS paper Pool.
Multi-Anchor Active Domain Adaptation for Semantic Segmentation ICCV paper code Pool.
Active Learning for Lane Detection: A Knowledge Distillation Approach ICCV paper Pool.
Active Contrastive Learning of Audio-Visual Video Representations ICLR paper code Pool.
Multiple instance active learning for object detection CVPR paper code Pool.
SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency NeurIPS paper Robot exploration
Influence Selection for Active Learning ICCV paper code Pool.
Reducing Label Effort: Self-Supervised meets Active Learning arXiv paper Pool. SS. Cri. A meaningful attempt on the combination of SS & AL

Turtorials

Tools

Owner
BAI Fan
Deep Learning, Active Learning, Robotics, Artificial Intelligence.
BAI Fan
HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset (ICCV 2021)

Code for HDR Video Reconstruction HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset (ICCV 2021) Guanying Chen, Cha

Guanying Chen 64 Nov 19, 2022
CVPR2021 Workshop - HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization.

HDRUNet [Paper Link] HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization By Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao an

XyChen 105 Dec 20, 2022
Self-Supervised Learning for Domain Adaptation on Point-Clouds

Self-Supervised Learning for Domain Adaptation on Point-Clouds Introduction Self-supervised learning (SSL) allows to learn useful representations from

Idan Achituve 66 Dec 20, 2022
PyTorch reimplementation of REALM and ORQA

PyTorch reimplementation of REALM and ORQA

Li-Huai (Allan) Lin 17 Aug 20, 2022
Liver segmentation using MONAI and pytorch

Machine Learning use case in the field of Healthcare. In this project MONAI and pytorch frameworks are used for 3D Liver segmentation.

Abhishek Gajbhiye 2 May 30, 2022
A mini lib that implements several useful functions binding to PyTorch in C++.

Torch-gather A mini library that implements several useful functions binding to PyTorch in C++. What does gather do? Why do we need it? When dealing w

maxwellzh 8 Sep 07, 2022
An Straight Dilated Network with Wavelet for image Deblurring

SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurring(offical) 1. Introduction This repo is not only used for our paper(

FlyEgle 41 Jan 04, 2023
Yoga - Yoga asana classifier for python

Yoga Asana Classifier Description Hi welcome to my new deep learning project "Yo

Programminghut 35 Dec 12, 2022
CondenseNet: Light weighted CNN for mobile devices

CondenseNets This repository contains the code (in PyTorch) for "CondenseNet: An Efficient DenseNet using Learned Group Convolutions" paper by Gao Hua

Shichen Liu 690 Nov 30, 2022
Automatic Number Plate Recognition using Contours and Convolution Neural Networks (CNN)

Cite our paper if you find this project useful https://www.ijariit.com/manuscripts/v7i4/V7I4-1139.pdf Abstract Image processing technology is used in

Adithya M 2 Jun 28, 2022
Scikit-event-correlation - Event Correlation and Forecasting over High Dimensional Streaming Sensor Data algorithms

scikit-event-correlation Event Correlation and Changing Detection Algorithm Theo

Intellia ICT 5 Oct 30, 2022
State of the Art Neural Networks for Generative Deep Learning

pyradox-generative State of the Art Neural Networks for Generative Deep Learning Table of Contents pyradox-generative Table of Contents Installation U

Ritvik Rastogi 8 Sep 29, 2022
SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement

SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement This repository implements the approach described in SporeAgent: Reinforced

Dominik Bauer 5 Jan 02, 2023
Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature-Based Decisions

APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i

kenro515 3 Jan 04, 2023
PyTorch implementation of "MLP-Mixer: An all-MLP Architecture for Vision" Tolstikhin et al. (2021)

mlp-mixer-pytorch PyTorch implementation of "MLP-Mixer: An all-MLP Architecture for Vision" Tolstikhin et al. (2021) Usage import torch from mlp_mixer

isaac 27 Jul 09, 2022
"Domain Adaptive Semantic Segmentation without Source Data" (ACM MM 2021)

LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.

benfour 16 Sep 28, 2022
Gesture-Volume-Control - This Python program can adjust the system's volume by using hand gestures

Gesture-Volume-Control This Python program can adjust the system's volume by usi

VatsalAryanBhatanagar 1 Dec 30, 2021
PN-Net a neural field-based framework for depth estimation from single-view RGB images.

PN-Net We present a neural field-based framework for depth estimation from single-view RGB images. Rather than representing a 2D depth map as a single

1 Oct 02, 2021
Mixup for Supervision, Semi- and Self-Supervision Learning Toolbox and Benchmark

OpenSelfSup News Downstream tasks now support more methods(Mask RCNN-FPN, RetinaNet, Keypoints RCNN) and more datasets(Cityscapes). 'GaussianBlur' is

AI Lab, Westlake University 332 Jan 03, 2023
Framework for training options with different attention mechanism and using them to solve downstream tasks.

Using Attention in HRL Framework for training options with different attention mechanism and using them to solve downstream tasks. Requirements GPU re

5 Nov 03, 2022