Matlab source code of the paper: D. Wu*, C-T Lin and J. Huang*, "Active Learning for Regression Using Greedy Sampling," Information Sciences, vol. 474, pp. 90-105, 2019.

Matlab source code of the iRDM algorithm in the paper: Z. Liu, X. Jiang, H. Luo, W. Fang, J. Liu and D. Wu*, "Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM)," Pattern Recognition Letters, 142:11-19, 2021.

The demo partially associated with the following papers: "Spatial Prior Fuzziness Pool-Based Interactive Classification of Hyperspectral Images" and "Multiclass Non-Randomized Spectral–Spatial Active Learning for Hyperspectral Image Classification".

The Matlab code of "A Variance Maximization Criterion for Active Learning"

Active Learning Project

ALPUD: Active Learning from Positive and Unlabeled Data

This repository contains the code to reproduce all of the results in our paper: Nuclear discrepancy for single-shot batch active learning, Tom J Viering, Jesse H Krijthe, Marco Loog, in Machine Learning 2019.

Matlab code of the IRD algorithm in the paper: 刘子昂, 蒋雪, 伍冬睿, "基于池的无监督线性回归主动学习," 自动化学报, 2020. Or the English version here: https://arxiv.org/pdf/2001.05028.pdf

Matlab source code of the paper: D. Wu, "Pool-based sequential active learning for regression," IEEE Trans. on Neural Networks and Learning Systems, 30(5), pp. 1348-1359, 2019.

The code of ''Single Shot Active Learning using Pseudo Annotators"

Domain Adaptation by Transferring Model-Complexity Priors Across Tasks Paper Experiments

Language Agnostic Syllabification with Active Learning

A toolbox for Weighted Sparse Simplex Representation (WSSR).

Gaussian Processes for Cyclic Voltammetry

Quantile set inversion [arXiv:2211.01008] — Numerical experiments

This is a repository for CS4ML. It is a general framework for active learning in regression problems. It approximates a target function arising from general types of data, rather than pointwise samples.

Active Learning combining Online Semi-Supervised Dictionary Learning

Project source code and data for risk estimation with an imperfect Machine learning model

Active learning-guided exploration of parameter space of air plasmas to enhance the energy efficiency of NO x production