Active Learning

Active Learning is a paradigm in supervised machine learning which uses fewer training examples to achieve better optimization by iteratively training a predictor, and using the predictor in each iteration to choose the training examples which will increase its chances of finding better configurations and at the same time improving the accuracy of the prediction model

Source: Polystore++: Accelerated Polystore System for Heterogeneous Workloads

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 3051–3073 of 3073 papers

Title	Date	Tasks	Status	Hype
Active Learning Ranking from Pairwise Preferences with Almost Optimal Query Complexity	Dec 1, 2011	Active LearningLearning-To-Rank	—Unverified	0
Closing the Loop: Fast, Interactive Semi-Supervised Annotation With Queries on Features and Instances	Jul 1, 2011	Active LearningInformation Extraction	CodeCode Available	1
Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning	Dec 1, 2010	Active Learning	—Unverified	0
Active Learning Applied to Patient-Adaptive Heartbeat Classification	Dec 1, 2010	Active LearningClassification	—Unverified	0
Multi-View Active Learning in the Non-Realizable Case	Dec 1, 2010	Active Learning	—Unverified	0
Active Instance Sampling via Matrix Partition	Dec 1, 2010	Active LearningCombinatorial Optimization	—Unverified	0
Extensions of Generalized Binary Search to Group Identification and Exponential Costs	Dec 1, 2010	Active LearningObject	—Unverified	0
Agnostic Active Learning Without Constraints	Dec 1, 2010	Active LearningGeneral Classification	—Unverified	0
Active Learning by Querying Informative and Representative Examples	Dec 1, 2010	Active LearningInformativeness	—Unverified	0
Extended Active Learning Method	Nov 10, 2010	Active Learning	—Unverified	0
Near-Optimal Bayesian Active Learning with Noisy Observations	Oct 15, 2010	Active LearningExperimental Design	—Unverified	0
Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization	Mar 21, 2010	Active LearningMarketing	—Unverified	0
Sufficient Conditions for Agnostic Active Learnable	Dec 1, 2009	Active LearningGeneral Classification	—Unverified	0
Noisy Generalized Binary Search	Dec 1, 2009	Active LearningScheduling	—Unverified	0
Learning to Explore and Exploit in POMDPs	Dec 1, 2009	Active LearningReinforcement Learning	—Unverified	0
Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition	Dec 1, 2009	Active LearningDiagnostic	—Unverified	0
Submodularity Cuts and Applications	Dec 1, 2009	Active Learningfeature selection	—Unverified	0
Human Active Learning	Dec 1, 2008	Active LearningBIG-bench Machine Learning	—Unverified	0
Multiple-Instance Active Learning	Dec 1, 2007	Active Learningtext-classification	—Unverified	0
Discriminative Batch Mode Active Learning	Dec 1, 2007	Active Learning	—Unverified	0
Active Preference Learning with Discrete Choice Data	Dec 1, 2007	Active LearningDecision Making	—Unverified	0
Active Learning with Statistical Models	Mar 1, 1996	Active Learningregression	—Unverified	0
Building a Scalable and Interpretable Bayesian Deep Learning Framework for Quality Control of Free Form Surfaces	Apr 7, 1994	Active LearningBenchmarking	CodeCode Available	1

Show:10 25 50

← PrevPage 62 of 62Next →

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	TypiClust	Accuracy	93.2	—	Unverified
2	PT4AL	Accuracy	93.1	—	Unverified
3	Learning loss	Accuracy	91.01	—	Unverified
4	CoreGCN	Accuracy	90.7	—	Unverified
5	Core-set	Accuracy	89.92	—	Unverified
6	Random Baseline (Resnet18)	Accuracy	88.45	—	Unverified
7	Random Baseline (VGG16)	Accuracy	85.09	—	Unverified