Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1521–1530 of 10307 papers

Title	Date	Tasks	Status	Hype
Temporal 3D ConvNets: New Architecture and Transfer Learning for Video Classification	Nov 22, 2017	Action RecognitionGeneral Classification	CodeCode Available	1
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise	Nov 20, 2017	ClassificationGeneral Classification	CodeCode Available	1
Bayesian Optimization with Automatic Prior Selection for Data-Efficient Direct Policy Search	Sep 20, 2017	Bayesian OptimizationTransfer Learning	CodeCode Available	1
Automated Cloud Provisioning on AWS using Deep Reinforcement Learning	Sep 13, 2017	Cloud ComputingDeep Reinforcement Learning	CodeCode Available	1
Like What You Like: Knowledge Distill via Neuron Selectivity Transfer	Jul 5, 2017	object-detectionObject Detection	CodeCode Available	1
Deep Hashing Network for Unsupervised Domain Adaptation	Jun 22, 2017	Deep HashingDomain Adaptation	CodeCode Available	1
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data	May 5, 2017	Cross-Lingual Natural Language InferenceNatural Language Inference	CodeCode Available	1
Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks	Mar 18, 2017	Feature EngineeringNamed Entity Recognition (NER)	CodeCode Available	1
Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles	Mar 30, 2016	Representation LearningTransfer Learning	CodeCode Available	1
Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning	Oct 13, 2015	Document ClassificationRepresentation Learning	CodeCode Available	1

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All datasets Office-Home 100 sleep nights of 8 caregivers BanglaLekha Isolated Dataset COCO70 KITTI Object Tracking Evaluation 2012 Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	APCLIP	Accuracy	84.2	—	Unverified
2	DFA-ENT	Accuracy	69.2	—	Unverified
3	DFA-SAFN	Accuracy	69.1	—	Unverified
4	EasyTL	Accuracy	63.3	—	Unverified
5	MEDA	Accuracy	60.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN	10-20% Mask PSNR	3.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Chatterjee, Dutta et al.[1]	Accuracy	96.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Co-Tuning	Accuracy	85.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Physical Access	EER	5.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	riadd.aucmedi	AUROC	0.95	—	Unverified