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 431–440 of 10307 papers

Title	Date	Tasks	Status	Hype	Score
An Evaluation of Self-Supervised Pre-Training for Skin-Lesion Analysis	Jun 17, 2021	Transfer Learning	CodeCode Available	1	5
A Qualitative Evaluation of Language Models on Automatic Question-Answering for COVID-19	Jun 19, 2020	ChatbotLanguage Modeling	CodeCode Available	1	5
Denoised Self-Augmented Learning for Social Recommendation	May 22, 2023	Self-Supervised LearningTransfer Learning	CodeCode Available	1	5
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification	Jul 11, 2020	ClassificationGeneral Classification	CodeCode Available	1	5
Adversarial Masking for Self-Supervised Learning	Jan 31, 2022	Representation LearningSelf-Supervised Learning	CodeCode Available	1	5
An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural Representations	May 15, 2023	Automated Theorem ProvingTransfer Learning	CodeCode Available	1	5
Automated Cloud Provisioning on AWS using Deep Reinforcement Learning	Sep 13, 2017	Cloud ComputingDeep Reinforcement Learning	CodeCode Available	1	5
DenseShift: Towards Accurate and Efficient Low-Bit Power-of-Two Quantization	Aug 20, 2022	QuantizationTransfer Learning	CodeCode Available	1	5
Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity	Sep 6, 2020	NMTTransfer Learning	CodeCode Available	1	5
An Encoder-Decoder Based Audio Captioning System With Transfer and Reinforcement Learning	Aug 5, 2021	Audio captioningDecoder	CodeCode Available	1	5

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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