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 2191–2200 of 10307 papers

Title	Date	Tasks	Status	Score
BERT for Sentiment Analysis: Pre-trained and Fine-Tuned Alternatives	Jan 10, 2022	Sentiment Analysistext-classification	CodeCode Available	5
BERT-Based Approach for Automating Course Articulation Matrix Construction with Explainable AI	Nov 21, 2024	POSTransfer Learning	CodeCode Available	5
Gated Domain Units for Multi-source Domain Generalization	Jun 24, 2022	Domain GeneralizationTransfer Learning	CodeCode Available	5
BertaQA: How Much Do Language Models Know About Local Culture?	Jun 11, 2024	Multiple-choiceTransfer Learning	CodeCode Available	5
Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem Solving	Aug 5, 2024	Geometry-based operator learningMulti-Task Learning	CodeCode Available	5
Context selectivity with dynamic availability enables lifelong continual learning	Jun 2, 2023	Continual LearningLifelong learning	CodeCode Available	5
Generalizable Local Feature Pre-training for Deformable Shape Analysis	Mar 27, 2023	Transfer Learning	CodeCode Available	5
General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learning	May 13, 2018	Deep Reinforcement LearningReinforcement Learning	CodeCode Available	5
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations	Jun 14, 2018	image-classificationImage Classification	CodeCode Available	5
Bengali Handwritten Character Classification using Transfer Learning on Deep Convolutional Neural Network	Feb 25, 2019	Ensemble LearningGeneral Classification	CodeCode Available	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