SOTAVerified

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

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Showing 10051–10075 of 10307 papers

TitleStatusHype
Image Credibility Analysis with Effective Domain Transferred Deep Networks—0
Deep Transfer Learning for Person Re-identification—0
Intrinsic Geometric Information Transfer Learning on Multiple Graph-Structured Datasets—0
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot TranslationCode0
Predicting User Roles in Social Networks using Transfer Learning with Feature Transformation—0
Incremental Sequence LearningCode0
Beyond Fine Tuning: A Modular Approach to Learning on Small Data—0
Binary Paragraph Vectors—0
A General Regularization Framework for Domain Adaptation—0
Learning to Generate Textual Data—0
Transferring User Interests Across Websites with Unstructured Text for Cold-Start Recommendation—0
Named Entity Recognition for Novel Types by Transfer Learning—0
Local Similarity-Aware Deep Feature Embedding—0
Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes—0
Learning Bound for Parameter Transfer Learning—0
Regret Bounds for Lifelong Learning—0
Tool and Phase recognition using contextual CNN features—0
A Growing Long-term Episodic & Semantic Memory—0
Kernel Alignment for Unsupervised Transfer Learning—0
Semi-supervised Knowledge Transfer for Deep Learning from Private Training DataCode0
Generalized Online Transfer Learning for Climate Control in Residential Buildings—0
Multi-Task Curriculum Transfer Deep Learning of Clothing Attributes—0
Personalizing a Dialogue System with Transfer Reinforcement Learning—0
DeepGaze II: Reading fixations from deep features trained on object recognition—0
Asynchronous Multi-Task LearningCode0
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All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified