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 7051–7075 of 10307 papers

TitleStatusHype
Exploring Knowledge Distillation of a Deep Neural Network for Multi-Script identification—0
Versatile and Robust Transient Stability Assessment via Instance Transfer Learning—0
Intrinsically Motivated Open-Ended Multi-Task Learning Using Transfer Learning to Discover Task HierarchyCode0
An Empirical Study on Measuring the Similarity of Sentential Arguments with Language Model Domain Adaptation—0
Fortify Machine Learning Production Systems: Detect and Classify Adversarial Attacks—0
Transfer Learning for Linear Regression: a Statistical Test of Gain—0
Geostatistical Learning: Challenges and OpportunitiesCode0
Learning Visual Models using a Knowledge Graph as a Trainer—0
Ensemble Transfer Learning of Elastography and B-mode Breast Ultrasound Images—0
Improving speech recognition models with small samples for air traffic control systems—0
Boosting Deep Transfer Learning for COVID-19 Classification—0
FEWS: Large-Scale, Low-Shot Word Sense Disambiguation with the Dictionary—0
Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies—0
Fast End-to-End Speech Recognition via Non-Autoregressive Models and Cross-Modal Knowledge Transferring from BERT—0
Identifying Misinformation from Website Screenshots—0
Transfer Learning for Future Wireless Networks: A Comprehensive Survey—0
indicnlp@kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian LanguagesCode0
indicnlp@ kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian LanguagesCode0
Self Regulated Learning Mechanism for Data Efficient Knowledge Distillation—0
Learning Student-Friendly Teacher Networks for Knowledge Distillation—0
Emoji-Based Transfer Learning for Sentiment TasksCode0
Transformer-Based Approaches for Automatic Music TranscriptionCode0
Anomaly Detection through Transfer Learning in Agriculture and Manufacturing IoT Systems—0
Real-Time Topology Optimization in 3D via Deep Transfer LearningCode0
Conditional Loss and Deep Euler Scheme for Time Series Generation—0
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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