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 5326–5350 of 10307 papers

TitleStatusHype
Improving Meta-Learning Generalization with Activation-Based Early-StoppingCode0
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift—0
The Importance of the Instantaneous Phase in Detecting Faces with Convolutional Neural Networks—0
Content-Based Landmark Retrieval Combining Global and Local Features using Siamese Neural NetworksCode0
Cross-Lingual Knowledge Transfer for Clinical PhenotypingCode0
A Novel Transformer Network with Shifted Window Cross-Attention for Spatiotemporal Weather Forecasting—0
The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence—0
Learning from flowsheets: A generative transformer model for autocompletion of flowsheets—0
A Survey of Learning on Small Data: Generalization, Optimization, and Challenge—0
Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain RandomizationCode0
A Transfer Learning-Based Approach to Marine Vessel Re-Identification—0
Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder—0
Combining human parsing with analytical feature extraction and ranking schemes for high-generalization person reidentification—0
A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks—0
Applied Computer Vision on 2-Dimensional Lung X-Ray Images for Assisted Medical Diagnosis of Pneumonia—0
Generalizable multi-task, multi-domain deep segmentation of sparse pediatric imaging datasets via multi-scale contrastive regularization and multi-joint anatomical priors—0
Structural Similarity for Improved Transfer in Reinforcement Learning—0
AI Approaches in Processing and Using Data in Personalized Medicine—0
AMF: Adaptable Weighting Fusion with Multiple Fine-tuning for Image Classification—0
Learning structures of the French clinical language:development and validation of word embedding models using 21 million clinical reports from electronic health records—0
Active Learning of Ordinal Embeddings: A User Study on Football Data—0
Fine-Tuning BERT for Automatic ADME Semantic Labeling in FDA Drug Labeling to Enhance Product-Specific Guidance Assessment—0
SecretGen: Privacy Recovery on Pre-Trained Models via Distribution DiscriminationCode0
From Multi-label Learning to Cross-Domain Transfer: A Model-Agnostic Approach—0
ArmanEmo: A Persian Dataset for Text-based Emotion DetectionCode0
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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