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 6151–6200 of 10307 papers

TitleStatusHype
Do sound event representations generalize to other audio tasks? A case study in audio transfer learning—0
CUDA-GHR: Controllable Unsupervised Domain Adaptation for Gaze and Head RedirectionCode0
Data Optimisation for a Deep Learning Recommender System—0
Towards Better Shale Gas Production Forecasting Using Transfer Learning—0
Multirate Training of Neural NetworksCode0
Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery—0
Memory Oriented Transfer Learning for Semi-Supervised Image Deraining—0
Learning Graphs for Knowledge Transfer With Limited Labels—0
Amalgamating Knowledge From Heterogeneous Graph Neural NetworksCode1
Self-Supervised Learning on 3D Point Clouds by Learning Discrete Generative Models—0
Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection—0
Scalable Differential Privacy With Sparse Network Finetuning—0
Practical Transferability Estimation for Image Classification Tasks—0
Cross Modality Knowledge Distillation for Multi-Modal Aerial View Object ClassificationCode0
Cross-hospital Sepsis Early Detection via Semi-supervised Optimal Transport with Self-paced EnsembleCode0
Recurrent Stacking of Layers in Neural Networks: An Application to Neural Machine Translation—0
Golos: Russian Dataset for Speech ResearchCode1
Adversarial Training Helps Transfer Learning via Better Representations—0
Toward Fault Detection in Industrial Welding Processes with Deep Learning and Data Augmentation—0
MoVi: A large multi-purpose human motion and video datasetCode1
Dual-Teacher Class-Incremental Learning With Data-Free Generative Replay—0
PyKale: Knowledge-Aware Machine Learning from Multiple Sources in PythonCode1
Frustratingly Easy Transferability Estimation—0
Amortized Auto-Tuning: Cost-Efficient Bayesian Transfer Optimization for Hyperparameter RecommendationCode0
An Evaluation of Self-Supervised Pre-Training for Skin-Lesion AnalysisCode1
Deep Subdomain Adaptation Network for Image ClassificationCode1
Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event ExtractionCode1
A Hands-on Comparison of DNNs for Dialog Separation Using Transfer Learning from Music Source Separation—0
Evolving Image Compositions for Feature Representation Learning—0
Positional Contrastive Learning for Volumetric Medical Image SegmentationCode1
rSoccer: A Framework for Studying Reinforcement Learning in Small and Very Small Size Robot SoccerCode1
Bilateral Personalized Dialogue Generation with Contrastive LearningCode0
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification—0
Learning Stable Classifiers by Transferring Unstable FeaturesCode1
Generating Thermal Human Faces for Physiological Assessment Using Thermal Sensor Auxiliary LabelsCode0
User-specific Adaptive Fine-tuning for Cross-domain Recommendations—0
Zero-shot Node Classification with Decomposed Graph Prototype NetworkCode1
Incorporating Domain Knowledge into Health Recommender Systems using Hyperbolic Embeddings—0
Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification—0
Why Can You Lay Off Heads? Investigating How BERT Heads Transfer—0
Pre-Trained Models: Past, Present and Future—0
FGLP: A Federated Fine-Grained Location Prediction System for Mobile Users—0
HistoTransfer: Understanding Transfer Learning for Histopathology—0
Domain Generalization on Medical Imaging Classification using Episodic Training with Task Augmentation—0
Schema-Guided Paradigm for Zero-Shot DialogCode0
GenSF: Simultaneous Adaptation of Generative Pre-trained Models and Slot FillingCode0
CARTL: Cooperative Adversarially-Robust Transfer LearningCode0
Improving weakly supervised sound event detection with self-supervised auxiliary tasksCode1
Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification—0
ModelDiff: Testing-Based DNN Similarity Comparison for Model Reuse DetectionCode1
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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