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 3351–3400 of 10307 papers

TitleStatusHype
Application of Artificial Intelligence in the Classification of Microscopical Starch Images for Drug Formulation—0
Bone Marrow Cytomorphology Cell Detection using InceptionResNetV2—0
Detection of depression on social networks using transformers and ensemblesCode0
Improving Implicit Feedback-Based Recommendation through Multi-Behavior AlignmentCode1
CrAFT: Compression-Aware Fine-Tuning for Efficient Visual Task Adaptation—0
SEGA: Structural Entropy Guided Anchor View for Graph Contrastive LearningCode0
MultiTACRED: A Multilingual Version of the TAC Relation Extraction DatasetCode1
Model-Contrastive Federated Domain Adaptation—0
Approximation by non-symmetric networks for cross-domain learning—0
Towards a Simple Framework of Skill Transfer Learning for Robotic Ultrasound-guidance ProceduresCode0
PointCMP: Contrastive Mask Prediction for Self-supervised Learning on Point Cloud VideosCode1
Cross-domain Augmentation Networks for Click-Through Rate Prediction—0
Online Gesture Recognition using Transformer and Natural Language Processing—0
Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning—0
Towards Effective Collaborative Learning in Long-Tailed Recognition—0
An Imitation Learning Based Algorithm Enabling Priori Knowledge Transfer in Modern Electricity Markets for Bayesian Nash Equilibrium Estimation—0
Avatar Knowledge Distillation: Self-ensemble Teacher Paradigm with UncertaintyCode1
Semi-supervised Domain Adaptation via Prototype-based Multi-level LearningCode1
Emulation Learning for Neuromimetic Systems—0
Shotgun crystal structure prediction using machine-learned formation energiesCode1
Transfer and Active Learning for Dissonance Detection: Addressing the Rare-Class ChallengeCode0
DocLangID: Improving Few-Shot Training to Identify the Language of Historical DocumentsCode0
Improving Contrastive Learning of Sentence Embeddings from AI FeedbackCode1
VPGTrans: Transfer Visual Prompt Generator across LLMsCode2
Improving Cancer Hallmark Classification with BERT-based Deep Learning Approach—0
Parameter-Efficient Cross-lingual Transfer of Vision and Language Models via Translation-based AlignmentCode0
Detect, Distill and Update: Detect, Distill and Update: Learned DB Systems Facing Out of Distribution DataCode0
CLIP-S^4: Language-Guided Self-Supervised Semantic Segmentation—0
Deception Detection with Feature-Augmentation by soft Domain Transfer—0
Towards Unbiased Training in Federated Open-world Semi-supervised Learning—0
Procedural Content Generation via Knowledge Transformation (PCG-KT)—0
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on GraphsCode0
Redundancy and Concept Analysis for Code-trained Language Models—0
Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and EquityCode0
A Transfer Learning Approach to Minimize Reinforcement Learning Risks in Energy Optimization for Smart Buildings—0
Transfer of knowledge among instruments in automatic music transcription—0
The ART of Transfer Learning: An Adaptive and Robust Pipeline—0
Few-shot Classification via Ensemble Learning with Multi-Order Statistics—0
Optimized Machine Learning for CHD Detection using 3D CNN-based Segmentation, Transfer Learning and Adagrad Optimization—0
Limits of Model Selection under Transfer Learning—0
Accelerated and Inexpensive Machine Learning for Manufacturing Processes with Incomplete Mechanistic Knowledge—0
Polyp-SAM: Transfer SAM for Polyp SegmentationCode1
NLNDE at SemEval-2023 Task 12: Adaptive Pretraining and Source Language Selection for Low-Resource Multilingual Sentiment Analysis—0
Towards Better Domain Adaptation for Self-supervised Models: A Case Study of Child ASRCode0
HausaNLP at SemEval-2023 Task 10: Transfer Learning, Synthetic Data and Side-Information for Multi-Level Sexism Classification—0
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential RecommendationCode0
Synergy of Machine and Deep Learning Models for Multi-Painter RecognitionCode0
BactInt: A domain driven transfer learning approach and a corpus for extracting inter-bacterial interactions from biomedical text—0
Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalization—0
Lightweight, Pre-trained Transformers for Remote Sensing TimeseriesCode2
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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