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 8551–8600 of 10307 papers

TitleStatusHype
Leveraging Non-Conversational Tasks for Low Resource Slot Filling: Does it help?—0
Zero-shot transfer for implicit discourse relation classification—0
Transfer Learning Between Related Tasks Using Expected Label ProportionsCode0
Repurposing Decoder-Transformer Language Models for Abstractive Summarization—0
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation—0
Detecting floodwater on roadways from image data with handcrafted features and deep transfer learningCode0
Energy Clustering for Unsupervised Person Re-identification—0
Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment ClassificationCode0
TGG: Transferable Graph Generation for Zero-shot and Few-shot LearningCode0
Ellipsis Resolution as Question Answering: An EvaluationCode0
Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning—0
Defeating Misclassification Attacks Against Transfer Learning—0
Analyzing Customer Feedback for Product Fit Prediction—0
DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic LandslidesCode0
Online Sensor Hallucination via Knowledge Distillation for Multimodal Image Classification—0
Transfer Learning from Partial Annotations for Whole Brain Segmentation—0
Unsupervised Deep Feature Transfer for Low Resolution Image Classification—0
MIDAS: A Dialog Act Annotation Scheme for Open Domain Human Machine Spoken ConversationsCode0
Sentence-BERT: Sentence Embeddings using Siamese BERT-NetworksCode1
A Semantics-Guided Class Imbalance Learning Model for Zero-Shot Classification—0
Improving Automatic Jazz Melody Generation by Transfer Learning TechniquesCode0
Learning to Discover Novel Visual Categories via Deep Transfer ClusteringCode1
Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans—0
Urban flows prediction from spatial-temporal data using machine learning: A survey—0
Don't Just Scratch the Surface: Enhancing Word Representations for Korean with HanjaCode0
A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity RecognizersCode0
LEAP nets for power grid perturbationsCode0
Tiered Graph Autoencoders with PyTorch Geometric for Molecular Graphs—0
Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning—0
Automated Multi-sequence Cardiac MRI Segmentation Using Supervised Domain Adaptation—0
Transferring Robustness for Graph Neural Network Against Poisoning AttacksCode0
P2L: Predicting Transfer Learning for Images and Semantic Relations—0
Cross-Enhancement Transform Two-Stream 3D ConvNets for Action Recognition—0
Models Genesis: Generic Autodidactic Models for 3D Medical Image AnalysisCode1
Latent User Linking for Collaborative Cross Domain Recommendation—0
An Autonomous Performance Testing Framework using Self-Adaptive Fuzzy Reinforcement LearningCode0
Transfer Learning-Based Label Proportions Method with Data of Uncertainty—0
Transfer in Deep Reinforcement Learning using Knowledge Graphs—0
Two-Staged Acoustic Modeling Adaption for Robust Speech Recognition by the Example of German Oral History Interviews—0
VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual NavigationCode1
Language Graph Distillation for Low-Resource Machine Translation—0
PubLayNet: largest dataset ever for document layout analysisCode2
Regularizing CNN Transfer Learning with Randomised Regression—0
Few-Shot Dialogue Generation Without Annotated Data: A Transfer Learning Approach—0
Transferable Contrastive Network for Generalized Zero-Shot Learning—0
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems—0
Multitask and Transfer Learning for Autotuning Exascale Applications—0
Skill Transfer in Deep Reinforcement Learning under Morphological Heterogeneity—0
End-to-End Multi-Speaker Speech Recognition using Speaker Embeddings and Transfer Learning—0
Generalizing Deep Whole Brain Segmentation for Pediatric and Post-Contrast MRI with Augmented Transfer Learning—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