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 8601–8650 of 10307 papers

TitleStatusHype
Transferable Neural Processes for Hyperparameter Optimization—0
Recognition Of Surface Defects On Steel Sheet Using Transfer Learning—0
Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning—0
Video Surveillance of Highway Traffic Events by Deep Learning Architectures—0
Learning Action-Transferable Policy with Action EmbeddingCode0
Effective Domain Knowledge Transfer with Soft Fine-tuning—0
A Transfer Learning Approach for Network Intrusion Detection—0
Investigating Multilingual NMT Representations at Scale—0
ACES -- Automatic Configuration of Energy Harvesting Sensors with Reinforcement Learning—0
Graph Transfer Learning via Adversarial Domain Adaptation with Graph ConvolutionCode0
Decoupled Box Proposal and Featurization with Ultrafine-Grained Semantic Labels Improve Image Captioning and Visual Question Answering—0
Tensor Analysis with n-Mode Generalized Difference SubspaceCode0
A CNN-based approach to classify cricket bowlers based on their bowling actions—0
Multimodal Deep Learning for Mental Disorders Prediction from Audio Speech Samples—0
Personalizing Smartwatch Based Activity Recognition Using Transfer Learning—0
Federated Imitation Learning: A Privacy Considered Imitation Learning Framework for Cloud Robotic Systems with Heterogeneous Sensor Data—0
Generalization in Transfer Learning—0
Transfer Fine-Tuning: A BERT Case StudyCode0
Transfer Learning Between Related Tasks Using Expected Label ProportionsCode0
Zero-shot transfer for implicit discourse relation classification—0
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation—0
Multi-lingual Wikipedia Summarization and Title Generation On Low Resource Corpus—0
Cross-Domain Training for Goal-Oriented Conversational Agents—0
Leveraging Non-Conversational Tasks for Low Resource Slot Filling: Does it help?—0
NITK-IT_NLP@NSURL2019: Transfer Learning based POS Tagger for Under Resourced Bhojpuri and Magahi Language—0
Repurposing Decoder-Transformer Language Models for Abstractive Summarization—0
Energy Clustering for Unsupervised Person Re-identification—0
Detecting floodwater on roadways from image data with handcrafted features and deep transfer learningCode0
TGG: Transferable Graph Generation for Zero-shot and Few-shot LearningCode0
Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment ClassificationCode0
Defeating Misclassification Attacks Against Transfer Learning—0
Ellipsis Resolution as Question Answering: An EvaluationCode0
Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning—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
Analyzing Customer Feedback for Product Fit Prediction—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
Improving Automatic Jazz Melody Generation by Transfer Learning TechniquesCode0
A Semantics-Guided Class Imbalance Learning Model for Zero-Shot Classification—0
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
P2L: Predicting Transfer Learning for Images and Semantic Relations—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