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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 10176–10200 of 10307 papers

TitleStatusHype
Transfer learning approach for financial applications—0
Data-selective Transfer Learning for Multi-Domain Speech Recognition—0
Knowledge transfer between speakers for personalised dialogue management—0
Visual Classifier Prediction by Distributional Semantic Embedding of Text Descriptions—0
Multi-agent Reinforcement Learning with Sparse Interactions by Negotiation and Knowledge Transfer—0
Learning from LDA using Deep Neural Networks—0
Semantic Pose using Deep Networks Trained on Synthetic RGB-D—0
Invariant Models for Causal Transfer LearningCode0
A Probabilistic Approach to Knowledge Translation—0
Recipe recognition with large multimodal food datasetCode0
Online Transfer Learning in Reinforcement Learning Domains—0
Cross-lingual Transfer of Named Entity Recognizers without Parallel Corpora—0
Learning to Adapt Credible Knowledge in Cross-lingual Sentiment Analysis—0
Model Adaptation for Personalized Opinion Analysis—0
New Transfer Learning Techniques for Disparate Label Sets—0
An Iterative Similarity based Adaptation Technique for Cross-domain Text Classification—0
Word Order Typology through Multilingual Word Alignment—0
Dual Memory Architectures for Fast Deep Learning of Stream Data via an Online-Incremental-Transfer Strategy—0
Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective—0
Learning to Select Pre-Trained Deep Representations with Bayesian Evidence Framework—0
Knowledge Transfer Pre-training—0
Large-scale Simple Question Answering with Memory NetworksCode0
Joint Photo Stream and Blog Post Summarization and Exploration—0
Metric Imitation by Manifold Transfer for Efficient Vision Applications—0
A Deep Learning and Knowledge Transfer Based Architecture for Social Media User Characteristic Determination—0
Show:102550
← PrevPage 408 of 413Next →
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