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 10051–10100 of 10307 papers

TitleStatusHype
Deep Transfer Learning for Person Re-identification—0
Image Credibility Analysis with Effective Domain Transferred Deep Networks—0
Intrinsic Geometric Information Transfer Learning on Multiple Graph-Structured Datasets—0
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot TranslationCode0
Predicting User Roles in Social Networks using Transfer Learning with Feature Transformation—0
Incremental Sequence LearningCode0
Beyond Fine Tuning: A Modular Approach to Learning on Small Data—0
Binary Paragraph Vectors—0
A General Regularization Framework for Domain Adaptation—0
Learning to Generate Textual Data—0
Transferring User Interests Across Websites with Unstructured Text for Cold-Start Recommendation—0
Named Entity Recognition for Novel Types by Transfer Learning—0
Local Similarity-Aware Deep Feature Embedding—0
Learning Bound for Parameter Transfer Learning—0
Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes—0
Regret Bounds for Lifelong Learning—0
Tool and Phase recognition using contextual CNN features—0
A Growing Long-term Episodic & Semantic Memory—0
Kernel Alignment for Unsupervised Transfer Learning—0
Semi-supervised Knowledge Transfer for Deep Learning from Private Training DataCode0
Generalized Online Transfer Learning for Climate Control in Residential Buildings—0
Multi-Task Curriculum Transfer Deep Learning of Clothing Attributes—0
Personalizing a Dialogue System with Transfer Reinforcement Learning—0
DeepGaze II: Reading fixations from deep features trained on object recognition—0
Asynchronous Multi-Task LearningCode0
Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer—0
How should we evaluate supervised hashing?Code0
Transfer Learning for Material Classification using Convolutional Networks—0
Towards Deep Symbolic Reinforcement Learning—0
An Iterative Transfer Learning Based Ensemble Technique for Automatic Short Answer Grading—0
Transfer String Kernel for Cross-Context DNA-Protein Binding PredictionCode0
Towards Automated Melanoma Screening: Exploring Transfer Learning Schemes—0
What makes ImageNet good for transfer learning?Code0
Transfer Learning for Endoscopic Image Classification—0
A novel transfer learning method based on common space mapping and weighted domain matching—0
Generative Knowledge Transfer for Neural Language Models—0
Deep Convolution Networks for Compression Artifacts ReductionCode0
Letter Sequence Labeling for Compound Splitting—0
Language Transfer Learning for Supervised Lexical Substitution—0
Cross-domain Text Classification with Multiple Domains and Disparate Label Sets—0
A Two-stage Approach for Extending Event Detection to New Types via Neural Networks—0
A Multi-media Approach to Cross-lingual Entity Knowledge Transfer—0
Modeling Social Norms Evolution for Personalized Sentiment Classification—0
A Domain Adaptation Regularization for Denoising Autoencoders—0
Cross-Lingual Image Caption Generation—0
Transductive Adaptation of Black Box Predictions—0
Towards Generalizable Sentence Embeddings—0
Hyperparameter Transfer Learning through Surrogate Alignment for Efficient Deep Neural Network Training—0
Re-presenting a Story by Emotional Factors using Sentimental Analysis Method—0
Effects of Additional Data on Bayesian Clustering—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