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 10151–10200 of 10307 papers

TitleStatusHype
Minimally Supervised Feature Selection for Classification (Master's Thesis, University Politehnica of Bucharest)—0
Reuse of Neural Modules for General Video Game Playing—0
What can we learn about CNNs from a large scale controlled object dataset?—0
Unsupervised Domain Adaptation for Zero-Shot Learning—0
Confidence Preserving Machine for Facial Action Unit Detection—0
Learning to Transfer: Transferring Latent Task Structures and Its Application to Person-Specific Facial Action Unit Detection—0
Bayesian Model Adaptation for Crowd Counts—0
The Multiverse Loss for Robust Transfer Learning—0
Homophily and missing links in citation networks—0
Integrating Deep Features for Material Recognition—0
Actor-Mimic: Deep Multitask and Transfer Reinforcement LearningCode0
Multilingual Relation Extraction using Compositional Universal SchemaCode0
Transfer Learning for Speech and Language Processing—0
Net2Net: Accelerating Learning via Knowledge TransferCode0
Heterogeneous Knowledge Transfer in Video Emotion Recognition, Attribution and Summarization—0
AgeNet: Deeply Learned Regressor and Classifier for Robust Apparent Age Estimation—0
Natural Language Object RetrievalCode0
Representational Distance Learning for Deep Neural Networks—0
Basic Level Categorization Facilitates Visual Object Recognition—0
Convolutional Neural Network for Stereotypical Motor Movement Detection in Autism—0
Learn on Source, Refine on Target:A Model Transfer Learning Framework with Random ForestsCode0
Prediction-Adaptation-Correction Recurrent Neural Networks for Low-Resource Language Speech Recognition—0
Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks—0
Learning under Covariate Shift for Domain Adaptation for Word Sense Disambiguation—0
Transfer Learning from Deep Features for Remote Sensing and Poverty MappingCode0
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
Model Adaptation for Personalized Opinion Analysis—0
New Transfer Learning Techniques for Disparate Label Sets—0
Learning to Adapt Credible Knowledge in Cross-lingual Sentiment Analysis—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
A Deep Learning and Knowledge Transfer Based Architecture for Social Media User Characteristic Determination—0
Learning a Non-Linear Knowledge Transfer Model for Cross-View Action Recognition—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