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 9301–9350 of 10307 papers

TitleStatusHype
Fast Approach to Build an Automatic Sentiment Annotator for Legal Domain using Transfer Learning—0
Transfer Learning via Unsupervised Task Discovery for Visual Question AnsweringCode0
Target Aware Network Adaptation for Efficient Representation Learning—0
Continuous Word Embedding Fusion via Spectral Decomposition—0
A Simple yet Effective Joint Training Method for Cross-Lingual Universal Dependency Parsing—0
CUNI Basque-to-English Submission in IWSLT18—0
Language Independent Sentiment Analysis with Sentiment-Specific Word Embeddings—0
The JHU/KyotoU Speech Translation System for IWSLT 2018—0
Learning Representations for Detecting Abusive Language—0
An Interpretable Neural Network with Topical Information for Relevant Emotion Ranking—0
Learning Text Representations for 500K Classification Tasks on Named Entity DisambiguationCode0
Learning Unsupervised Word Translations Without Adversaries—0
Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention MechanismCode0
Improving Multi-label Emotion Classification via Sentiment Classification with Dual Attention Transfer Network—0
Hunter NMT System for WMT18 Biomedical Translation Task: Transfer Learning in Neural Machine Translation—0
Phonological Features for Morphological Inflection—0
Similarity-Based Reconstruction Loss for Meaning Representation—0
Adapting Multilingual NMT to Extremely Low Resource Languages FBK’s Participation in the Basque-English Low-Resource MT Task, IWSLT 2018—0
Did you offend me? Classification of Offensive Tweets in Hinglish LanguageCode0
Syntax-based Transfer Learning for the Task of Biomedical Relation Extraction—0
Exploring Named Entity Recognition As an Auxiliary Task for Slot Filling in Conversational Language Understanding—0
The SLT-Interactions Parsing System at the CoNLL 2018 Shared Task—0
Transfer and Multi-Task Learning for Noun--Noun Compound Interpretation—0
Posture recognition using an RGB-D camera : exploring 3D body modeling and deep learning approaches—0
Bayesian Transfer Reinforcement Learning with Prior Knowledge Rules—0
Reuse and Adaptation for Entity Resolution through Transfer Learning—0
Learning Robust, Transferable Sentence Representations for Text Classification—0
Using Multi-task and Transfer Learning to Solve Working Memory Tasks—0
Transferrable End-to-End Learning for Protein Interface Prediction—0
Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards—0
Zero-Resource Multilingual Model Transfer: Learning What to Share—0
Transfer Value or Policy? A Value-centric Framework Towards Transferrable Continuous Reinforcement Learning—0
Weakly-Supervised Localization and Classification of Proximal Femur Fractures—0
An analytic theory of generalization dynamics and transfer learning in deep linear networks—0
Measuring Density and Similarity of Task Relevant Information in Neural Representations—0
Learning Physics Priors for Deep Reinforcement Learing—0
Language Modeling Teaches You More Syntax than Translation Does: Lessons Learned Through Auxiliary Task Analysis—0
Developmental Bayesian Optimization of Black-Box with Visual Similarity-Based Transfer Learning—0
Deep Transfer Learning of Pick Points on Fabric for Robot Bed-MakingCode0
Non-native children speech recognition through transfer learning—0
Mind Your Language: Abuse and Offense Detection for Code-Switched Languages—0
Domain Adaptation for Robot Predictive Maintenance Systems—0
DT-LET: Deep Transfer Learning by Exploring where to Transfer—0
Segmentation of Skin Lesions and their Attributes Using Multi-Scale Convolutional Neural Networks and Domain Specific Augmentations—0
On Reinforcement Learning for Full-length Game of StarCraft—0
Global Weighted Average Pooling Bridges Pixel-level Localization and Image-level Classification—0
A Meta-Learning Approach for Custom Model Training—0
Target Transfer Q-Learning and Its Convergence Analysis—0
Sim-to-Real Transfer of Robot Learning with Variable Length Inputs—0
Transfer and Multi-Task Learning for Noun-Noun Compound InterpretationCode0
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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