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 9251–9300 of 10307 papers

TitleStatusHype
Efficient Neural Network Compression via Transfer Learning for Industrial Optical Inspection—0
A neural network to classify metaphorical violence on cable news—0
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New ExperimentsCode0
Domain-Invariant Projection Learning for Zero-Shot Recognition—0
Transfer Learning versus Multi-agent Learning regarding Distributed Decision-Making in Highway Traffic—0
KTAN: Knowledge Transfer Adversarial Network—0
Multi-Task Deep Learning for Legal Document Translation, Summarization and Multi-Label Classification—0
Feature Representation Analysis of Deep Convolutional Neural Network using Two-stage Feature Transfer -An Application for Diffuse Lung Disease Classification-—0
Stop Illegal Comments: A Multi-Task Deep Learning Approach—0
Deep Transfer Reinforcement Learning for Text SummarizationCode0
Named-Entity Linking Using Deep Learning For Legal Documents: A Transfer Learning Approach—0
Theoretical Guarantees of Transfer Learning—0
An Empirical Study on Crosslingual Transfer in Probabilistic Topic Models—0
Cats or CAT scans: transfer learning from natural or medical image source datasets?Code0
Policy Transfer with Strategy OptimizationCode0
Virtual Battery Parameter Identification using Transfer Learning based Stacked Autoencoder—0
Bird Species Classification using Transfer Learning with Multistage TrainingCode0
A Distributed Reinforcement Learning Solution With Knowledge Transfer Capability for A Bike Rebalancing Problem—0
Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel AttacksCode0
Multi-Source Cross-Lingual Model Transfer: Learning What to ShareCode0
Cross-Subject Transfer Learning Improves the Practicality of Real-World Applications of Brain-Computer Interfaces—0
Survival prediction using ensemble tumor segmentation and transfer learningCode0
Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling—0
Dynamics and Reachability of Learning Tasks—0
Transfer Learning via Unsupervised Task Discovery for Visual Question AnsweringCode0
Fast Approach to Build an Automatic Sentiment Annotator for Legal Domain using Transfer Learning—0
Target Aware Network Adaptation for Efficient Representation Learning—0
The JHU/KyotoU Speech Translation System for IWSLT 2018—0
CUNI Basque-to-English Submission in IWSLT18—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
Phonological Features for Morphological Inflection—0
Hunter NMT System for WMT18 Biomedical Translation Task: Transfer Learning in Neural Machine Translation—0
Language Independent Sentiment Analysis with Sentiment-Specific Word Embeddings—0
Exploring Named Entity Recognition As an Auxiliary Task for Slot Filling in Conversational Language Understanding—0
Learning Representations for Detecting Abusive Language—0
Syntax-based Transfer Learning for the Task of Biomedical Relation Extraction—0
The SLT-Interactions Parsing System at the CoNLL 2018 Shared Task—0
A Simple yet Effective Joint Training Method for Cross-Lingual Universal Dependency Parsing—0
Learning Text Representations for 500K Classification Tasks on Named Entity DisambiguationCode0
Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention MechanismCode0
Similarity-Based Reconstruction Loss for Meaning Representation—0
Learning Unsupervised Word Translations Without Adversaries—0
An Interpretable Neural Network with Topical Information for Relevant Emotion Ranking—0
Continuous Word Embedding Fusion via Spectral Decomposition—0
Improving Multi-label Emotion Classification via Sentiment Classification with Dual Attention Transfer Network—0
Transfer and Multi-Task Learning for Noun--Noun Compound Interpretation—0
Bayesian Transfer Reinforcement Learning with Prior Knowledge Rules—0
Posture recognition using an RGB-D camera : exploring 3D body modeling and deep learning approaches—0
Learning Robust, Transferable Sentence Representations for Text Classification—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