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 9501–9550 of 10307 papers

TitleStatusHype
Multi-Module Recurrent Neural Networks with Transfer Learning—0
Toward Data-Driven Tutorial Question Answering with Deep Learning Conversational Models—0
EPUTION at SemEval-2018 Task 2: Emoji Prediction with User Adaption—0
psyML at SemEval-2018 Task 1: Transfer Learning for Sentiment and Emotion Analysis—0
SNU\_IDS at SemEval-2018 Task 12: Sentence Encoder with Contextualized Vectors for Argument Reasoning ComprehensionCode0
GIST at SemEval-2018 Task 12: A network transferring inference knowledge to Argument Reasoning Comprehension taskCode0
Predicting Foreign Language Usage from English-Only Social Media Posts—0
Epita at SemEval-2018 Task 1: Sentiment Analysis Using Transfer Learning Approach—0
FOI DSS at SemEval-2018 Task 1: Combining LSTM States, Embeddings, and Lexical Features for Affect Analysis—0
ELISA-EDL: A Cross-lingual Entity Extraction, Linking and Localization System—0
Benchmarks and models for entity-oriented polarity detection—0
Improve Neural Entity Recognition via Multi-Task Data Selection and Constrained Decoding—0
Cross-Domain Review Helpfulness Prediction Based on Convolutional Neural Networks with Auxiliary Domain Discriminators—0
AffecThor at SemEval-2018 Task 1: A cross-linguistic approach to sentiment intensity quantification in tweets—0
DMCB at SemEval-2018 Task 1: Transfer Learning of Sentiment Classification Using Group LSTM for Emotion Intensity prediction—0
The Word Analogy Testing Caveat—0
Domain Adaptation for MRI Organ Segmentation using Reverse Classification AccuracyCode0
Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image TranslationCode0
Multi-Label Transfer Learning for Multi-Relational Semantic Similarity—0
Hyperspectral Imaging Technology and Transfer Learning Utilized in Identification Haploid Maize Seeds—0
Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition—0
Transductive Label Augmentation for Improved Deep Network Learning—0
Meta Transfer Learning for Facial Emotion Recognition—0
Using transfer learning to detect galaxy mergers—0
Language Modeling Teaches You More than Translation Does: Lessons Learned Through Auxiliary Task Analysis—0
SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy LabelsCode0
Meta-Learning for Low-Resource Neural Machine Translation—0
Do Better ImageNet Models Transfer Better?—0
Transfer Learning for Illustration ClassificationCode0
ASR-based Features for Emotion Recognition: A Transfer Learning Approach—0
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer LearningCode0
Accelerated Bayesian Optimization throughWeight-Prior Tuning—0
Comparison of Semantic Segmentation Approaches for Horizon/Sky Line Detection—0
Morphological analysis using a sequence decoderCode0
Object Localization with a Weakly Supervised CapsNet—0
Neural Architecture Search using Deep Neural Networks and Monte Carlo Tree SearchCode1
SNU_IDS at SemEval-2018 Task 12: Sentence Encoder with Contextualized Vectors for Argument Reasoning ComprehensionCode0
Cross-domain attribute representation based on convolutional neural network—0
Optimization of Transfer Learning for Sign Language Recognition Targeting Mobile Platform—0
Learning Time-Sensitive Strategies in Space FortressCode0
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature VectorsCode0
General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learningCode0
Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration—0
Exploring object-centric and scene-centric CNN features and their complementarity for human rights violations recognition in imagesCode0
Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge TransferCode0
Semi-Supervised Domain Adaptation with Representation Learning for Semantic Segmentation across Time—0
Transfer Learning from Adult to Children for Speech Recognition: Evaluation, Analysis and Recommendations—0
DocFace: Matching ID Document Photos to SelfiesCode0
Image Based Fashion Product Recommendation with Deep Learning—0
Transfer Learning of Artist Group Factors to Musical Genre ClassificationCode0
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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