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 8001–8050 of 10307 papers

TitleStatusHype
Adaptive Invariance for Molecule Property Prediction—0
DoQA -- Accessing Domain-Specific FAQs via Conversational QA—0
3D Printed Brain-Controlled Robot-Arm Prosthetic via Embedded Deep Learning from sEMG Sensors—0
How Can We Accelerate Progress Towards Human-like Linguistic Generalization?—0
A Novel GDP Prediction Technique based on Transfer Learning using CO2 Emission Dataset—0
Understanding and Improving Information Transfer in Multi-Task Learning—0
Towards a Multi-Dataset for Complex Emotions Learning Based on Deep Neural Networks—0
Transfer Learning for Less-Resourced Semitic Languages Speech Recognition: the Case of Amharic—0
Transfer learning applied to text classification in Spanish radiological reports—0
Being Generous with Sub-Words towards Small NMT Children—0
Improving the Language Model for Low-Resource ASR with Online Text Corpora—0
Macsen: A Voice Assistant for Speakers of a Lesser Resourced LanguageCode0
Improving Sentence Boundary Detection for Spoken Language Transcripts—0
Cross-lingual Structure Transfer for Zero-resource Event Extraction—0
Offensive Video Detection: Dataset and Baseline Results—0
Aggression Identification in Social Media: a Transfer Learning Based Approach—0
An Evaluation of Progressive Neural Networksfor Transfer Learning in Natural Language Processing—0
Domain Adapted Distant Supervision for Pedagogically Motivated Relation Extraction—0
Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?—0
Adapting BERT to Implicit Discourse Relation Classification with a Focus on Discourse Connectives—0
Headword-Oriented Entity Linking: A Special Entity Linking Task with Dataset and Baseline—0
Optimizing Annotation Effort Using Active Learning Strategies: A Sentiment Analysis Case Study in Persian—0
Sentiment Analysis for Hinglish Code-mixed Tweets by means of Cross-lingual Word Embeddings—0
Pay Attention to Features, Transfer Learn Faster CNNs—0
Can a powerful neural network be a teacher for a weaker neural network?Code0
Do Neural Ranking Models Intensify Gender Bias?Code0
Affect inTweets: A Transfer Learning Approach—0
Irony Detection in Persian Language: A Transfer Learning Approach Using Emoji Prediction—0
Multitask Learning for Arabic Offensive Language and Hate-Speech Detection—0
Supervised Hypernymy Detection in Spanish through Order Embeddings—0
SAJA at TRAC 2020 Shared Task: Transfer Learning for Aggressive Identification with XGBoost—0
Evaluating and Improving Child-Directed Automatic Speech Recognition—0
Adaptation of Deep Bidirectional Transformers for Afrikaans Language—0
Learning to Ask Screening Questions for Job Postings—0
A Deep Convolutional Neural Network for COVID-19 Detection Using Chest X-RaysCode0
Generative Adversarial Data Programming—0
GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning—0
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minimaCode0
Investigating Transferability in Pretrained Language ModelsCode0
Don't Use English Dev: On the Zero-Shot Cross-Lingual Evaluation of Contextual Embeddings—0
Deepfake Video Forensics based on Transfer Learning—0
Deep Transfer Learning For Plant Center Localization—0
Transfer Learning for Thermal Comfort Prediction in Multiple Cities—0
Video Contents Understanding using Deep Neural Networks—0
Heterogeneous Representation Learning: A Review—0
Meta-Learning for Few-Shot Land Cover Classification—0
Extending Multilingual BERT to Low-Resource Languages—0
UXLA: A Robust Unsupervised Data Augmentation Framework for Zero-Resource Cross-Lingual NLP—0
A Cognition-Affect Integrated Model of Emotion—0
A scoping review of transfer learning research on medical image analysis using ImageNet—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