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 4551–4600 of 10307 papers

TitleStatusHype
LingJing at SemEval-2022 Task 3: Applying DeBERTa to Lexical-level Presupposed Relation Taxonomy with Knowledge TransferCode0
Knowledge Transfer between Structured and Unstructured Sources for Complex Question Answering—0
LastResort at SemEval-2022 Task 5: Towards Misogyny Identification using Visual Linguistic Model Ensembles And Task-Specific Pretraining—0
Harmless Transfer Learning for Item Embeddings—0
Dynamic Gazetteer Integration in Multilingual Models for Cross-Lingual and Cross-Domain Named Entity Recognition—0
Pruning Adatperfusion with Lottery Ticket Hypothesis—0
Language Models for Code-switch Detection of te reo Māori and English in a Low-resource Setting—0
Team Innovators at SemEval-2022 for Task 8: Multi-Task Training with Hyperpartisan and Semantic Relation for Multi-Lingual News Article Similarity—0
Transfer Learning and Masked Generation for Answer Verbalization—0
The Specificity and Helpfulness of Peer-to-Peer Feedback in Higher Education—0
Geographical Distance Is The New Hyperparameter: A Case Study Of Finding The Optimal Pre-trained Language For English-isiZulu Machine Translation.—0
Are You Really Okay? A Transfer Learning-based Approach for Identification of Underlying Mental Illnesses—0
The Importance of the Instantaneous Phase for classification using Convolutional Neural Networks—0
Training Novices: The Role of Human-AI Collaboration and Knowledge Transfer—0
COVID-19 Detection Using Transfer Learning Approach from Computed Tomography ImagesCode0
Neural Networks can Learn Representations with Gradient Descent—0
Transfer Learning with Deep Tabular ModelsCode1
Efficient Entity Candidate Generation for Low-Resource LanguagesCode0
Spatial Transformer Network with Transfer Learning for Small-scale Fine-grained Skeleton-based Tai Chi Action Recognition—0
On-Device Training Under 256KB MemoryCode2
No Reason for No Supervision: Improved Generalization in Supervised ModelsCode1
GERNERMED++: Transfer Learning in German Medical NLPCode0
Learning Gait Representation from Massive Unlabelled Walking Videos: A Benchmark—0
ECG Heartbeat classification using deep transfer learning with Convolutional Neural Network and STFT technique—0
Few-Shot Cross-Lingual TTS Using Transferable Phoneme Embedding—0
A View Independent Classification Framework for Yoga Postures—0
ST-Adapter: Parameter-Efficient Image-to-Video Transfer LearningCode1
Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning—0
Discovering Salient Neurons in Deep NLP Models—0
Interpretable Acoustic Representation Learning on Breathing and Speech Signals for COVID-19 DetectionCode0
Automatic identification of segmentation errors for radiotherapy using geometric learningCode1
Transfer Learning via Test-Time Neural Networks Aggregation—0
Transfer learning for ensembles: reducing computation time and keeping the diversity—0
Predicting the Need for Blood Transfusion in Intensive Care Units with Reinforcement Learning—0
Defense against adversarial attacks on deep convolutional neural networks through nonlocal denoising—0
Asymmetric Transfer Hashing with Adaptive Bipartite Graph Learning—0
Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI—0
RAPid-Learn: A Framework for Learning to Recover for Handling Novelties in Open-World EnvironmentsCode0
Gated Domain Units for Multi-source Domain GeneralizationCode0
An Intensity and Phase Stacked Analysis of Phase-OTDR System using Deep Transfer Learning and Recurrent Neural Networks—0
Aggregated Multi-output Gaussian Processes with Knowledge Transfer Across Domains—0
Automatic extraction of coronary arteries using deep learning in invasive coronary angiograms—0
Mutual Information-guided Knowledge Transfer for Novel Class Discovery—0
Imitation Learning for Generalizable Self-driving Policy with Sim-to-real TransferCode0
Optimistic Linear Support and Successor Features as a Basis for Optimal Policy TransferCode0
Template-based Approach to Zero-shot Intent Recognition—0
A Transfer-Learning Based Ensemble Architecture for ECG Signal Classification—0
An Efficient Industrial Federated Learning Framework for AIoT: A Face Recognition Application—0
Building an Endangered Language Resource in the Classroom: Universal Dependencies for KakataiboCode0
SFace: Privacy-friendly and Accurate Face Recognition using Synthetic DataCode1
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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