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 6101–6150 of 10307 papers

TitleStatusHype
A Lottery Ticket Hypothesis Framework for Low-Complexity Device-Robust Neural Acoustic Scene Classification—0
Learning Efficient Vision Transformers via Fine-Grained Manifold DistillationCode1
Learning from scarce information: using synthetic data to classify Roman fine ware pottery—0
Isotonic Data Augmentation for Knowledge Distillation—0
Disentangling Transfer and Interference in Multi-Domain Learning—0
Toward Drug-Target Interaction Prediction via Ensemble Modeling and Transfer Learning—0
Empirically Measuring Transfer Distance for System Design and Operation—0
Language Identification of Hindi-English tweets using code-mixed BERT—0
Memory Efficient Meta-Learning with Large ImagesCode1
Parasitic Egg Detection and Classification in Low-cost Microscopic Images using Transfer Learning—0
A Systems Theory of Transfer Learning—0
A Comparison between Named Entity Recognition Models in the Biomedical DomainCode0
Recent Neural Methods on Dialogue State Tracking for Task-Oriented Dialogue Systems: A Survey—0
A Primer on Pretrained Multilingual Language Models—0
Cross-Lingual Transfer Learning for Statistical Type Inference—0
Learning to See before Learning to Act: Visual Pre-training for Manipulation—0
Shared Data and Algorithms for Deep Learning in Fundamental PhysicsCode1
Deep Transfer Learning Baselines for Sentiment Analysis in RussianCode1
Inverse Design of Grating Couplers Using the Policy Gradient Method from Reinforcement Learning—0
Extraction of Key-frames of Endoscopic Videos by using Depth Information—0
Learning Bounds for Open-Set LearningCode1
CityNet: A Comprehensive Multi-Modal Urban Dataset for Advanced Research in Urban ComputingCode0
IMS' Systems for the IWSLT 2021 Low-Resource Speech Translation Task—0
When Video Classification Meets Incremental Classes—0
Zoo-Tuning: Adaptive Transfer from a Zoo of Models—0
Critically examining the Domain Generalizability of Facial Expression Recognition models—0
Knowledge Transfer by Discriminative Pre-training for Academic Performance Prediction—0
A Knowledge-Grounded Dialog System Based on Pre-Trained Language Models—0
Exploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images—0
Domain Adaptation Broad Learning System Based on Locally Linear Embedding—0
ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing ModalitiesCode1
PNet -- A Deep Learning Based Photometry and Astrometry Bayesian Framework—0
Time-Series Representation Learning via Temporal and Contextual ContrastingCode1
Saying the Unseen: Video Descriptions via Dialog AgentsCode0
An Automated Knowledge Mining and Document Classification System with Multi-model Transfer Learning—0
Power and Modulation Format Transfer Learning for Neural Network Equalizers in Coherent Optical Transmission Systems—0
Multilingual transfer of acoustic word embeddings improves when training on languages related to the target zero-resource languageCode0
Pre-training transformer-based framework on large-scale pediatric claims data for downstream population-specific tasks—0
Towards Exploiting Geometry and Time for Fast Off-Distribution Adaptation in Multi-Task Robot Learning—0
The Option Keyboard: Combining Skills in Reinforcement Learning—0
Gender Recognition in Informal and Formal Language Scenarios via Transfer Learning—0
Classifying Textual Data with Pre-trained Vision Models through Transfer Learning and Data TransformationsCode0
Neural Fashion Image Captioning : Accounting for Data DiversityCode1
Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual LearningCode0
Near-Optimal Linear Regression under Distribution Shift—0
Teacher Model Fingerprinting Attacks Against Transfer LearningCode1
Prompt Tuning or Fine-Tuning - Investigating Relational Knowledge in Pre-Trained Language ModelsCode0
Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of SeizuresCode0
On the importance of cross-task features for class-incremental learningCode0
GAIA: A Transfer Learning System of Object Detection that Fits Your NeedsCode1
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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