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 8751–8775 of 10307 papers

TitleStatusHype
Alioth: A Machine Learning Based Interference-Aware Performance Monitor for Multi-Tenancy Applications in Public CloudCode0
A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity RecognizersCode0
AlphaNet: Improving Long-Tail Classification By Combining ClassifiersCode0
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree SearchCode0
AMLNet: Adversarial Mutual Learning Neural Network for Non-AutoRegressive Multi-Horizon Time Series ForecastingCode0
AMNet: Memorability Estimation with AttentionCode0
Amortized Auto-Tuning: Cost-Efficient Bayesian Transfer Optimization for Hyperparameter RecommendationCode0
AMPL: A Data-Driven Modeling Pipeline for Drug DiscoveryCode0
A Multifactorial Optimization Paradigm for Linkage Tree Genetic AlgorithmCode0
A Multi-lingual Multi-task Architecture for Low-resource Sequence LabelingCode0
An AI-Powered VVPAT Counter for Elections in IndiaCode0
Analysing Cross-Lingual Transfer in Low-Resourced African Named Entity RecognitionCode0
Analysis and Prediction of NLP Models Via Task EmbeddingsCode0
Understanding the Transferability of Representations via Task-RelatednessCode0
Analyzing BERT Cross-lingual Transfer Capabilities in Continual Sequence LabelingCode0
Analyzing the Domain Shift Immunity of Deep Homography EstimationCode0
An Analysis of the Influence of Transfer Learning When Measuring the Tortuosity of Blood VesselsCode0
Anatomy-Aware Contrastive Representation Learning for Fetal UltrasoundCode0
Anatomy of Neural Language ModelsCode0
An Attention-based Representation Distillation Baseline for Multi-Label Continual LearningCode0
An Automatic Speech Recognition System for Bengali Language based on Wav2Vec2 and Transfer LearningCode0
An Autonomous Performance Testing Framework using Self-Adaptive Fuzzy Reinforcement LearningCode0
An easy zero-shot learning combination: Texture Sensitive Semantic Segmentation IceHrNet and Advanced Style Transfer Learning StrategyCode0
An Efficient and Explainable Transformer-Based Few-Shot Learning for Modeling Electricity Consumption Profiles Across Thousands of DomainsCode0
An Efficient Confidence Measure-Based Evaluation Metric for Breast Cancer Screening Using Bayesian Neural NetworksCode0
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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