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 4701–4750 of 10307 papers

TitleStatusHype
Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models—0
A Meta-Learning Approach to Population-Based Modelling of Structures—0
Detection and classification of vocal productions in large scale audio recordingsCode0
Graph schemas as abstractions for transfer learning, inference, and planning—0
Cliff-Learning—0
Intelligent Model Update Strategy for Sequential Recommendation—0
Label-efficient Time Series Representation Learning: A Review—0
Knowledge from Large-Scale Protein Contact Prediction Models Can Be Transferred to the Data-Scarce RNA Contact Prediction TaskCode0
Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning—0
LiT Tuned Models for Efficient Species DetectionCode0
Exploiting Graph Structured Cross-Domain Representation for Multi-Domain RecommendationCode0
Transfer Learning for Bayesian Optimization: A Survey—0
Vertical Federated Knowledge Transfer via Representation Distillation for Healthcare Collaboration Networks—0
Cross-center Early Sepsis Recognition by Medical Knowledge Guided Collaborative Learning for Data-scarce Hospitals—0
Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features—0
Text recognition on images using pre-trained CNN—0
Robust Knowledge Transfer in Tiered Reinforcement LearningCode0
Self-supervised learning-based cervical cytology for the triage of HPV-positive women in resource-limited settings and low-data regime—0
ChemVise: Maximizing Out-of-Distribution Chemical Detection with the Novel Application of Zero-Shot Learning—0
Toward Extremely Lightweight Distracted Driver Recognition With Distillation-Based Neural Architecture Search and Knowledge TransferCode0
A Dynamic Graph CNN with Cross-Representation Distillation for Event-Based Recognition—0
Neonatal Face and Facial Landmark Detection from Video Recordings—0
Investigating the role of model-based learning in exploration and transfer—0
Rover: An online Spark SQL tuning service via generalized transfer learning—0
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning ConventionsCode0
Adaptive Aggregation for Safety-Critical Control—0
Multi-organ segmentation: a progressive exploration of learning paradigms under scarce annotation—0
Automatic Sleep Stage Classification with Cross-modal Self-supervised Features from Deep Brain Signals—0
Transfer learning for process design with reinforcement learning—0
Novel Fundus Image Preprocessing for Retcam Images to Improve Deep Learning Classification of Retinopathy of Prematurity—0
COVID-19 Infection Analysis Framework using Novel Boosted CNNs and Radiological Images—0
ClueGAIN: Application of Transfer Learning On Generative Adversarial Imputation Nets (GAIN)—0
MOMA:Distill from Self-Supervised Teachers—0
TAP: The Attention Patch for Cross-Modal Knowledge Transfer from Unlabeled Modality—0
Interpretations of Domain Adaptations via Layer Variational AnalysisCode0
Efficient Domain Adaptation for Speech Foundation Models—0
SoK: A Systematic Evaluation of Backdoor Trigger Characteristics in Image Classification—0
Self-Supervised In-Domain Representation Learning for Remote Sensing Image Scene Classification—0
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature LearningCode0
Local transfer learning from one data space to another—0
An Empirical Study on the Transferability of Transformer Modules in Parameter-Efficient Fine-Tuning—0
Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets—0
Towards interpretable quantum machine learning via single-photon quantum walks—0
Dynamic Flows on Curved Space Generated by Labeled Data—0
Supporting Safety Analysis of Image-processing DNNs through Clustering-based Approaches—0
Learning Universal Policies via Text-Guided Video Generation—0
Transfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer Disease—0
PaCaNet: A Study on CycleGAN with Transfer Learning for Diversifying Fused Chinese Painting and Calligraphy—0
Knowledge Distillation Label Smoothing: Fact or Fallacy?—0
Supervised and Contrastive Self-Supervised In-Domain Representation Learning for Dense Prediction Problems in Remote Sensing—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