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 3501–3550 of 10307 papers

TitleStatusHype
Credit Risk Meets Large Language Models: Building a Risk Indicator from Loan Descriptions in P2P Lending—0
A New Method for Vehicle Logo Recognition Based on Swin Transformer—0
Managing Household Waste through Transfer LearningCode0
Exploring the Transferability of a Foundation Model for Fundus Images: Application to Hypertensive Retinopathy—0
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—0
Asymptotic Midpoint Mixup for Margin Balancing and Moderate Broadening—0
Transfer Learning for the Prediction of Entity Modifiers in Clinical Text: Application to Opioid Use Disorder Case Detection—0
Hierarchical Continual Reinforcement Learning via Large Language Model—0
Transfer Learning With Densenet201 Architecture Model For Potato Leaf Disease Classification—0
Deep Learning Innovations in Diagnosing Diabetic Retinopathy: The Potential of Transfer Learning and the DiaCNN Model—0
A comparative study of zero-shot inference with large language models and supervised modeling in breast cancer pathology classification—0
StyleInject: Parameter Efficient Tuning of Text-to-Image Diffusion Models—0
Assessing the Portability of Parameter Matrices Trained by Parameter-Efficient Finetuning Methods—0
Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning—0
Towards Complementary Knowledge Distillation for Efficient Dense Image Prediction—0
Bayesian adaptive learning to latent variables via Variational Bayes and Maximum a Posteriori—0
SEDNet: Shallow Encoder-Decoder Network for Brain Tumor SegmentationCode0
Maximizing Data Efficiency for Cross-Lingual TTS Adaptation by Self-Supervised Representation Mixing and Embedding Initialization—0
Multi-Agent Based Transfer Learning for Data-Driven Air Traffic Applications—0
Feature Denoising Diffusion Model for Blind Image Quality Assessment—0
Transfer Learning for Nonparametric Regression: Non-asymptotic Minimax Analysis and Adaptive Procedure—0
Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal DataCode0
Cross-lingual Transfer Learning for Javanese Dependency Parsing—0
Contrastive Learning and Cycle Consistency-based Transductive Transfer Learning for Target Annotation—0
Transfer learning-assisted inverse modeling in nanophotonics based on mixture density networks—0
A Hybrid Approach of Transfer Learning and Physics-Informed Modeling: Improving Dissolved Oxygen Concentration Prediction in an Industrial Wastewater Treatment Plant—0
Progressive Distillation Based on Masked Generation Feature Method for Knowledge Graph CompletionCode0
Named Entity Recognition Under Domain Shift via Metric Learning for Life SciencesCode0
A Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding—0
Transfer Learning in Human Activity Recognition: A Survey—0
Boosting Few-Shot Segmentation via Instance-Aware Data Augmentation and Local Consensus Guided Cross Attention—0
Few-shot learning for COVID-19 Chest X-Ray Classification with Imbalanced Data: An Inter vs. Intra Domain StudyCode0
Cross-lingual Offensive Language Detection: A Systematic Review of Datasets, Transfer Approaches and ChallengesCode0
Generative Denoise Distillation: Simple Stochastic Noises Induce Efficient Knowledge Transfer for Dense PredictionCode0
Transferring Core Knowledge via Learngenes—0
Surface-Enhanced Raman Spectroscopy and Transfer Learning Toward Accurate Reconstruction of the Surgical Zone—0
Using i-vectors for subject-independent cross-session EEG transfer learning—0
N-Adaptive Ritz Method: A Neural Network Enriched Partition of Unity for Boundary Value Problems—0
Selecting Subsets of Source Data for Transfer Learning with Applications in Metal Additive Manufacturing—0
SAPT: A Shared Attention Framework for Parameter-Efficient Continual Learning of Large Language Models—0
Quantum Transfer Learning for Acceptability Judgements—0
Harnessing Machine Learning for Discerning AI-Generated Synthetic Images—0
Concrete Surface Crack Detection with Convolutional-based Deep Learning Models—0
Knowledge Distillation of Black-Box Large Language Models—0
Transcending Controlled Environments Assessing the Transferability of ASRRobust NLU Models to Real-World Applications—0
PersianMind: A Cross-Lingual Persian-English Large Language Model—0
Dynamic Indoor Fingerprinting Localization based on Few-Shot Meta-Learning with CSI Images—0
POMP: Probability-driven Meta-graph Prompter for LLMs in Low-resource Unsupervised Neural Machine Translation—0
Zero Resource Cross-Lingual Part Of Speech Tagging—0
VI-PANN: Harnessing Transfer Learning and Uncertainty-Aware Variational Inference for Improved Generalization in Audio Pattern RecognitionCode0
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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