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 4251–4300 of 10307 papers

TitleStatusHype
GDA-HIN: A Generalized Domain Adaptive Model across Heterogeneous Information Networks—0
DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation—0
Amobee at IEST 2018: Transfer Learning from Language Models—0
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
Headword-Oriented Entity Linking: A Special Entity Linking Task with Dataset and Baseline—0
HelixADMET: a robust and endpoint extensible ADMET system incorporating self-supervised knowledge transfer—0
H-ensemble: An Information Theoretic Approach to Reliable Few-Shot Multi-Source-Free Transfer—0
DADNN: Multi-Scene CTR Prediction via Domain-Aware Deep Neural Network—0
DADIN: Domain Adversarial Deep Interest Network for Cross Domain Recommender Systems—0
DA-DETR: Domain Adaptive Detection Transformer with Information Fusion—0
A Unified Framework for Cross-Domain Recommendation—0
Adaptive Physics-informed Neural Networks: A Survey—0
Headache to Overstock? Promoting Long-tail Items through Debiased Product Bundling—0
A Unified Deep Transfer Learning Model for Accurate IoT Localization in Diverse Environments—0
DACB-Net: Dual Attention Guided Compact Bilinear Convolution Neural Network for Skin Disease Classification—0
A Unified Deep Learning Approach for Prediction of Parkinson's Disease—0
D3T-GAN: Data-Dependent Domain Transfer GANs for Few-shot Image Generation—0
10Sent: A Stable Sentiment Analysis Method Based on the Combination of Off-The-Shelf Approaches—0
CyFormer: Accurate State-of-Health Prediction of Lithium-Ion Batteries via Cyclic Attention—0
AUKT: Adaptive Uncertainty-Guided Knowledge Transfer with Conformal Prediction—0
Supervised domain adaptation for building extraction from off-nadir aerial images—0
AMMU : A Survey of Transformer-based Biomedical Pretrained Language Models—0
Have You Poisoned My Data? Defending Neural Networks against Data Poisoning—0
Head2Toe: Utilizing Intermediate Representations for Better OOD Generalization—0
Cyclegan Network for Sheet Metal Welding Drawing Translation—0
Hate Speech Detection and Racial Bias Mitigation in Social Media based on BERT model—0
Augmenting transferred representations for stock classification—0
CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation—0
Adaptive Part Learning for Fine-Grained Generalized Category Discovery: A Plug-and-Play Enhancement—0
HausaNLP at SemEval-2023 Task 10: Transfer Learning, Synthetic Data and Side-Information for Multi-Level Sexism Classification—0
Headless Horseman: Adversarial Attacks on Transfer Learning Models—0
CVAE-based Re-anchoring for Implicit Discourse Relation Classification—0
Augmenting Transfer Learning with Semantic Reasoning—0
AMLN: Adversarial-based Mutual Learning Network for Online Knowledge Distillation—0
Customizing General-Purpose Foundation Models for Medical Report Generation—0
Harnessing Transformers: A Leap Forward in Lung Cancer Image Detection—0
Customizing Contextualized Language Models forLegal Document Reviews—0
Customized Video QoE Estimation with Algorithm-Agnostic Transfer Learning—0
A Minimax Game for Instance based Selective Transfer Learning—0
Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning—0
Curriculum Learning in Deep Neural Networks for Financial Forecasting—0
Augmenting Offline RL with Unlabeled Data—0
Adaptive Multi-Source Causal Inference—0
Hashtag Healthcare: From Tweets to Mental Health Journals Using Deep Transfer Learning—0
CURO: Curriculum Learning for Relative Overgeneralization—0
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey—0
A microservice-based framework for exploring data selection in cross-building knowledge transfer—0
Augmenting Knowledge Distillation With Peer-To-Peer Mutual Learning For Model Compression—0
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks—0
AM Flow: Adapters for Temporal Processing in Action Recognition—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