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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9251–9300 of 10307 papers

TitleStatusHype
Language Modeling Teaches You More than Translation Does: Lessons Learned Through Auxiliary Syntactic Task Analysis—0
DERE: A Task and Domain-Independent Slot Filling Framework for Declarative Relation Extraction—0
An Analysis of Encoder Representations in Transformer-Based Machine Translation—0
Cogni-Net: Cognitive Feature Learning through Deep Visual PerceptionCode0
Cross-Lingual Argumentative Relation Identification: from English to PortugueseCode0
Cross-Lingual Transfer Learning for Multilingual Task Oriented Dialog—0
Don't forget, there is more than forgetting: new metrics for Continual Learning—0
Adaptive Transfer Learning in Deep Neural Networks: Wind Power Prediction using Knowledge Transfer from Region to Region and Between Different Task Domains—0
Gated Transfer Network for Transfer Learning—0
Semi-unsupervised Learning of Human Activity using Deep Generative ModelsCode0
Speaking style adaptation in Text-To-Speech synthesis using Sequence-to-sequence models with attention—0
Cross-Modal Distillation for RGB-Depth Person Re-Identification—0
Accumulating Knowledge for Lifelong Online Learning—0
Finding Answers from the Word of God: Domain Adaptation for Neural Networks in Biblical Question Answering—0
Transfer of Deep Reactive Policies for MDP PlanningCode0
Improving Document Binarization via Adversarial Noise-Texture AugmentationCode0
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning—0
Training neural audio classifiers with few dataCode0
Universal Language Model Fine-Tuning with Subword Tokenization for PolishCode0
Testing the Generalization Power of Neural Network Models Across NLI Benchmarks—0
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data—0
How transferable are features in convolutional neural network acoustic models across languages?—0
Boosting pathology detection in infants by deep transfer learning from adult speech—0
Mechanisms for Integrated Feature Normalization and Remaining Useful Life Estimation Using LSTMs Applied to Hard-Disks—0
Machine Learning Methods for Track Classification in the AT-TPCCode0
Cross-domain aspect extraction for sentiment analysis: a transductive learning approach—0
Efficient Neural Network Compression via Transfer Learning for Industrial Optical Inspection—0
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New ExperimentsCode0
A neural network to classify metaphorical violence on cable news—0
Domain-Invariant Projection Learning for Zero-Shot Recognition—0
Transfer Learning versus Multi-agent Learning regarding Distributed Decision-Making in Highway Traffic—0
KTAN: Knowledge Transfer Adversarial Network—0
Multi-Task Deep Learning for Legal Document Translation, Summarization and Multi-Label Classification—0
Feature Representation Analysis of Deep Convolutional Neural Network using Two-stage Feature Transfer -An Application for Diffuse Lung Disease Classification-—0
Deep Transfer Reinforcement Learning for Text SummarizationCode0
Stop Illegal Comments: A Multi-Task Deep Learning Approach—0
Named-Entity Linking Using Deep Learning For Legal Documents: A Transfer Learning Approach—0
Theoretical Guarantees of Transfer Learning—0
An Empirical Study on Crosslingual Transfer in Probabilistic Topic Models—0
Cats or CAT scans: transfer learning from natural or medical image source datasets?Code0
Policy Transfer with Strategy OptimizationCode0
Virtual Battery Parameter Identification using Transfer Learning based Stacked Autoencoder—0
Bird Species Classification using Transfer Learning with Multistage TrainingCode0
A Distributed Reinforcement Learning Solution With Knowledge Transfer Capability for A Bike Rebalancing Problem—0
Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel AttacksCode0
Multi-Source Cross-Lingual Model Transfer: Learning What to ShareCode0
Cross-Subject Transfer Learning Improves the Practicality of Real-World Applications of Brain-Computer Interfaces—0
Survival prediction using ensemble tumor segmentation and transfer learningCode0
Dynamics and Reachability of Learning Tasks—0
Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling—0
Show:102550
← PrevPage 186 of 207Next →
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