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 6051–6100 of 10307 papers

TitleStatusHype
AutoTransfer: Subject Transfer Learning with Censored Representations on Biosignals Data—0
Human-vehicle Cooperative Visual Perception for Autonomous Driving under Complex Road and Traffic Scenarios—0
An Empirical Study on Transfer Learning for Privilege Review—0
Predicting Shallow Water Dynamics using Echo-State Networks with Transfer Learning—0
Monitoring crop phenology with street-level imagery using computer vision—0
MissMarple : A Novel Socio-inspired Feature-transfer Learning Deep Network for Image Splicing Detection—0
Cross-Domain Generalization and Knowledge Transfer in Transformers Trained on Legal Data—0
A Comparative Analysis of Machine Learning Approaches for Automated Face Mask Detection During COVID-19Code0
Chimpanzee voice prints? Insights from transfer learning experiments from human voices—0
One System to Rule them All: a Universal Intent Recognition System for Customer Service Chatbots—0
Confidence-Aware Subject-to-Subject Transfer Learning for Brain-Computer Interface—0
Fine-Tuning Large Neural Language Models for Biomedical Natural Language Processing—0
Know Thy Strengths: Comprehensive Dialogue State Tracking DiagnosticsCode0
Epigenomic language models powered by Cerebras—0
On the Use of External Data for Spoken Named Entity RecognitionCode0
Maximum Bayes Smatch Ensemble Distillation for AMR ParsingCode0
Long-tail Recognition via Compositional Knowledge Transfer—0
Large Language Models are not Models of Natural Language: they are Corpus Models—0
Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant SetupCode0
Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement—0
Technical Language Supervision for Intelligent Fault Diagnosis in Process Industry—0
Automated tabulation of clinical trial results: A joint entity and relation extraction approach with transformer-based language representationsCode0
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical recordsCode0
Analysis and Prediction of NLP Models Via Task EmbeddingsCode0
KartalOl: Transfer learning using deep neural network for iris segmentation and localization: New dataset for iris segmentationCode0
Transfer learning using deep neural networks for Ear Presentation Attack Detection: New Database for PADCode0
Best Arm Identification under Additive Transfer Bandits—0
Pareto Domain AdaptationCode0
ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake ImagesCode0
Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks—0
CSG0: Continual Urban Scene Generation with Zero Forgetting—0
Flexible Option LearningCode0
Prototypical Model with Novel Information-theoretic Loss Function for Generalized Zero Shot Learning—0
Transfer learning to improve streamflow forecasts in data sparse regions—0
CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks—0
Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning—0
Overcome Anterograde Forgetting with Cycled Memory Networks—0
Fast Data-Driven Adaptation of Radar Detection via Meta-Learning—0
Learning Curves for Continual Learning in Neural Networks: Self-Knowledge Transfer and Forgetting—0
Divergent representations of ethological visual inputs emerge from supervised, unsupervised, and reinforcement learning—0
Deep Transfer Learning: A Novel Collaborative Learning Model for Cyberattack Detection Systems in IoT Networks—0
Transfer Learning in Conversational Analysis through Reusing Preprocessing Data as Supervisors—0
Unsupervised Representation Transfer for Small Networks: I Believe I Can Distill On-the-Fly—0
Total-Body Low-Dose CT Image Denoising using Prior Knowledge Transfer Technique with Contrastive Regularization Mechanism—0
Variational Continual Bayesian Meta-Learning—0
以遷移學習改善深度神經網路模型於中文歌詞情緒辨識 (Using Transfer Learning to Improve Deep Neural Networks for Lyrics Emotion Recognition in Chinese)—0
Wiki to Automotive: Understanding the Distribution Shift and its impact on Named Entity Recognition—0
Meta Arcade: A Configurable Environment Suite for Meta-Learning—0
On the Transferability of Massively Multilingual Pretrained Models in the Pretext of the Indo-Aryan and Tibeto-Burman Languages—0
Low-Fidelity Video Encoder Optimization for Temporal Action Localization—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