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 8301–8350 of 10307 papers

TitleStatusHype
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversionCode0
Research Frontiers in Transfer Learning -- a systematic and bibliometric review—0
Pruning by Explaining: A Novel Criterion for Deep Neural Network PruningCode0
Lightweight and Robust Representation of Economic Scales from Satellite ImageryCode0
Predicting the real-valued distances between residue pairs for proteins—0
KonVid-150k: A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild—0
Transfer learning in hybrid classical-quantum neural networksCode0
A Transferable Adaptive Domain Adversarial Neural Network for Virtual Reality Augmented EMG-Based Gesture RecognitionCode0
Automated Thalamic Nuclei Segmentation Using Multi-Planar Cascaded Convolutional Neural NetworksCode0
Iterative Dual Domain Adaptation for Neural Machine Translation—0
A Comparison of Architectures and Pretraining Methods for Contextualized Multilingual Word Embeddings—0
Multilingual is not enough: BERT for FinnishCode0
Targeted transfer learning to improve performance in small medical physics datasets—0
Meta-Learning Initializations for Image SegmentationCode0
Local Context Normalization: Revisiting Local NormalizationCode0
CLOSURE: Assessing Systematic Generalization of CLEVR ModelsCode0
Self-Driving Car Steering Angle Prediction Based on Image RecognitionCode0
Winning the Lottery with Continuous SparsificationCode0
Transfer Learning-Based Outdoor Position Recovery with Telco Data—0
Unsupervised Transfer Learning via BERT Neuron Selection—0
Decision Support System for Detection and Classification of Skin Cancer using CNN—0
Machine UnlearningCode0
Security of Deep Learning Methodologies: Challenges and Opportunities—0
Personalized Patent Claim Generation and Measurement—0
Kernel learning for visual perceptionCode0
DeepEthnic: Multi-Label Ethnic Classification from Face Images—0
How Does an Approximate Model Help in Reinforcement Learning?—0
300 GHz Radar Object Recognition based on Deep Neural Networks and Transfer Learning—0
ClusterFit: Improving Generalization of Visual RepresentationsCode0
Self-Supervised Learning of Video-Induced Visual Invariances—0
Transfer Learning from an Auxiliary Discriminative Task for Unsupervised Anomaly Detection—0
An Automated Deep Learning Approach for Bacterial Image Classification—0
AMUSED: A Multi-Stream Vector Representation Method for Use in Natural Dialogue—0
Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation—0
Degenerative Adversarial NeuroImage Nets for Brain Scan Simulations: Application in Ageing and Dementia—0
Unsupervised Inflection Generation Using Neural Language Modeling—0
TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLPCode0
Is Discriminator a Good Feature Extractor?—0
Implicit Priors for Knowledge Sharing in Bayesian Neural Networks—0
Applying Knowledge Transfer for Water Body Segmentation in Peru—0
Deep Neural Network Fingerprinting by Conferrable Adversarial ExamplesCode0
Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative TransferCode0
Syntactically Meaningful and Transferable Recursive Neural Networks for Aspect and Opinion Extraction—0
Better Transfer Learning with Inferred Successor Maps—0
Online Knowledge Distillation with Diverse PeersCode0
Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain ActivityCode0
Cross-Domain Recommendation via Preference Propagation GraphNet—0
Comparing Unsupervised Word Translation Methods Step by Step—0
Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks—0
Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer LearningCode0
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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