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 9901–9950 of 10307 papers

TitleStatusHype
Zero-Shot Transfer Learning for Event ExtractionCode0
Multilingual Hierarchical Attention Networks for Document ClassificationCode0
Discriminatory Transfer—0
Hidden Layers in Perceptual Learning—0
Attentional Push: A Deep Convolutional Network for Augmenting Image Salience With Shared Attention Modeling in Social Scenes—0
MuCaLe-Net: Multi Categorical-Level Networks to Generate More Discriminating Features—0
Matrix Tri-Factorization With Manifold Regularizations for Zero-Shot Learning—0
Fine-Tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally—0
A Gift From Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning—0
AGA: Attribute-Guided AugmentationCode0
Learning bilingual word embeddings with (almost) no bilingual data—0
Active Sentiment Domain Adaptation—0
SMC Faster R-CNN: Toward a scene-specialized multi-object detector—0
Learning to Learn: Meta-Critic Networks for Sample Efficient Learning—0
What's Mine is Yours: Pretrained CNNs for Limited Training Sonar ATR—0
Two-Stage Synthesis Networks for Transfer Learning in Machine ComprehensionCode0
Deep Transfer Learning: A new deep learning glitch classification method for advanced LIGO—0
Deep Hashing Network for Unsupervised Domain AdaptationCode1
Object Detection Using Deep CNNs Trained on Synthetic Images—0
Robust and Efficient Transfer Learning with Hidden-Parameter Markov Decision ProcessesCode0
Bayesian Joint Modelling for Object Localisation in Weakly Labelled Images—0
Using Transfer Learning for Image-Based Cassava Disease Detection—0
Knowledge Transfer for Out-of-Knowledge-Base Entities: A Graph Neural Network ApproachCode0
Consensus-Based Transfer Linear Support Vector Machines for Decentralized Multi-Task Multi-Agent Learning—0
Provable benefits of representation learning—0
Transfer Learning for Neural Semantic Parsing—0
Neural Domain Adaptation for Biomedical Question AnsweringCode0
Progressive Neural Networks for Transfer Learning in Emotion RecognitionCode0
MirBot: A collaborative object recognition system for smartphones using convolutional neural networks—0
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning—0
Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog ModelCode0
Deep-Learning Convolutional Neural Networks for scattered shrub detection with Google Earth Imagery—0
Concept Transfer Learning for Adaptive Language Understanding—0
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?—0
r-BTN: Cross-domain Face Composite and Synthesis from Limited Facial Patches—0
Krylov Subspace Recycling for Fast Iterative Least-Squares in Machine Learning—0
Transfer Learning for Speech Recognition on a BudgetCode0
Joint auto-encoders: a flexible multi-task learning framework—0
Lifelong Generative ModelingCode0
Zero-Shot Learning with Generative Latent Prototype Model—0
Deep image representations using caption generatorsCode0
Robust Data Geometric Structure Aligned Close yet Discriminative Domain Adaptation—0
Ridesourcing Car Detection by Transfer Learning—0
An Out-of-the-box Full-network Embedding for Convolutional Neural Networks—0
Effective Representations of Clinical Notes—0
Transfer Learning for Named-Entity Recognition with Neural Networks—0
WebVision Challenge: Visual Learning and Understanding With Web Data—0
Single Image Action Recognition by Predicting Space-Time Saliency—0
Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition: A Problem-Oriented Perspective—0
Supervised Learning of Universal Sentence Representations from Natural Language Inference DataCode1
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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