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 8901–8950 of 10307 papers

TitleStatusHype
Utilizing Deep Learning Towards Multi-modal Bio-sensing and Vision-based Affective Computing—0
Active Multitask Learning with Committees—0
System Demo for Transfer Learning from Vision to Language using Domain Specific CNN Accelerator for On-Device NLP Applications—0
Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classificationCode0
Enabling Continual Learning in Neural Networks with Meta Learning—0
SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models—0
Improving Relevance Prediction with Transfer Learning in Large-scale Retrieval Systems—0
Learning Visually Consistent Label Embeddings for Zero-Shot Learning—0
Domain Adaptive Transfer Learning for Fault Diagnosis—0
Learning What and Where to TransferCode0
Transferable Clean-Label Poisoning Attacks on Deep Neural NetsCode0
Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared VocabulariesCode0
A Brief Survey of Multilingual Neural Machine Translation—0
Transfer Learning for Scientific Data Chain Extraction in Small Chemical Corpus with BERT-CRF Model—0
Data augmentation in microscopic images for material data mining—0
Deep Zero-Shot Learning for Scene Sketch—0
A logical-based corpus for cross-lingual evaluationCode0
Anomaly Detection in Images—0
SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models—0
Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs—0
An Empirical Evaluation of Adversarial Robustness under Transfer Learning—0
Transferable Knowledge for Low-cost Decision Making in Cloud Environments—0
Tuned Inception V3 for Recognizing States of Cooking Ingredients—0
On Transfer Learning For Chatter Detection in Turning Using Wavelet Packet Transform and Empirical Mode DecompositionCode0
Large-scale weakly-supervised pre-training for video action recognitionCode0
From Video Game to Real Robot: The Transfer between Action SpacesCode0
An Information-Theoretic Metric of Transferability for Task Transfer LearningCode0
BIGSAGE: unsupervised inductive representation learning of graph via bi-attended sampling and global-biased aggregating—0
Cross-Task Knowledge Transfer for Visually-Grounded Navigation—0
PCNN: Environment Adaptive Model Without Finetuning—0
In Your Pace: Learning the Right Example at the Right Time—0
Stacking for Transfer Learning—0
K For The Price Of 1: Parameter Efficient Multi-task And Transfer Learning—0
FEED: Feature-level Ensemble Effect for knowledge Distillation—0
Attentive Task-Agnostic Meta-Learning for Few-Shot Text Classification—0
Transferring SLU Models in Novel Domains—0
To believe or not to believe: Validating explanation fidelity for dynamic malware analysis—0
Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration—0
Deep Transfer Learning for Few-Shot SAR Image Classification—0
Coevo: a collaborative design platform with artificial agents—0
DAC: The Double Actor-Critic Architecture for Learning OptionsCode0
Curriculum Learning in Deep Neural Networks for Financial Forecasting—0
SEALion: a Framework for Neural Network Inference on Encrypted Data—0
Solo or Ensemble? Choosing a CNN Architecture for Melanoma ClassificationCode0
Copy mechanism and tailored training for character-based data-to-text generationCode0
Attention-based Transfer Learning for Brain-computer Interface—0
Scene Graph Prediction with Limited LabelsCode0
Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning—0
Lung Nodule Classification using Deep Local-Global NetworksCode0
SocialIQA: Commonsense Reasoning about Social InteractionsCode0
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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