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 8751–8775 of 10307 papers

TitleStatusHype
Attentive Multi-Task Deep Reinforcement LearningCode0
A Methodology for Controlling the Emotional Expressiveness in Synthetic Speech -- a Deep Learning approach—0
Graph-based Knowledge Distillation by Multi-head Attention NetworkCode0
Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation StudyCode0
Sim2real transfer learning for 3D human pose estimation: motion to the rescue—0
Transfer learning enhanced physics informed neural network for phase-field modeling of fracture—0
Measuring the Data Efficiency of Deep Learning Methods—0
A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer LearningCode0
Rethinking Continual Learning for Autonomous Agents and Robots—0
Low-Rank Subspace Override for Unsupervised Domain AdaptationCode0
Applying Transfer Learning To Deep Learned Models For EEG Analysis—0
Deep Transfer Learning For Whole-Brain fMRI Analyses—0
Celebrity ProfilingCode0
A Minimax Game for Instance based Selective Transfer Learning—0
Learning Transferable Feature Representations Using Neural Networks—0
On mechanisms for transfer using landmark value functions in multi-task lifelong reinforcement learning—0
Large-Scale Transfer Learning for Natural Language GenerationCode0
Dynamically Composing Domain-Data Selection with Clean-Data Selection by ``Co-Curricular Learning'' for Neural Machine Translation—0
Claim Extraction in Biomedical Publications using Deep Discourse Model and Transfer LearningCode0
Soft Representation Learning for Sparse Transfer—0
Cross-Domain NER using Cross-Domain Language ModelingCode0
Hierarchical Transfer Learning for Multi-label Text Classification—0
Exploration de l'apprentissage par transfert pour l'analyse de textes des r\'eseaux sociaux (Exploring neural transfer learning for social media text analysis )—0
Convolutional Neural Networks for Financial Text Regression—0
Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings—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