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 9301–9350 of 10307 papers

TitleStatusHype
Reuse and Adaptation for Entity Resolution through Transfer Learning—0
Using Multi-task and Transfer Learning to Solve Working Memory Tasks—0
Transfer Value or Policy? A Value-centric Framework Towards Transferrable Continuous Reinforcement Learning—0
Transferrable End-to-End Learning for Protein Interface Prediction—0
Learning Physics Priors for Deep Reinforcement Learing—0
Measuring Density and Similarity of Task Relevant Information in Neural Representations—0
Zero-Resource Multilingual Model Transfer: Learning What to Share—0
Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards—0
Weakly-Supervised Localization and Classification of Proximal Femur Fractures—0
An analytic theory of generalization dynamics and transfer learning in deep linear networks—0
Developmental Bayesian Optimization of Black-Box with Visual Similarity-Based Transfer Learning—0
Deep Transfer Learning of Pick Points on Fabric for Robot Bed-MakingCode0
Language Modeling Teaches You More Syntax than Translation Does: Lessons Learned Through Auxiliary Task Analysis—0
Non-native children speech recognition through transfer learning—0
Segmentation of Skin Lesions and their Attributes Using Multi-Scale Convolutional Neural Networks and Domain Specific Augmentations—0
On Reinforcement Learning for Full-length Game of StarCraft—0
Mind Your Language: Abuse and Offense Detection for Code-Switched Languages—0
Domain Adaptation for Robot Predictive Maintenance Systems—0
DT-LET: Deep Transfer Learning by Exploring where to Transfer—0
Global Weighted Average Pooling Bridges Pixel-level Localization and Image-level Classification—0
A Meta-Learning Approach for Custom Model Training—0
Target Transfer Q-Learning and Its Convergence Analysis—0
Sim-to-Real Transfer of Robot Learning with Variable Length Inputs—0
Transfer and Multi-Task Learning for Noun-Noun Compound InterpretationCode0
Language Identification with Deep Bottleneck Features—0
Adversarial Imitation via Variational Inverse Reinforcement Learning—0
Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks—0
Revisit Multinomial Logistic Regression in Deep Learning: Data Dependent Model Initialization for Image Recognition—0
Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation for Sim-to-Real Domain Adaptation—0
Inspiration Learning through Preferences—0
Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion RecognitionCode0
Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics—0
LSTM knowledge transfer for HRV-based sleep staging—0
Combined Reinforcement Learning via Abstract RepresentationsCode0
Ensemble of Convolutional Neural Networks for Automatic Grading of Diabetic Retinopathy and Macular Edema—0
Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation—0
Binary Classification of Alzheimer Disease using sMRI Imaging modality and Deep Learning—0
Generic Probabilistic Interactive Situation Recognition and Prediction: From Virtual to Real—0
Instance-based Deep Transfer Learning—0
A Deeper Look at 3D Shape Classifiers—0
Driving Experience Transfer Method for End-to-End Control of Self-Driving Cars—0
Five lessons from building a deep neural network recommender—0
Parameter Transfer Extreme Learning Machine based on Projective ModelCode0
NTUA-SLP at IEST 2018: Ensemble of Neural Transfer Methods for Implicit Emotion ClassificationCode0
Trivial Transfer Learning for Low-Resource Neural Machine Translation—0
Zero-shot User Intent Detection via Capsule Neural NetworksCode0
On the Adaptability of Unsupervised CNN-Based Deformable Image Registration to Unseen Image Domains—0
Scenes-Objects-Actions: A Multi-Task, Multi-Label Video Dataset—0
Deep Multi-Task Learning to Recognise Subtle Facial Expressions of Mental States—0
Learning Single-View 3D Reconstruction with Limited Pose SupervisionCode0
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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