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 9551–9600 of 10307 papers

TitleStatusHype
Fast and Scalable Expansion of Natural Language Understanding Functionality for Intelligent Agents—0
Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute Classification—0
Exploring the Limits of Weakly Supervised PretrainingCode0
Improving Machine Translation of Educational Content via Crowdsourcing—0
A Neural Network Model for Part-Of-Speech Tagging of Social Media Texts—0
KIT-Multi: A Translation-Oriented Multilingual Embedding Corpus—0
English-Basque Statistical and Neural Machine Translation—0
Simple Semantic Annotation and Situation Frames: Two Approaches to Basic Text Understanding in LORELEI—0
Tel(s)-Telle(s)-Signs: Highly Accurate Automatic Crosslingual Hypernym Discovery—0
Boosting Self-Supervised Learning via Knowledge Transfer—0
Sketch-a-Classifier: Sketch-based Photo Classifier Generation—0
Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial LossCode0
A Unified Framework for Domain Adaptation using Metric Learning on ManifoldsCode0
Deep learning approach to Fourier ptychographic microscopyCode0
Decoupling Dynamics and Reward for Transfer LearningCode0
Capsule networks for low-data transfer learning—0
Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph Distillation for Video Classification—0
Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification—0
On the effectiveness of task granularity for transfer learningCode1
Label-aware Double Transfer Learning for Cross-Specialty Medical Named Entity Recognition—0
Light-weight Head Pose Invariant Gaze Tracking—0
Deep cross-domain building extraction for selective depth estimation from oblique aerial imagery—0
Taskonomy: Disentangling Task Transfer LearningCode0
Towards Symbolic Reinforcement Learning with Common SenseCode0
Dropping Networks for Transfer Learning—0
A New Channel Boosted Convolutional Neural Network using Transfer Learning—0
Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion RateCode0
Multi-task Learning for Universal Sentence Embeddings: A Thorough Evaluation using Transfer and Auxiliary Tasks—0
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language UnderstandingCode1
CactusNets: Layer Applicability as a Metric for Transfer Learning—0
Direct Network Transfer: Transfer Learning of Sentence Embeddings for Semantic Similarity—0
Putting Question-Answering Systems into Practice: Transfer Learning for Efficient Domain Customization—0
Cell Selection with Deep Reinforcement Learning in Sparse Mobile Crowdsensing—0
Robustness via Deep Low-Rank Representations—0
NTUA-SLP at SemEval-2018 Task 1: Predicting Affective Content in Tweets with Deep Attentive RNNs and Transfer LearningCode0
CoNet: Collaborative Cross Networks for Cross-Domain RecommendationCode0
Deep Transfer Network with Joint Distribution Adaptation: A New Intelligent Fault Diagnosis Framework for Industry Application—0
Deep transfer learning in the assessment of the quality of protein modelsCode0
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis—0
Network Signatures from Image Representation of Adjacency Matrices: Deep/Transfer Learning for Subgraph Classification—0
Training a Binary Weight Object Detector by Knowledge Transfer for Autonomous Driving—0
Deep Embedding Kernel—0
Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation TaskCode0
RIPEx: Extracting malicious IP addresses from security forums using cross-forum learning—0
A Large-scale Attribute Dataset for Zero-shot LearningCode0
Plaque Classification in Coronary Arteries from IVOCT Images Using Convolutional Neural Networks and Transfer Learning—0
Personalized Dynamics Models for Adaptive Assistive Navigation Systems—0
Universal Successor Representations for Transfer Reinforcement Learning—0
Gotta Learn Fast: A New Benchmark for Generalization in RLCode0
Markerless tracking of user-defined features with deep learning—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