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 9451–9500 of 10307 papers

TitleStatusHype
Detecting Offensive Tweets in Hindi-English Code-Switched Language—0
BioAMA: Towards an End to End BioMedical Question Answering System—0
Unsupervised Random Walk Sentence Embeddings: A Strong but Simple Baseline—0
Two Methods for Domain Adaptation of Bilingual Tasks: Delightfully Simple and Broadly ApplicableCode0
Isomorphic Transfer of Syntactic Structures in Cross-Lingual NLP—0
A Helping Hand: Transfer Learning for Deep Sentiment Analysis—0
A Multi-lingual Multi-task Architecture for Low-resource Sequence LabelingCode0
Identifying Transferable Information Across Domains for Cross-domain Sentiment Classification—0
A Named Entity Recognition Shootout for German—0
Neural Networks Trained to Solve Differential Equations Learn General Representations—0
TextWorld: A Learning Environment for Text-based GamesCode0
A Multimodal Recommender System for Large-scale Assortment Generation in E-commerce—0
A probabilistic constrained clustering for transfer learning and image category discovery—0
Data Efficient Lithography Modeling with Transfer Learning and Active Data Selection—0
Estimating Bicycle Route Attractivity from Image Data—0
Cross-position Activity Recognition with Stratified Transfer Learning—0
Zeta Distribution and Transfer Learning Problem—0
Considerations for a PAP Smear Image Analysis System with CNN Features—0
Domain Adaptation for Infection Prediction from Symptoms Based on Data from Different Study Designs and Contexts—0
DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural NetworksCode0
The Natural Language Decathlon: Multitask Learning as Question AnsweringCode1
Uncertainty in Multitask Transfer Learning—0
Transfer Learning with Human Corneal Tissues: An Analysis of Optimal Cut-Off Layer—0
Towards an efficient deep learning model for musical onset detectionCode0
A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation—0
Large Scale Fine-Grained Categorization and Domain-Specific Transfer LearningCode1
Deformable Generator Networks: Unsupervised Disentanglement of Appearance and GeometryCode0
Action Learning for 3D Point Cloud Based Organ Segmentation—0
Motion Planning NetworksCode0
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable RepresentationsCode0
Transfer Learning for Context-Aware Question Matching in Information-seeking Conversations in E-commerce—0
Crowd-Powered Data Mining—0
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech SynthesisCode0
Learning Multilingual Topics from Incomparable Corpus—0
Context-Aware Policy Reuse—0
Learning Answer Embeddings for Visual Question Answering—0
Semi-supervised and Transfer learning approaches for low resource sentiment classification—0
Deep Image Compression via End-to-End LearningCode0
Attention Based Fully Convolutional Network for Speech Emotion RecognitionCode0
State Classification with CNN—0
DRCD: a Chinese Machine Reading Comprehension DatasetCode0
Psychological State in Text: A Limitation of Sentiment Analysis—0
Building Advanced Dialogue Managers for Goal-Oriented Dialogue Systems—0
Study and development of a Computer-Aided Diagnosis system for classification of chest x-ray images using convolutional neural networks pre-trained for ImageNet and data augmentation—0
TernausNetV2: Fully Convolutional Network for Instance SegmentationCode0
Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation—0
Coupled End-to-End Transfer Learning With Generalized Fisher Information—0
Bootstrapping the Performance of Webly Supervised Semantic SegmentationCode0
Good View Hunting: Learning Photo Composition From Dense View Pairs—0
CLEAR: Cumulative LEARning for One-Shot One-Class Image Recognition—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