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 10251–10300 of 10307 papers

TitleStatusHype
Multi-Domain Sentiment Relevance Classification with Automatic Representation Learning—0
Transfer Learning across Networks for Collective Classification—0
Tensor Representation and Manifold Learning Methods for Remote Sensing Images—0
Adaptive Feature Ranking for Unsupervised Transfer Learning—0
Multi-View Priors for Learning Detectors from Sparse Viewpoint Data—0
Associative embeddings for large-scale knowledge transfer with self-assessment—0
Learning a Deep Compact Image Representation for Visual Tracking—0
Discriminative Transfer Learning with Tree-based Priors—0
Transfer Learning in a Transductive Setting—0
On the definition of a general learning system with user-defined operators—0
Clustering Markov Decision Processes For Continual Transfer—0
A PAC-Bayesian bound for Lifelong Learning—0
Use of Combined Topic Models in Unsupervised Domain Adaptation for Word Sense Disambiguation—0
Multi-Task Regularization with Covariance Dictionary for Linear Classifiers—0
Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties—0
Predicting Social Links for New Users across Aligned Heterogeneous Social Networks—0
DeCAF: A Deep Convolutional Activation Feature for Generic Visual RecognitionCode0
A Study on Bootstrapping Bilingual Vector Spaces from Non-Parallel Data (and Nothing Else)—0
Case Study of Model Adaptation: Transfer Learning and Online Learning—0
SuMT: A Framework of Summarization and MT—0
Sentiment Relevance—0
Embedding Semantic Similarity in Tree Kernels for Domain Adaptation of Relation Extraction—0
POMDP-based dialogue manager adaptation to extended domains—0
Hidden Markov tree models for semantic class induction—0
Transfer Learning Based Cross-lingual Knowledge Extraction for Wikipedia—0
Transfer Learning for Constituency-Based Grammars—0
Controlling the Precision-Recall Tradeoff in Differential Dependency Network Analysis—0
Bayesian Discovery of Multiple Bayesian Networks via Transfer Learning—0
Learning Fair RepresentationsCode0
Designing Category-Level Attributes for Discriminative Visual Recognition—0
Identifying Intention Posts in Discussion Forums—0
From N to N+1: Multiclass Transfer Incremental Learning—0
Zipfian corruptions for robust POS tagging—0
Transfer Learning for Content-Based Recommender Systems using Tree Matching—0
Inverse Density as an Inverse Problem: The Fredholm Equation Approach—0
The Impact of Selectional Preference Agreement on Semantic Relational Similarity—0
Exploiting Social Tags for Cross-Domain Collaborative Filtering—0
Transfer Learning Using Logistic Regression in Credit Scoring—0
Transferring Expectations in Model-based Reinforcement Learning—0
Semi-supervised Learning of Naive Bayes Classifier with feature constraints—0
A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling—0
Semi-supervised Chinese Word Segmentation for CLP2012—0
Sparse coding for multitask and transfer learning—0
The Arcade Learning Environment: An Evaluation Platform for General AgentsCode0
Active Learning with Transfer Learning—0
On Causal and Anticausal LearningCode0
Large-Scale Feature Learning With Spike-and-Slab Sparse Coding—0
Analyzing Urdu Social Media for Sentiments using Transfer Learning with Controlled Translations—0
Phrase-Based Approach for Adaptive Tokenization—0
PAC-Bayesian Policy Evaluation for Reinforcement 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