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 7751–7800 of 10307 papers

TitleStatusHype
A Method for Building a Commonsense Inference Dataset based on Basic Events—0
A Method of Augmenting Bilingual Terminology by Taking Advantage of the Conceptual Systematicity of Terminologies—0
A Methodology for Controlling the Emotional Expressiveness in Synthetic Speech -- a Deep Learning approach—0
AMEX-AI-LABS: Investigating Transfer Learning for Title Detection in Table of Contents Generation—0
AMF: Adaptable Weighting Fusion with Multiple Fine-tuning for Image Classification—0
AM Flow: Adapters for Temporal Processing in Action Recognition—0
A microservice-based framework for exploring data selection in cross-building knowledge transfer—0
A Minimax Game for Instance based Selective Transfer Learning—0
AMLN: Adversarial-based Mutual Learning Network for Online Knowledge Distillation—0
AMMU : A Survey of Transformer-based Biomedical Pretrained Language Models—0
Amobee at IEST 2018: Transfer Learning from Language Models—0
A model is worth tens of thousands of examples—0
Long-Tailed Learning Requires Feature Learning—0
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation—0
Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images—0
A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problem—0
A Modular and Unified Framework for Detecting and Localizing Video Anomalies—0
MSPM: A Modularized and Scalable Multi-Agent Reinforcement Learning-based System for Financial Portfolio Management—0
Adaptive Sample Aggregation In Transfer Learning—0
Amortized Network Intervention to Steer the Excitatory Point Processes—0
Amplitude-Independent Machine Learning for PPG through Visibility Graphs and Transfer Learning—0
A Multi-class Approach -- Building a Visual Classifier based on Textual Descriptions using Zero-Shot Learning—0
A Multi-Fidelity Graph U-Net Model for Accelerated Physics Simulations—0
A Multi-Format Transfer Learning Model for Event Argument Extraction via Variational Information Bottleneck—0
A Multi-input Multi-output Transformer-based Hybrid Neural Network for Multi-class Privacy Disclosure Detection—0
Multilingual Approach to Joint Speech and Accent Recognition with DNN-HMM Framework—0
A multilingual training strategy for low resource Text to Speech—0
A Multi-media Approach to Cross-lingual Entity Knowledge Transfer—0
A Multimodal German Dataset for Automatic Lip Reading Systems and Transfer Learning—0
A Multi-Modal Knowledge-Enhanced Framework for Vessel Trajectory Prediction—0
A Multimodal Lightweight Approach to Fault Diagnosis of Induction Motors in High-Dimensional Dataset—0
A Multimodal Recommender System for Large-scale Assortment Generation in E-commerce—0
A multi-objective perspective on jointly tuning hardware and hyperparameters—0
A Multi-Resolution Physics-Informed Recurrent Neural Network: Formulation and Application to Musculoskeletal Systems—0
A multi-source approach for Breton–French hybrid machine translation—0
A Multi-Stage Attentive Transfer Learning Framework for Improving COVID-19 Diagnosis—0
A Multi-Task and Multi-Label Classification Model for Implicit Discourse Relation Recognition—0
A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition—0
A multitask transfer learning framework for the prediction of virus-human protein-protein interactions—0
AMUSED: A Multi-Stream Vector Representation Method for Use in Natural Dialogue—0
An Acceleration Method Based on Deep Learning and Multilinear Feature Space—0
An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series—0
An adaptive human-in-the-loop approach to emission detection of Additive Manufacturing processes and active learning with computer vision—0
An adaptive transfer learning perspective on classification in non-stationary environments—0
An AI-driven framework for the prediction of personalised health response to air pollution—0
Analysis and Adaptation of YOLOv4 for Object Detection in Aerial Images—0
Analysis and Prediction of NLP models via Task Embeddings—0
Analysis of Convolutional Neural Network-based Image Classifications: A Multi-Featured Application for Rice Leaf Disease Prediction and Recommendations for Farmers—0
An Analysis of Semantically-Aligned Speech-Text Embeddings—0
Analysis of Multilingual Sequence-to-Sequence speech recognition systems—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