Transfer Learning Framework

Transfer learning frameworks aim to improve the efficiency and effectiveness of machine learning models by leveraging knowledge gained from a source task to enhance performance on a related, but different, target task. Current research focuses on adapting these frameworks across diverse domains, employing deep learning architectures and techniques like attention mechanisms and contrastive learning to address challenges such as data scarcity and domain shift. This approach is proving valuable in various applications, including crime prediction, healthcare monitoring, speech reconstruction, and traffic flow estimation, by enabling accurate model training even with limited data in the target domain.

Papers

November 7, 2024

Enhancing Bronchoscopy Depth Estimation through Synthetic-to-Real Domain Adaptation
Qingyao Tian, Huai Liao, Xinyan Huang, Lujie Li, Hongbin Liu
Depth Estimation Monocular Depth Estimation Adaptation Concern Depth Prediction Transfer Learning Framework

November 4, 2024

Distribution alignment based transfer fusion frameworks on quantum devices for seeking quantum advantages
Xi He, Feiyu Du, Xiaohan Yu, Yang Zhao, Tao Lei
Quantum Machine Learning Distribution Alignment Quantum Advantage Smart Device Deep Transfer Transfer Learning Framework

June 10, 2024

Network-Based Transfer Learning Helps Improve Short-Term Crime Prediction Accuracy
Jiahui Wu, Vanessa Frias-Martinez
Transfer Learning Crime Prediction Transfer Learning Framework

May 26, 2024

Daily Physical Activity Monitoring -- Adaptive Learning from Multi-source Motion Sensor Data
Haoting Zhang, Donglin Zhan, Yunduan Lin, Jinghai He, Qing Zhu, Zuo-Jun Max Shen, Zeyu Zheng
Adaptive Learning Wearable Device Multi Source Source Identification Transfer Learning Framework

October 7, 2023

August 7, 2023

July 12, 2023

Prototypical Contrastive Transfer Learning for Multimodal Language Understanding
Seitaro Otsuki, Shintaro Ishikawa, Komei Sugiura
Contrastive Loss Multimodal Understanding Prototypical Contrastive Learning Transfer Learning Framework

June 26, 2023

A Collaborative Transfer Learning Framework for Cross-domain Recommendation
Wei Zhang, Pengye Zhang, Bo Zhang, Xingxing Wang, Dong Wang
Transfer Learning Cross Domain Recommendation Domain Specific Feature CTR Prediction Transfer Learning Framework

November 17, 2022

Transfer learning for tensor Gaussian graphical models
Mingyang Ren, Yaoming Zhen, Junhui Wang
Formality Transfer Tensor Type Calculus Tensor Data Transfer Learning Framework Tensor Graph

November 1, 2022

Transfer Learning with Kernel Methods
Adityanarayanan Radhakrishnan, Max Ruiz Luyten, Neha Prasad, Caroline Uhler
Transfer Learning Large Scale Kernel Method Effective Transfer Learning Transfer Learning Framework

June 17, 2022

TLETA: Deep Transfer Learning and Integrated Cellular Knowledge for Estimated Time of Arrival Prediction
Hieu Tran, Son Nguyen, I-Ling Yen, Farokh Bastani
Traffic Data Intelligent Transportation System Deep Transfer Learning Time Prediction Transfer Learning Framework Bus Arrival

April 18, 2022

Enhancing Non-mass Breast Ultrasound Cancer Classification With Knowledge Transfer
Yangrun Hu, Yuanfan Guo, Fan Zhang, Mingda Wang, Tiancheng Lin, Rong Wu, Yi Xu
Transfer Learning Knowledge Transfer Breast Ultrasound Transfer Learning Framework Lesion Image Non Image Data

March 29, 2022

Transfer Learning Framework for Low-Resource Text-to-Speech using a Large-Scale Unlabeled Speech Corpus
Minchan Kim, Myeonghun Jeong, Byoung Jin Choi, Sunghwan Ahn, Joun Yeop Lee, Nam Soo Kim
Text to Speech Text to Speech Model Unlabeled Speech Multi Speaker Text to Speech Single Speaker Transfer Learning Framework Low Resource Text to Speech

February 22, 2022

Multi-fidelity reinforcement learning framework for shape optimization
Sahil Bhola, Suraj Pawar, Prasanna Balaprakash, Romit Maulik
Deep Reinforcement Learning Policy Learning Multi Fidelity Shape Optimization Transfer Learning Framework Airfoil Shape Optimization

February 12, 2022

Automatic Issue Classifier: A Transfer Learning Framework for Classifying Issue Reports
Anas Nadeem, Muhammad Usman Sarwar, Muhammad Zubair Malik
Bug Report Transfer Learning Framework Issue Tracking System Issue Type

Transfer Learning Framework

Papers

Enhancing Bronchoscopy Depth Estimation through Synthetic-to-Real Domain Adaptation

Distribution alignment based transfer fusion frameworks on quantum devices for seeking quantum advantages

Network-Based Transfer Learning Helps Improve Short-Term Crime Prediction Accuracy

Daily Physical Activity Monitoring -- Adaptive Learning from Multi-source Motion Sensor Data

Transferable Deep Clustering Model

Neural2Speech: A Transfer Learning Framework for Neural-Driven Speech Reconstruction

A Transfer Learning Framework for Proactive Ramp Metering Performance Assessment

On-ramp and Off-ramp Traffic Flows Estimation Based on A Data-driven Transfer Learning Framework

Prototypical Contrastive Transfer Learning for Multimodal Language Understanding

A Collaborative Transfer Learning Framework for Cross-domain Recommendation

Transfer learning for tensor Gaussian graphical models

Transfer Learning with Kernel Methods

TLETA: Deep Transfer Learning and Integrated Cellular Knowledge for Estimated Time of Arrival Prediction

Enhancing Non-mass Breast Ultrasound Cancer Classification With Knowledge Transfer

Transfer Learning Framework for Low-Resource Text-to-Speech using a Large-Scale Unlabeled Speech Corpus

Multi-fidelity reinforcement learning framework for shape optimization

Automatic Issue Classifier: A Transfer Learning Framework for Classifying Issue Reports