Transfer Learning Algorithm

Transfer learning algorithms aim to improve the efficiency and performance of machine learning models by leveraging knowledge gained from solving related tasks. Current research focuses on enhancing robustness to data inconsistencies (e.g., noise, distributional shifts), developing novel algorithms like meta-learning frameworks for dynamic tasks, and exploring quantum-classical hybrid approaches. These advancements are impacting diverse fields, including natural language processing, genetic data analysis, and agriculture, by enabling more accurate and efficient models with limited data in specific domains.

Papers

July 11, 2024

A Cantor-Kantorovich Metric Between Markov Decision Processes with Application to Transfer Learning
Adrien Banse, Venkatraman Renganathan, Raphaël M. Jungers
Reinforcement Learning Transfer Learning Application Proficiency Markov Decision Process Markov Chain Kantorovich Rubinstein Distance Transfer Learning Algorithm

January 15, 2024

Quantum Transfer Learning for Acceptability Judgements
Giuseppe Buonaiuto, Raffaele Guarasci, Aniello Minutolo, Giuseppe De Pietro, Massimo Esposito
Quantum Advantage Hybrid Quantum Classical Quantum Transfer Learning Transfer Learning Algorithm Acceptability Judgment

July 17, 2023

Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study
Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn
Native Robustness Transfer Learning Distribution Shift Covariate Shift Transfer Learning Algorithm Min Entropy

July 12, 2022

An Information-Theoretic Analysis for Transfer Learning: Error Bounds and Applications
Xuetong Wu, Jonathan H. Manton, Uwe Aickelin, Jingge Zhu
Domain Adaptation Transfer Learning Financial Application Generalization Error Information Theoretic Error Bound Transfer Learning Algorithm

July 5, 2022

A Unified Meta-Learning Framework for Dynamic Transfer Learning
Jun Wu, Jingrui He
Meta Learning Framework Transfer Learning Algorithm

June 20, 2022

A Neural Network Based Method with Transfer Learning for Genetic Data Analysis
Jinghang Lin, Shan Zhang, Qing Lu
Transfer Learning Neural Method Transfer Learning Algorithm

February 10, 2022

Transfer-Learning Across Datasets with Different Input Dimensions: An Algorithm and Analysis for the Linear Regression Case
Luis Pedro Silvestrin, Harry van Zanten, Mark Hoogendoorn, Ger Koole
Data Set Machine Learning Model General Analysis Practical Algorithm Least Square Hyperparameter Tuning Transfer Learning Algorithm Input Dimension

February 4, 2022

TIML: Task-Informed Meta-Learning for Agriculture
Gabriel Tseng, Hannah Kerner, David Rolnick
Agricultural Domain Meta Training Agricultural Data Transfer Learning Algorithm Data Rich Region