[PDF] Feature Selection for Transfer Learning

Feature Selection for Transfer Learning - Carnegie Mellon University

Feature Selection for Transfer Learning. 431 are described in the reviews differ across domains, and therefore two dataset distributions may be different [10] ...

(PDF) Feature Selection for Transfer Learning - ResearchGate

Feature selection is an important task in machine learning, which aims to find a small number of features that describes the dataset as well as, or even better, ...

Feature Selection for Transfer Learning | SpringerLink

In such settings, knowing in which dimensions source and target data vary is extremely important to reduce the distance between domains and accurately transfer ...

Transfer Learning in Information Criteria-based Feature Selection

In addition to feature selection, another method to address the problem of insufficient data is transfer learning, which uses knowledge from similar tasks to ...

[PDF] Feature Selection for Transfer Learning - Semantic Scholar

This paper presents a novel method to identify variant and invariant features between two datasets, and formalizes the problem of finding differently ...

Feature selection for transfer learning using particle swarm ...

Feature selection for transfer learning using particle swarm optimization and complexity measures. Guillermo Castillo-Garcıa1, Laura Morán ...

Feature selection for transfer learning - ACM Digital Library

Feature selection for transfer learning. ECML PKDD'11: Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - ...

[0905.4022] Transfer Learning Using Feature Selection - arXiv

Abstract: We present three related ways of using Transfer Learning to improve feature selection. The three methods address different ...

(PDF) Transfer Learning Based on AdaBoost for Feature Selection ...

Combining multiple ConvNet layer features will result in more complex feature space with some features being repetitive. This requires some form ...

[PDF] Transfer Learning Using Feature Selection | Semantic Scholar

Three related ways of using Transfer Learning to improve feature selection based on the information theoretic Minimum Description Length principle are ...

(PDF) Transfer Learning Using Feature Selection | Paramveer Dhillon

Abstract: We present three related ways of using Transfer Learning to improve feature selection. The three methods address different problems, ...

Feature Selection For Transfer Learning | PDF - Scribd

Feature Selection for Transfer Learning - Free download as PDF File (.pdf), Text File (.txt) or read online for free.

Feature Selection by Transfer Learning with Linear Regularized ...

The dimen- sions to be favored are previously selected from similar datasets in large microarray databases, hence performing inductive transfer learning at the ...

Transfer Learning in Information Criteria-based Feature Selection

Title:Transfer Learning in Information Criteria-based Feature Selection ; Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG) ; ACM ...

A Feature-based Transfer Learning to Improve the Image ...

Keywords—Feature-transfer learning; image; feature selection; weight; distance. I. INTRODUCTION. In this big data era, the use of machine learning is growing.

Efficient feature selection for domain adaptation using Mutual ...

In this paper, we introduce a novel and efficient method for feature selection in domain adaptation, a type of transfer learning where the source and target ...

An Investigation of Feature Selection and Transfer Learning for ...

Index. Terms—Offline signature verification, Writer- independent signature verification, Dichotomy transformation,. Feature selection, Transfer learning, Binary ...

Transfer Learning, Feature Selection and Word Sense Disambiguation

Transfer Learning, Feature Selection and Word Sense Disambguation. Paramveer S. Dhillon and Lyle H. Ungar. Computer and Information Science.

An Improved Text Feature Selection Method for Transfer Learning

In this paper, we use two-class text classification problem as a baseline, and improve the traditional method for text feature selection so that the method can ...

Inductive Transfer Learning for Handling Individual Differences in ...

Individual differences were quite obvious in our previous experiments as we also performed feature selection in constructing the individual classifiers, and the ...