DeepAI AI Chat
Log In Sign Up

Sparse online relative similarity learning

by   Dezhong Yao, et al.

For many data mining and machine learning tasks, the quality of a similarity measure is the key for their performance. To automatically find a good similarity measure from datasets, metric learning and similarity learning are proposed and studied extensively. Metric learning will learn a Mahalanobis distance based on positive semi-definite (PSD) matrix, to measure the distances between objectives, while similarity learning aims to directly learn a similarity function without PSD constraint so that it is more attractive. Most of the existing similarity learning algorithms are online similarity learning method, since online learning is more scalable than offline learning. However, most existing online similarity learning algorithms learn a full matrix with d 2 parameters, where d is the dimension of the instances. This is clearly inefficient for high dimensional tasks due to its high memory and computational complexity. To solve this issue, we introduce several Sparse Online Relative Similarity (SORS) learning algorithms, which learn a sparse model during the learning process, so that the memory and computational cost can be significantly reduced. We theoretically analyze the proposed algorithms, and evaluate them on some real-world high dimensional datasets. Encouraging empirical results demonstrate the advantages of our approach in terms of efficiency and efficacy.


page 1

page 8


Similarity Learning for High-Dimensional Sparse Data

A good measure of similarity between data points is crucial to many task...

Large Scale Local Online Similarity/Distance Learning Framework based on Passive/Aggressive

Similarity/Distance measures play a key role in many machine learning, p...

Low-Rank Robust Online Distance/Similarity Learning based on the Rescaled Hinge Loss

An important challenge in metric learning is scalability to both size an...

Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds

Similarity and metric learning provides a principled approach to constru...

SOL: A Library for Scalable Online Learning Algorithms

SOL is an open-source library for scalable online learning algorithms, a...

Learning Style Similarity for Searching Infographics

Infographics are complex graphic designs integrating text, images, chart...

Similarity Learning for Provably Accurate Sparse Linear Classification

In recent years, the crucial importance of metrics in machine learning a...