← Back to papers
2008 JMLR JMLR 2008

A Library for Locally Weighted Projection Regression

Abstract

In this paper we introduce an improved implementation of locally weighted projection regression (LWPR), a supervised learning algorithm that is capable of handling high-dimensional input data. As the key features, our code supports multi-threading, is available for multiple platforms, and provides wrappers for several programming languages. [abs] [ pdf ][ bib ] [ code ] © JMLR 2008. (edit, beta)

🧭 Keyword Pioneer — locally weighted regression
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
🐣 Hot Topic Early Bird — function approximation

Authors

Stefan Klanke , Sethu Vijayakumar , Stefan Schaal

Topics

Machine Learning > Core Methods > Regression Machine Learning > Learning Types > Supervised Learning

Keywords

function approximation supervised learning high-dimensional datum locally weighted regression
Download PDF

Related papers

On the Equivalence of Linear Dimensionality-Reducing Transformations 2008
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies 2008
Algorithms for Sparse Linear Classifiers in the Massive Data Setting 2008
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models 2008
Shark 2008