Výsledky vyhledávání

Report

A Finite-Horizon Approach to Active Level Set Estimation

Autor: Kearns, Phillip, Jedynak, Bruno, Lipor, John

We consider the problem of active learning in the context of spatial sampling for level set estimation (LSE), where the goal is to localize all regions where a function of interest lies above/below a given threshold as quickly as possible. We present

Externí odkaz: http://arxiv.org/abs/2310.11985

Zobrazit plný text záznamu

Akademický článek

Vessel trajectory prediction with recurrent neural networks: An evaluation of datasets, features, and architectures

Autor: Slaughter, Isaac, Charla, Jagir Laxmichand, Siderius, Martin, Lipor, John

Publikováno v: In Journal of Ocean Engineering and Science January 2024

Zobrazit plný text záznamu

Akademický článek

When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates

Autor: Mordensky, Stanley P., Lipor, John J., DeAngelo, Jacob, Burns, Erick R., Lindsey, Cary R.

Publikováno v: In Geothermics May 2023 110

Zobrazit plný text záznamu

Report

Subspace Clustering using Ensembles of $K$-Subspaces

Autor: Lipor, John, Hong, David, Tan, Yan Shuo, Balzano, Laura

Subspace clustering is the unsupervised grouping of points lying near a union of low-dimensional linear subspaces. Algorithms based directly on geometric properties of such data tend to either provide poor empirical performance, lack theoretical guar

Externí odkaz: http://arxiv.org/abs/1709.04744

Zobrazit plný text záznamu

Report

Leveraging Union of Subspace Structure to Improve Constrained Clustering

Autor: Lipor, John, Balzano, Laura

Publikováno v: Proceedings of the 34th International Conference on Machine Learning, in PMLR 70:2130-2139 (2017)

Many clustering problems in computer vision and other contexts are also classification problems, where each cluster shares a meaningful label. Subspace clustering algorithms in particular are often applied to problems that fit this description, for e

Externí odkaz: http://arxiv.org/abs/1608.02146

Zobrazit plný text záznamu

Dissertation/ Thesis

MIMO Radar Transceiver Design for High Signal-to-Interference-Plus-Noise Ratio

Autor: Lipor, John

Multiple-input multiple-output (MIMO) radar employs orthogonal or partially correlated transmit signals to achieve performance benefits over its phased-array counterpart. It has been shown that MIMO radar can achieve greater spatial resolution, impro

Externí odkaz: http://hdl.handle.net/10754/291103

Zobrazit plný text záznamu

Report

Distance-Penalized Active Learning Using Quantile Search

Autor: Lipor, John, Wong, Brandon, Scavia, Donald, Kerkez, Branko, Balzano, Laura

Adaptive sampling theory has shown that, with proper assumptions on the signal class, algorithms exist to reconstruct a signal in $\mathbb{R}^{d}$ with an optimal number of samples. We generalize this problem to the case of spatial signals, where the

Externí odkaz: http://arxiv.org/abs/1509.08387

Zobrazit plný text záznamu