Jeff Calder

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University of Minnesota ∙ berkeley college

The Virtual Goniometer: A new method for measuring angles on 3D models of fragmentary bone and lithics

The contact goniometer is a commonly used tool in lithic and zooarchaeol...
11/10/2020 ∙ by Katrina Yezzi-Woodley, et al. ∙ 22 ∙ share

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Asymptotically optimal strategies for online prediction with history-dependent experts

We establish sharp asymptotically optimal strategies for the problem of ...
08/31/2020 ∙ by Jeff Calder, et al. ∙ 0 ∙ share

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Online Prediction With History-Dependent Experts: The General Case

We study the problem of prediction of binary sequences with expert advic...
07/31/2020 ∙ by Nadejda Drenska, et al. ∙ 0 ∙ share

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Lipschitz regularity of graph Laplacians on random data clouds

In this paper we study Lipschitz regularity of elliptic PDEs on geometri...
07/13/2020 ∙ by Jeff Calder, et al. ∙ 0 ∙ share

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Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates

We propose a new framework, called Poisson learning, for graph based sem...
06/19/2020 ∙ by Jeff Calder, et al. ∙ 0 ∙ share

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Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates

We study graph-based Laplacian semi-supervised learning at low labeling ...
06/04/2020 ∙ by Jeff Calder, et al. ∙ 0 ∙ share

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A continuum limit for the PageRank algorithm

Semi-supervised and unsupervised machine learning methods often rely on ...
01/24/2020 ∙ by Amber Yuan, et al. ∙ 0 ∙ share

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Improved spectral convergence rates for graph Laplacians on epsilon-graphs and k-NN graphs

In this paper we improve the spectral convergence rates for graph-based ...
10/29/2019 ∙ by Jeff Calder, et al. ∙ 0 ∙ share

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Computation of Circular Area and Spherical Volume Invariants via Boundary Integrals

We show how to compute the circular area invariant of planar curves, and...
05/06/2019 ∙ by Riley O'Neill, et al. ∙ 24 ∙ share

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Algorithms for ℓ_p-based semi-supervised learning on graphs

We develop fast algorithms for solving the variational and game-theoreti...
01/15/2019 ∙ by Mauricio Flores Rios, et al. ∙ 12 ∙ share

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Properly-weighted graph Laplacian for semi-supervised learning

The performance of traditional graph Laplacian methods for semi-supervis...
10/10/2018 ∙ by Jeff Calder, et al. ∙ 0 ∙ share

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Accelerated PDE's for efficient solution of regularized inversion problems

We further develop a new framework, called PDE Acceleration, by applying...
09/30/2018 ∙ by Minas Benyamin, et al. ∙ 0 ∙ share

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Lipschitz regularized Deep Neural Networks converge and generalize

Lipschitz regularized neural networks augment the usual fidelity term us...
08/28/2018 ∙ by Adam M. Oberman, et al. ∙ 0 ∙ share

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The limit shape of convex hull peeling

We prove that the convex peeling of a random point set in dimension d ap...
05/21/2018 ∙ by Jeff Calder, et al. ∙ 0 ∙ share

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Anomaly detection and classification for streaming data using PDEs

Nondominated sorting, also called Pareto Depth Analysis (PDA), is widely...
08/15/2016 ∙ by Bilal Abbasi, et al. ∙ 0 ∙ share

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Multi-criteria Similarity-based Anomaly Detection using Pareto Depth Analysis

We consider the problem of identifying patterns in a data set that exhib...
08/20/2015 ∙ by Ko-Jen Hsiao, et al. ∙ 0 ∙ share

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Pareto-depth for Multiple-query Image Retrieval

Most content-based image retrieval systems consider either one single qu...
02/21/2014 ∙ by Ko-Jen Hsiao, et al. ∙ 0 ∙ share

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Multi-criteria Anomaly Detection using Pareto Depth Analysis

We consider the problem of identifying patterns in a data set that exhib...
10/17/2011 ∙ by Ko-Jen Hsiao, et al. ∙ 0 ∙ share

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Jeff Calder

Featured Co-authors

Alfred O. Hero III

Gilad Lerman

Nicolas Garcia Trillos

Braxton Osting

Dejan Slepčev

Ganesh Sundaramoorthi

Anthony Yezzi

Adam M. Oberman

Matthew Thorpe

Kevin S. Xu

Nadejda Drenska

The Virtual Goniometer: A new method for measuring angles on 3D models of fragmentary bone and lithics

Asymptotically optimal strategies for online prediction with history-dependent experts

Online Prediction With History-Dependent Experts: The General Case

Lipschitz regularity of graph Laplacians on random data clouds

Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates

Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates

A continuum limit for the PageRank algorithm

Improved spectral convergence rates for graph Laplacians on epsilon-graphs and k-NN graphs

Computation of Circular Area and Spherical Volume Invariants via Boundary Integrals

Algorithms for ℓ_p-based semi-supervised learning on graphs

Properly-weighted graph Laplacian for semi-supervised learning

Accelerated PDE's for efficient solution of regularized inversion problems

Lipschitz regularized Deep Neural Networks converge and generalize

The limit shape of convex hull peeling

Anomaly detection and classification for streaming data using PDEs

Multi-criteria Similarity-based Anomaly Detection using Pareto Depth Analysis

Pareto-depth for Multiple-query Image Retrieval

Multi-criteria Anomaly Detection using Pareto Depth Analysis