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07/19/2023
Novel Batch Active Learning Approach and Its Application to Synthetic Aperture Radar Datasets
Active learning improves the performance of machine learning methods by ...
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10/27/2022
Poisson Reweighted Laplacian Uncertainty Sampling for Graph-based Active Learning
We show that uncertainty sampling is sufficient to achieve exploration v...
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10/17/2022
Ratio convergence rates for Euclidean first-passage percolation: Applications to the graph infinity Laplacian
In this paper we prove the first quantitative convergence rates for the ...
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09/06/2022
Use and Misuse of Machine Learning in Anthropology
Machine learning (ML), being now widely accessible to the research commu...
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05/20/2022
Using machine learning on new feature sets extracted from 3D models of broken animal bones to classify fragments according to break agent
Distinguishing agents of bone modification at paleoanthropological sites...
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05/05/2022
The Batch Artifact Scanning Protocol: A new method using computed tomography (CT) to rapidly create three-dimensional models of objects from large collections en masse
Within anthropology, the use of three-dimensional (3D) imaging has becom...
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03/31/2022
Graph-based Active Learning for Semi-supervised Classification of SAR Data
We present a novel method for classification of Synthetic Aperture Radar...
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02/17/2022
Hamilton-Jacobi equations on graphs with applications to semi-supervised learning and data depth
Shortest path graph distances are widely used in data science and machin...
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11/24/2021
Uniform Convergence Rates for Lipschitz Learning on Graphs
Lipschitz learning is a graph-based semi-supervised learning method wher...
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11/05/2021
Boundary Estimation from Point Clouds: Algorithms, Guarantees and Applications
We investigate identifying the boundary of a domain from sample points i...
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11/10/2020
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...
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08/31/2020
Asymptotically optimal strategies for online prediction with history-dependent experts
We establish sharp asymptotically optimal strategies for the problem of ...
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07/31/2020
Online Prediction With History-Dependent Experts: The General Case
We study the problem of prediction of binary sequences with expert advic...
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07/13/2020
Lipschitz regularity of graph Laplacians on random data clouds
In this paper we study Lipschitz regularity of elliptic PDEs on geometri...
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06/19/2020
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates
We propose a new framework, called Poisson learning, for graph based sem...
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06/04/2020
Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates
We study graph-based Laplacian semi-supervised learning at low labeling ...
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01/24/2020
A continuum limit for the PageRank algorithm
Semi-supervised and unsupervised machine learning methods often rely on ...
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10/29/2019
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 ...
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05/06/2019
Computation of Circular Area and Spherical Volume Invariants via Boundary Integrals
We show how to compute the circular area invariant of planar curves, and...
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01/15/2019
Algorithms for ℓ_p-based semi-supervised learning on graphs
We develop fast algorithms for solving the variational and game-theoreti...
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10/10/2018
Properly-weighted graph Laplacian for semi-supervised learning
The performance of traditional graph Laplacian methods for semi-supervis...
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09/30/2018
Accelerated PDE's for efficient solution of regularized inversion problems
We further develop a new framework, called PDE Acceleration, by applying...
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08/28/2018
Lipschitz regularized Deep Neural Networks converge and generalize
Lipschitz regularized neural networks augment the usual fidelity term us...
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05/21/2018
The limit shape of convex hull peeling
We prove that the convex peeling of a random point set in dimension d ap...
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08/15/2016
Anomaly detection and classification for streaming data using PDEs
Nondominated sorting, also called Pareto Depth Analysis (PDA), is widely...
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08/20/2015
Multi-criteria Similarity-based Anomaly Detection using Pareto Depth Analysis
We consider the problem of identifying patterns in a data set that exhib...
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02/21/2014
Pareto-depth for Multiple-query Image Retrieval
Most content-based image retrieval systems consider either one single qu...
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10/17/2011
