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no code implementations • 8 Aug 2023 • Neophytos Charalambides, Hessam Mahdavifar, Mert Pilanci, Alfred O. Hero III

Specifically, we apply a random orthonormal matrix and then subsample \textit{blocks}, to simultaneously secure the information and reduce the dimension of the regression problem.

no code implementations • 16 Aug 2022 • Conrad D. Hougen, Lance M. Kaplan, Magdalena Ivanovska, Federico Cerutti, Kumar Vijay Mishra, Alfred O. Hero III

In second-order uncertain Bayesian networks, the conditional probabilities are only known within distributions, i. e., probabilities over probabilities.

no code implementations • 8 Aug 2022 • Conrad D. Hougen, Lance M. Kaplan, Federico Cerutti, Alfred O. Hero III

When the historical data are limited, the conditional probabilities associated with the nodes of Bayesian networks are uncertain and can be empirically estimated.

no code implementations • 22 Jul 2022 • Byoungwook Jang, Julia Nepper, Marc Chevrette, Jo Handelsman, Alfred O. Hero III

Recent works in bandit problems adopted lasso convergence theory in the sequential decision-making setting.

no code implementations • 15 Mar 2021 • Elyas Sabeti, Peter X. K. Song, Alfred O. Hero III

Sparse representation has been widely used in data compression, signal and image denoising, dimensionality reduction and computer vision.

no code implementations • 7 Oct 2020 • Benjamin D. Robinson, Robert Malinas, Alfred O. Hero III

An important problem in space-time adaptive detection is the estimation of the large p-by-p interference covariance matrix from training signals.

no code implementations • 13 Feb 2020 • Abram Magner, Mayank Baranwal, Alfred O. Hero III

We investigate the power of GCNs, as a function of their number of layers, to distinguish between different random graph models on the basis of the embeddings of their sample graphs.

no code implementations • 28 Oct 2019 • Abram Magner, Mayank Baranwal, Alfred O. Hero III

We give a precise characterization of the set of pairs of graphons that are indistinguishable by a GCN with nonlinear activation functions coming from a certain broad class if its depth is at least logarithmic in the size of the sample graph.

no code implementations • 28 Jan 2019 • Alexander Jung, Alfred O. Hero III, Alexandru Mara, Saeed Jahromi, Ayelet Heimowitz, Yonina C. Eldar

This lends naturally to learning the labels by total variation (TV) minimization, which we solve by applying a recently proposed primal-dual method for non-smooth convex optimization.

1 code implementation • 27 Jan 2018 • Morteza Noshad, Yu Zeng, Alfred O. Hero III

To the best of our knowledge EDGE is the first non-parametric MI estimator that can achieve parametric MSE rates with linear time complexity.

no code implementations • 15 Nov 2017 • Tianpei Xie, Sijia Liu, Alfred O. Hero III

Consider a social network where only a few nodes (agents) have meaningful interactions in the sense that the conditional dependency graph over node attribute variables (behaviors) is sparse.

no code implementations • 31 Oct 2017 • Morteza Noshad Iranzad, Alfred O. Hero III

Meta learning of optimal classifier error rates allows an experimenter to empirically estimate the intrinsic ability of any estimator to discriminate between two populations, circumventing the difficult problem of estimating the optimal Bayes classifier.

no code implementations • 17 Feb 2017 • Morteza Noshad, Kevin R. Moon, Salimeh Yasaei Sekeh, Alfred O. Hero III

Considering the $k$-nearest neighbor ($k$-NN) graph of $Y$ in the joint data set $(X, Y)$, we show that the average powered ratio of the number of $X$ points to the number of $Y$ points among all $k$-NN points is proportional to R\'{e}nyi divergence of $X$ and $Y$ densities.

no code implementations • 7 Jan 2017 • Kristjan Greenewald, Stephen Kelley, Brandon Oselio, Alfred O. Hero III

We propose Online Convex Ensemble StrongLy Adaptive Dynamic Learning (OCELAD), a general adaptive, online approach for learning and tracking optimal metrics as they change over time that is highly robust to a variety of nonstationary behaviors in the changing metric.

1 code implementation • 5 Dec 2016 • Alexander Jung, Alfred O. Hero III, Alexandru Mara, Saeed Jahromi

This learning algorithm allows for a highly scalable implementation as message passing over the underlying data graph.

no code implementations • 2 Nov 2016 • Alexander Jung, Alfred O. Hero III, Alexandru Mara, Sabeur Aridhi

We propose a scalable method for semi-supervised (transductive) learning from massive network-structured datasets.

no code implementations • 23 Sep 2016 • Pin-Yu Chen, Alfred O. Hero III

Multilayer graphs are commonly used for representing different relations between entities and handling heterogeneous data processing tasks.

1 code implementation • 21 Sep 2016 • Pin-Yu Chen, Thibaut Gensollen, Alfred O. Hero III

One of the longstanding problems in spectral graph clustering (SGC) is the so-called model order selection problem: automated selection of the correct number of clusters.

no code implementations • 13 Sep 2016 • Kevin R. Moon, Morteza Noshad, Salimeh Yasaei Sekeh, Alfred O. Hero III

Information theoretic measures (e. g. the Kullback Liebler divergence and Shannon mutual information) have been used for exploring possibly nonlinear multivariate dependencies in high dimension.

no code implementations • 12 Sep 2016 • Sundeep Prabhakar Chepuri, Sijia Liu, Geert Leus, Alfred O. Hero III

Given the noisy data, we show that the joint sparse graph learning and denoising problem can be simplified to designing only the sparse edge selection vector, which can be solved using convex optimization.

no code implementations • 13 Oct 2015 • Stephen V. Gliske, Kevin R. Moon, William C. Stacey, Alfred O. Hero III

High frequency oscillations (HFOs) are a promising biomarker of epileptic brain tissue and activity.

no code implementations • 20 Aug 2015 • Ko-Jen Hsiao, Kevin S. Xu, Jeff Calder, Alfred O. Hero III

If the relative importance of the different dissimilarity measures are not known in advance, as in many anomaly detection applications, the anomaly detection algorithm may need to be executed multiple times with different choices of weights in the linear combination.

no code implementations • 5 Jul 2015 • Tianpei Xie, Nasser M. Nasrabadi, Alfred O. Hero III

In this paper, we consider multi-sensor classification when there is a large number of unlabeled samples.

no code implementations • 27 Apr 2015 • Kevin R. Moon, Veronique Delouille, Alfred O. Hero III

For example, the Bayes error rate of a given feature space, if known, can be used to aid in choosing a classifier, as well as in feature selection and model selection for the base classifiers and the meta classifier.

no code implementations • 10 Apr 2015 • Kevin R. Moon, Veronique Delouille, Jimmy J. Li, Ruben De Visscher, Fraser Watson, Alfred O. Hero III

We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the $R$ value.

no code implementations • 9 Apr 2015 • Pin-Yu Chen, Alfred O. Hero III

We prove phase transitions in community detectability as a function of the external edge connection probability and the noisy edge presence probability under a general network model where two arbitrarily connected communities are interconnected by random external edges.

no code implementations • 13 Mar 2015 • Kevin R. Moon, Jimmy J. Li, Veronique Delouille, Ruben De Visscher, Fraser Watson, Alfred O. Hero III

We find the relationship between complexity of an active region as measured by Mount Wilson and the intrinsic dimension of its image patches.

no code implementations • 7 Nov 2014 • Kevin R. Moon, Alfred O. Hero III

The problem of f-divergence estimation is important in the fields of machine learning, information theory, and statistics.

no code implementations • 25 Sep 2014 • Goran Marjanovic, Magnus O. Ulfarsson, Alfred O. Hero III

Significant attention has been given to minimizing a penalized least squares criterion for estimating sparse solutions to large linear systems of equations.

no code implementations • 5 Aug 2014 • Goran Marjanovic, Alfred O. Hero III

In this paper we consider non-convex $l_0$ penalized log-likelihood inverse covariance estimation and present a novel cyclic descent algorithm for its optimization.

no code implementations • 24 Jun 2014 • Kevin R. Moon, Jimmy J. Li, Veronique Delouille, Fraser Watson, Alfred O. Hero III

Sunspots, as seen in white light or continuum images, are associated with regions of high magnetic activity on the Sun, visible on magnetogram images.

no code implementations • 10 Jun 2014 • Zhaoshi Meng, Brian Eriksson, Alfred O. Hero III

Gaussian graphical models (GGM) have been widely used in many high-dimensional applications ranging from biological and financial data to recommender systems.

no code implementations • 19 May 2014 • Kristjan H. Greenewald, Alfred O. Hero III

We consider the application of KronPCA spatio-temporal modeling techniques [Greenewald et al 2013, Tsiligkaridis et al 2013] to the extraction of spatiotemporal features for video dismount classification.

no code implementations • 13 Mar 2014 • Hamed Firouzi, Dennis Wei, Alfred O. Hero III

This property permits independent correlation analysis at each frequency, alleviating the computational and statistical challenges of high-dimensional time series.

no code implementations • 4 Mar 2014 • Kevin S. Xu, Alfred O. Hero III

There has been recent interest in statistical modeling of dynamic networks, which are observed at multiple points in time and offer a richer representation of many complex phenomena.

no code implementations • 21 Feb 2014 • Ko-Jen Hsiao, Jeff Calder, Alfred O. Hero III

Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information.

no code implementations • 31 Oct 2013 • Jie Chen, Cédric Richard, Alfred O. Hero III

Incorporating spatial information into hyperspectral unmixing procedures has been shown to have positive effects, due to the inherent spatial-spectral duality in hyperspectral scenes.

no code implementations • 27 Jul 2013 • Kristjan Greenewald, Theodoros Tsiligkaridis, Alfred O. Hero III

To allow a smooth tradeoff between the reduction in the number of parameters (to reduce estimation variance) and the accuracy of the covariance approximation (affecting estimation bias), we introduce a diagonally loaded modification of the sum of kronecker products representation [1].

no code implementations • 30 Apr 2013 • Kevin S. Xu, Mark Kliger, Yilun Chen, Peter J. Woolf, Alfred O. Hero III

To date, most studies on spam have focused only on the spamming phase of the spam cycle and have ignored the harvesting phase, which consists of the mass acquisition of email addresses.

no code implementations • 22 Apr 2013 • Kevin S. Xu, Alfred O. Hero III

Significant efforts have gone into the development of statistical models for analyzing data in the form of networks, such as social networks.

no code implementations • 19 Mar 2013 • Zhaoshi Meng, Dennis Wei, Ami Wiesel, Alfred O. Hero III

In this paper, we propose a general framework for distributed estimation based on a maximum marginal likelihood (MML) approach.

no code implementations • 12 Feb 2013 • Theodoros Tsiligkaridis, Alfred O. Hero III

We show that a class of block Toeplitz covariance matrices is approximatable by low separation rank and give bounds on the minimal separation rank $r$ that ensures a given level of bias.

no code implementations • 3 Apr 2012 • Theodoros Tsiligkaridis, Alfred O. Hero III, Shuheng Zhou

The KGlasso algorithm generalizes Glasso, introduced by Yuan and Lin ["Model selection and estimation in the Gaussian graphical model," Biometrika, vol.

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