Johan Karlsson
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View article: A cutting plane algorithm for globally solving low-dimensional k-means problems
A cutting plane algorithm for globally solving low-dimensional k-means problems Open
Clustering is one of the most fundamental tools in data science and machine learning, and k-means clustering is one of the most common of such methods. There is a variety of approximate algorithms for the k-means problem, but only a few me…
View article: Harrowing promotes Scots pine seedling establishment more effectively than mounding under herbivore exclusion in a southern Swedish field trial
Harrowing promotes Scots pine seedling establishment more effectively than mounding under herbivore exclusion in a southern Swedish field trial Open
In Sweden, browsing by large herbivores hampers seedling establishment and causes substantial growth losses in economically important, regenerating Scots pine (Pinus sylvestris) stands. In addition, suboptimal site conditions often require…
View article: Dynamic gene regulatory network inference from single-cell data using optimal transport
Dynamic gene regulatory network inference from single-cell data using optimal transport Open
Motivation Modelling gene expression is a central problem in systems biology. Single-cell technologies have revolutionized the field by enabling sequencing at the resolution of individual cells. This results in a much richer data compared …
View article: A parallel framework for graphical optimal transport
A parallel framework for graphical optimal transport Open
We study multi-marginal optimal transport (MOT) problems where the underlying cost has a graphical structure. These graphical multi-marginal optimal transport problems have found applications in several domains including traffic flow contr…
View article: Gene regulatory network inference from single-cell data using optimal transport
Gene regulatory network inference from single-cell data using optimal transport Open
Modelling gene expression is a central problem in systems biology. Single-cell technologies have revolutionised the field by enabling sequencing at the resolution of individual cells. This results in a much richer data compared to what is …
View article: A cutting plane algorithm for globally solving low dimensional k-means clustering problems
A cutting plane algorithm for globally solving low dimensional k-means clustering problems Open
Clustering is one of the most fundamental tools in data science and machine learning, and k-means clustering is one of the most common such methods. There is a variety of approximate algorithms for the k-means problem, but computing the gl…
View article: Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces
Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces Open
This paper presents a framework for computing the Gromov-Wasserstein problem between two sets of points in low dimensional spaces, where the discrepancy is the squared Euclidean norm. The Gromov-Wasserstein problem is a generalization of t…
View article: Scalable Computation of Dynamic Flow Problems via Multimarginal Graph-Structured Optimal Transport
Scalable Computation of Dynamic Flow Problems via Multimarginal Graph-Structured Optimal Transport Open
In this work, we develop a new framework for dynamic network flow problems based on optimal transport theory. We show that the dynamic multicommodity minimum-cost network flow problem can be formulated as a multimarginal optimal transport …
View article: Mean field type control with species dependent dynamics via structured tensor optimization
Mean field type control with species dependent dynamics via structured tensor optimization Open
In this work we consider mean field type control problems with multiple species that have different dynamics. We formulate the discretized problem using a new type of entropy-regularized multimarginal optimal transport problems where the c…
View article: Variance Analysis of Covariance and Spectral Estimates for Mixed-Spectrum Continuous-Time Signals
Variance Analysis of Covariance and Spectral Estimates for Mixed-Spectrum Continuous-Time Signals Open
Publisher Copyright: IEEE
View article: Mean Field Type Control With Species Dependent Dynamics via Structured Tensor Optimization
Mean Field Type Control With Species Dependent Dynamics via Structured Tensor Optimization Open
In this letter we consider mean field type control problems with multiple species that have different dynamics. We formulate the discretized problem using a new type of entropy-regularized multimarginal optimal transport problems where the…
View article: Phylogeography and evolutionary lineage diversity in the small-eared greater galago, <i>Otolemur garnettii</i> (Primates: Galagidae)
Phylogeography and evolutionary lineage diversity in the small-eared greater galago, <i>Otolemur garnettii</i> (Primates: Galagidae) Open
Assessing the true lineage diversity in elusive nocturnal organisms is particularly challenging due to their subtle phenotypic variation in diagnostic traits. The cryptic small-eared greater galago (Otolemur garnettii) offers a great oppor…
View article: Orthogonalization of data via Gromov-Wasserstein type feedback for clustering and visualization
Orthogonalization of data via Gromov-Wasserstein type feedback for clustering and visualization Open
In this paper we propose an adaptive approach for clustering and visualization of data by an orthogonalization process. Starting with the data points being represented by a Markov process using the diffusion map framework, the method adapt…
View article: Information technology and high-impact entrepreneurship
Information technology and high-impact entrepreneurship Open
This article presents a conceptual framework for analyzing the role of information technology in the formation of high-impact entrepreneurship. Entrepreneurial decision-making is contextualized in the setting of competent teams, and where …
View article: Graph-structured tensor optimization for nonlinear density control and mean field games
Graph-structured tensor optimization for nonlinear density control and mean field games Open
In this work we develop a numerical method for solving a type of convex graph-structured tensor optimization problems. This type of problems, which can be seen as a generalization of multi-marginal optimal transport problems with graph-str…
View article: Quantifying and Computing Covariance Uncertainty
Quantifying and Computing Covariance Uncertainty Open
In this work, we consider the problem of bounding the values of a covariance function corresponding to a continuous-time stationary stochastic process or signal. Specifically, for two signals whose covariance functions agree on a finite di…
View article: On the complexity of the optimal transport problem with graph-structured cost
On the complexity of the optimal transport problem with graph-structured cost Open
Multi-marginal optimal transport (MOT) is a generalization of optimal transport to multiple marginals. Optimal transport has evolved into an important tool in many machine learning applications, and its multi-marginal extension opens up fo…
View article: Optimal Transport for Applications in Control and Estimation
Optimal Transport for Applications in Control and Estimation Open
In recent decades, there has been a rapid development of theory and methods for optimal transport, both within systems and control as well as in other areas such as signal processing, medical imaging, statistics, and machine learning. Thes…
View article: Mixed-Spectrum Signals -- Discrete Approximations and Variance Expressions for Covariance Estimates
Mixed-Spectrum Signals -- Discrete Approximations and Variance Expressions for Covariance Estimates Open
The estimation of the covariance function of a stochastic process, or signal, is of integral importance for a multitude of signal processing applications. In this work, we derive closed-form expressions for the variance of covariance estim…
View article: Scalable computation of dynamic flow problems via multi-marginal graph-structured optimal transport
Scalable computation of dynamic flow problems via multi-marginal graph-structured optimal transport Open
In this work, we develop a new framework for dynamic network flow problems based on optimal transport theory. We show that the dynamic multi-commodity minimum-cost network flow problem can be formulated as a multi-marginal optimal transpor…
View article: VidHarm: A Clip Based Dataset for Harmful Content Detection
VidHarm: A Clip Based Dataset for Harmful Content Detection Open
Automatically identifying harmful content in video is an important task with a wide range of applications. However, there is a lack of professionally labeled open datasets available. In this work VidHarm, an open dataset of 3589 video clip…
View article: On analytic interpolation with non-classical constraints for solving problems in robust control
On analytic interpolation with non-classical constraints for solving problems in robust control Open
In this work we consider robust stabilization of uncertain dynamical systems and show that this can be achieved by solving a non-classically constrained analytic interpolation problem. In particular, this non-classical constraint confines …
View article: M$^2$ Spectral Estimation: A Flexible Approach Ensuring Rational Solutions
M$^2$ Spectral Estimation: A Flexible Approach Ensuring Rational Solutions Open
This paper concerns a spectral estimation problem for multivariate (i.e., vector-valued) signals defined on a multidimensional domain, abbreviated as M$^2$. The problem is posed as solving a finite number of trigonometric moment equations …
View article: Multimarginal Optimal Transport with a Tree-Structured Cost and the Schrödinger Bridge Problem
Multimarginal Optimal Transport with a Tree-Structured Cost and the Schrödinger Bridge Problem Open
The optimal transport problem has recently developed into a powerful framework for various applications in estimation and control. Many of the recent advances in the theory and application of optimal transport are based on regularizing the…
View article: M2 Spectral estimation: A flexible approach ensuring rational solutions
M2 Spectral estimation: A flexible approach ensuring rational solutions Open
This paper concerns a spectral estimation problem for multivariate (i.e., vectorvalued) signals defined on a multidimensional domain, abbreviated as M2. The problem is posed as solving a finite number of trigonometric moment equations for …
View article: Incremental inference of collective graphical models
Incremental inference of collective graphical models Open
We consider incremental inference problems from aggregate data for collective dynamics. In particular, we address the problem of estimating the aggregate marginals of a Markov chain from noisy aggregate observations in an incremental (onli…
View article: Multi-marginal optimal transport and probabilistic graphical models
Multi-marginal optimal transport and probabilistic graphical models Open
We study multi-marginal optimal transport problems from a probabilistic graphical model perspective. We point out an elegant connection between the two when the underlying cost for optimal transport allows a graph structure. In particular,…
View article: The Animal Sense warning system Low-cost technology to prevent animals from being killed by traffic
The Animal Sense warning system Low-cost technology to prevent animals from being killed by traffic Open
When free-ranging animals encounter traffic on roads or railways, it may have fatal outcome. In Europe, collisions between vehicles and animals have increased the last 40 years, causing eco-nomic losses and serious welfare concerns. Today …