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Explainability in time series models is crucial for fostering trust, facilitating debugging, and ensuring interpretability in real-world applications. In this work, we introduce Implet, a novel post-hoc explainer that generates accurate and…

Machine Learning · Computer Science 2025-05-14 Fanyu Meng , Ziwen Kan , Shahbaz Rezaei , Zhaodan Kong , Xin Chen , Xin Liu

Three pulsar timing arrays are now producing high quality data sets. As reviewed in this paper, these data sets are been processed to 1) develop a pulsar-based time standard, 2) search for errors in the solar system planetary ephemeris and…

Solar and Stellar Astrophysics · Physics 2015-06-11 G. Hobbs

We propose a new sparse Granger-causal learning framework for temporal event data. We focus on a specific class of point processes called the Hawkes process. We begin by pointing out that most of the existing sparse causal learning…

Machine Learning · Computer Science 2025-01-28 Tsuyoshi Idé , Georgios Kollias , Dzung T. Phan , Naoki Abe

Inference and prediction under the sparsity assumption have been a hot research topic in recent years. However, in practice, the sparsity assumption is difficult to test, and more importantly can usually be violated. In this paper, to study…

Statistics Theory · Mathematics 2022-10-18 Yanmei Shi , Zhiruo Li , Qi Zhang

We analyze and partially solve system of recurrences that can be derived from the properties of martingale orthogonal polynomials that characterize quadratic harnesses (QH). We also specify conditions for the existence of moments of one…

Probability · Mathematics 2013-12-18 Paweł J. Szabłowski

This is a review on subgaussian sequences of random variables, prepared for the Mediterranean Institute for the Mathematical Sciences (MIMS). We first describe the main examples of such sequences. Then we focus on examples coming from the…

Probability · Mathematics 2023-04-12 Gilles Pisier

We investigate convergence properties of discrete-time semigroup quantum dynamics, including asymptotic stability, probability and speed of convergence to pure states and subspaces. These properties are of interest in both the analysis of…

Quantum Physics · Physics 2015-06-22 Giuseppe Ilario Cirillo , Francesco Ticozzi

Relationship inference from sparse data is an important task with applications ranging from product recommendation to drug discovery. A recently proposed linear model for sparse matrix completion has demonstrated surprising advantage in…

Machine Learning · Computer Science 2024-03-14 Aleksandar Poleksic

In this paper we derive characterizations of boundedness of the subsequences of partial sums with respect to Vilenkin system on the martingale Hardy spaces when $ 0<p<1 $. Moreover, we find necessary and sufficient conditions for the…

Classical Analysis and ODEs · Mathematics 2018-02-22 G. Tephnadze

We study functions which are the pointwise limit of a sequence of holomorphic functions. In one complex variable this is a classical topic, though we offer some new points of view and new results. Some novel results for solutions of…

Complex Variables · Mathematics 2010-10-08 Steven G. Krantz

In this paper we propose a solution to the problem of moment matching with preservation of the port Hamiltonian structure, in the framework of time-domain moment matching. We characterize several families of parameterized port Hamiltonian…

Dynamical Systems · Mathematics 2024-05-06 Tudor C. Ionescu , Alessandro Astolfi

We study the persistence in a class of continuous stochastic processes that are stationary only under integer shifts of time. We show that under certain conditions, the persistence of such a continuous process reduces to the persistence of…

Statistical Mechanics · Physics 2009-11-07 Satya N. Majumdar , Deepak Dhar

In our previous papers, together with J. Paseka we introduced so-called sectionally pseudocomplemented lattices and posets and illuminated their role in algebraic constructions. We believe that - similar to relatively pseudocomplemented…

Logic · Mathematics 2020-07-28 Ivan Chajda , Helmut Länger

We consider the problem of identifying a mixture of Gaussian distributions with same unknown covariance matrix by their sequence of moments up to certain order. Our approach rests on studying the moment varieties obtained by taking special…

Statistics Theory · Mathematics 2026-03-09 Daniele Agostini , Carlos Améndola , Kristian Ranestad

We study the Subnormal Completion Problem (SCP) for 2-variable weighted shifts. We use tools and techniques from the theory of truncated moment problems to give a general strategy to solve SCP. We then show that when all quadratic moments…

Functional Analysis · Mathematics 2015-03-17 Raul E. Curto , Sang Hoon Lee , Jasang Yoon

Sparse systems are usually parameterized by a tuning parameter that determines the sparsity of the system. How to choose the right tuning parameter is a fundamental and difficult problem in learning the sparse system. In this paper, by…

Methodology · Statistics 2019-01-18 Moo K. Chung , Jamie L. Hanson , Jieping Ye , Richard J. Davidson , Seth D. Pollak

Approximate analytical formulae are derived for the pulse profile produced by small hot spots on a rapidly rotating neutron star. Its Fourier amplitudes and phases are calculated. The proposed formalism takes into account gravitational…

Astrophysics · Physics 2008-11-26 Juri Poutanen , Andrei M. Beloborodov

Statistical inference of the high-dimensional regression coefficients is challenging because the uncertainty introduced by the model selection procedure is hard to account for. A critical question remains unsettled; that is, is it possible…

Methodology · Statistics 2025-01-06 Xiaorui Zhu , Yichen Qin , Peng Wang

In this paper we study holomorphic approximation using boundary value problems for $\bar\partial$ on an annulus in the Hilbert space setting. The associated boundary conditions for $\bar\partial$ are the mixed boundary problems on an…

Complex Variables · Mathematics 2020-01-14 Christine Laurent-Thiébaut , Mei-Chi Shaw

We study the problem of characterizing the expected hitting times for a robust generalization of continuous-time Markov chains. This generalization is based on the theory of imprecise probabilities, and the models with which we work…

Probability · Mathematics 2022-06-28 Thomas Krak