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Many real optimisation problems lead to multimodal domains and so require the identification of multiple optima. Niching methods have been developed to maintain the population diversity, to investigate many peaks in parallel and to reduce…

Neural and Evolutionary Computing · Computer Science 2018-05-04 Edgar Covantes Osuna , Dirk Sudholt

We show that for unconstrained Deep Linear Discriminant Analysis (LDA) classifiers, maximum-likelihood training admits pathological solutions in which class means drift together, covariances collapse, and the learned representation becomes…

Machine Learning · Statistics 2026-01-06 Maxat Tezekbayev , Rustem Takhanov , Arman Bolatov , Zhenisbek Assylbekov

We prove existence and uniqueness of strong solutions, as well as continuous dependence on the initial datum, for a class of fully nonlinear second-order stochastic PDEs with drift in divergence form. Due to rather general assumptions on…

Analysis of PDEs · Mathematics 2018-10-03 Carlo Marinelli , Luca Scarpa

In many real-world decision making problems, reaching an optimal decision requires taking into account a variable number of objects around the agent. Autonomous driving is a domain in which this is especially relevant, since the number of…

Machine Learning · Computer Science 2020-08-13 Maria Hügle , Gabriel Kalweit , Branka Mirchevska , Moritz Werling , Joschka Boedecker

Real-world problems of operations research are typically high-dimensional and combinatorial. Linear programs are generally used to formulate and efficiently solve these large decision problems. However, in multi-period decision problems, we…

Machine Learning · Computer Science 2019-02-27 Wouter van Heeswijk , Han La Poutré

Educational policymakers often lack data on student outcomes where standardized tests were not administered. Machine learning can predict unobserved outcomes in target populations using source population data. However, covariate…

While many real-world data streams imply that they change frequently in a nonstationary way, most of deep learning methods optimize neural networks on training data, and this leads to severe performance degradation when dataset shift…

Machine Learning · Computer Science 2021-07-02 Wonju Lee , Seok-Yong Byun , Jooeun Kim , Minje Park , Kirill Chechil

The dynamics of disordered two-dimensional systems is much less understood than the dynamics of disordered chains, mainly due to the lack of appropriate numerical methods. We demonstrate that a single-trajectory version of the fermionic…

Statistical Mechanics · Physics 2024-09-20 Łukasz Iwanek , Marcin Mierzejewski , Anatoli Polkovnikov , Dries Sels , Adam S. Sajna

Dynamical systems with quadratic or polynomial drift exhibit complex dynamics, yet compared to nonlinear systems in general form, are often easier to analyze, simulate, control, and learn. Results going back over a century have shown that…

Symbolic Computation · Computer Science 2025-02-17 Boris Kramer , Gleb Pogudin

Introducing certain singularities, we generalize the class of one-dimensional stochastic differential equations with so-called generalized drift. Equations with generalized drift, well-known in the literature, possess a drift that is…

Probability · Mathematics 2013-10-22 Stefan Blei , Hans-Jürgen Engelbert

Dynamic decisions are pivotal to economic policy making. We show how existing evidence from randomized control trials can be utilized to guide personalized decisions in challenging dynamic environments with budget and capacity constraints.…

Econometrics · Economics 2024-11-26 Karun Adusumilli , Friedrich Geiecke , Claudio Schilter

The use of the two-way fixed effects regression in empirical social science was historically motivated by folk wisdom that it uncovers the Average Treatment effect on the Treated (ATT) as in the canonical two-period two-group case. This…

Econometrics · Economics 2025-03-10 Apoorva Lal

Accurate energy consumption prediction is crucial for optimizing the operation of electric commercial heavy-duty vehicles, e.g., route planning for charging. Moreover, understanding why certain predictions are cast is paramount for such a…

Machine Learning · Computer Science 2023-11-28 Yuantao Fan , Zhenkan Wang , Sepideh Pashami , Slawomir Nowaczyk , Henrik Ydreskog

This paper is devoted to variational problems on the set of probability measures which involve optimal transport between unequal dimensional spaces. In particular, we study the minimization of a functional consisting of the sum of a term…

Analysis of PDEs · Mathematics 2019-11-18 Luca Nenna , Brendan Pass

We study the distributional properties of the linear discriminant function under the assumption of normality by comparing two groups with the same covariance matrix but different mean vectors. A stochastic representation for the…

Statistics Theory · Mathematics 2017-05-09 Taras Bodnar , Stepan Mazur , Edward Ngailo , Nestor Parolya

Time Series Forecasting is at the core of many practical applications such as sales forecasting for business, rainfall forecasting for agriculture and many others. Though this problem has been extensively studied for years, it is still…

Machine Learning · Computer Science 2020-03-23 Anirban Chatterjee , Subhadip Paul , Uddipto Dutta , Smaranya Dey

For many complex diseases, prognosis is of essential importance. It has been shown that, beyond the main effects of genetic (G) and environmental (E) risk factors, the gene-environment (G$\times$E) interactions also play a critical role. In…

Applications · Statistics 2015-05-15 Hao Chai , Qingzhao Zhang , Yu Jiang , Guohua Wang , Sanguo Zhang , Shuangge Ma

We solve two continuous extremal problems on the classes of monotone functions: in the first problem we find extremal values for a line integral of a coordinate-wise monotone function of two variables from a rearrange\-ment-invariant class…

Functional Analysis · Mathematics 2026-03-03 Oleg Kovalenko

We investigated different dense multirotor UAV traffic simulation scenarios in open 2D and 3D space, under realistic environments with the presence of sensor noise, communication delay, limited communication range, limited sensor update…

Adaptation and Self-Organizing Systems · Physics 2016-11-28 Csaba Virágh , Máté Nagy , Carlos Gershenson , Gábor Vásárhelyi

In dynamical systems governed by differential equations, a guarantee that trajectories emanating from a given set of initial conditions do not enter another given set can be obtained by constructing a barrier function that satisfies certain…

Chaotic Dynamics · Physics 2022-05-26 Jeremy P Parker , David Goluskin , Geoffrey M Vasil
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