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Machine learning models deployed in nonstationary environments inevitably experience performance degradation due to data drift. While numerous drift detection heuristics exist, most lack a dynamical interpretation and provide limited…

Machine Learning · Computer Science 2026-01-19 Lennon Shikhman

The R\'{e}nyi $\alpha$-entropy $H_{\alpha}$ of complete antisymmetric directed graphs (i.e., tournaments) is explored. We optimize $H_{\alpha}$ when $\alpha = 2$ and $3$, and find that as $\alpha$ increases $H_{\alpha}$'s sensitivity to…

Combinatorics · Mathematics 2019-01-04 David E. Brown , Eric Culver , Bryce Frederickson , Sidney Tate , Brent J. Thomas

Entropy rate of sequential data-streams naturally quantifies the complexity of the generative process. Thus entropy rate fluctuations could be used as a tool to recognize dynamical perturbations in signal sources, and could potentially be…

Information Theory · Computer Science 2014-03-24 Ishanu Chattopadhyay , Hod Lipson

Risk-sensitive planning aims to identify policies maximizing some tail-focused metrics in Markov Decision Processes (MDPs). Such an optimization task can be very costly for the most widely used and interpretable metrics such as threshold…

Machine Learning · Statistics 2025-07-09 Alexandre Marthe , Samuel Bounan , Aurélien Garivier , Claire Vernade

We study in experiment and with computer simulation the free energy and the kinetics of vacancy and interstitial defects in two-dimensional dipolar crystals. The defects appear in different local topologies which we characterize by their…

Soft Condensed Matter · Physics 2015-06-23 Wolfgang Lechner , David Polster , Georg Maret , Christoph Dellago , Peter Keim

Understanding and optimizing passive scalar mixing in a diffusive fluid flow at finite P\'eclet number $Pe=U h/\kappa$ (where $U$ and $h$ are characteristic velocity and length scales, and $\kappa$ is the molecular diffusivisity of the…

Fluid Dynamics · Physics 2022-05-18 Conor Heffernan , Colm-cille Caulfield

Several distributed frameworks have been developed to scale Graph Neural Networks (GNNs) on billion-size graphs. On several benchmarks, we observe that the graph partitions generated by these frameworks have heterogeneous data distributions…

Machine Learning · Computer Science 2023-11-07 Dhruv Deshmukh , Gagan Raj Gupta , Manisha Chawla , Vishwesh Jatala , Anirban Haldar

We study a quantity called discrete layered entropy, which approximates the Shannon entropy within a logarithmic gap. Compared to the Shannon entropy, the discrete layered entropy is piecewise linear, approximates the expected length of the…

Information Theory · Computer Science 2026-01-27 Cheuk Ting Li

In this paper, we demonstrate how the physics of entropy production, when combined with symmetry constraints, can be used for implementing high-performance and energy-efficient analog computing systems. At the core of the proposed framework…

Neural and Evolutionary Computing · Computer Science 2025-10-30 Aswin Undavalli , Kareem Rashed , Zhili Xiao , Arun Natarajan , Shantanu Chakrabartty , Aravind Nagulu

The knowledge distillation uses a high-performance teacher network to guide the student network. However, the performance gap between the teacher and student networks can affect the student's training. This paper proposes a novel knowledge…

Computer Vision and Pattern Recognition · Computer Science 2023-05-10 Songling Zhu , Ronghua Shang , Bo Yuan , Weitong Zhang , Yangyang Li , Licheng Jiao

Point-to-multi-point (PtMP) optical networks become the main solutions for network-edge applications such as passive optical networks and radio access networks. Entropy-loading digital subcarrier multiplexing (DSCM) is the core technology…

Information Theory · Computer Science 2023-10-20 Ji Zhou , Haide Wang , Liangchuan Li , Weiping Liu , Changyuan Yu , Zhaohui Li

A new nonparametric approach for system identification has been recently proposed where the impulse response is seen as the realization of a zero--mean Gaussian process whose covariance, the so--called stable spline kernel, guarantees that…

Statistics Theory · Mathematics 2016-11-18 Francesca Paola Carli

Many foraging microorganisms rely upon cellular transport networks to deliver nutrients, fluid and organelles between different parts of the organism. Networked organisms ranging from filamentous fungi to slime molds demonstrate a…

Adaptation and Self-Organizing Systems · Physics 2020-12-08 Cassidy Mentus , Marcus Roper

Let $Y$ be a topological Markov chain with finite leading and follower sets. Special flow over $Y$ whose height function depends on the time zero of elements of $Y$ is constructed. Then a formula for computing the entropy of this flow will…

Dynamical Systems · Mathematics 2011-01-25 Dawoud Ahmadi Dastjerdi , Sanaz Lamei

We explore the properties of run-and-tumble particles moving in a piecewise-linear "ratchet" potential by deriving analytic results for the system's steady-state probability density, current, entropy production rate, extractable power, and…

Statistical Mechanics · Physics 2023-08-01 Connor Roberts , Zigan Zhen

Given a compact topological dynamical system (X, f) with positive entropy and upper semi-continuous entropy map, and any closed invariant subset $Y \subset X$ with positive entropy, we show that there exists a continuous roof function such…

Dynamical Systems · Mathematics 2021-01-29 Tamara Kucherenko , Daniel J. Thompson

In this paper, we study ergodic optimization of continuous functions for flows by concentrating on the entropy spectrum of their maximizing measures. Precisely, over a wide family of flows with non-uniformly hyperbolic structure, we obtain…

Dynamical Systems · Mathematics 2026-02-09 Qiao Liu , Tianyu Wang , Weisheng Wu

Numerous approximation algorithms for problems on unit disk graphs have been proposed in the literature, exhibiting a sharp trade-off between running times and approximation ratios. We introduce a variation of the known shifting strategy…

Data Structures and Algorithms · Computer Science 2016-11-08 Guilherme D. da Fonseca , Vinícius G. Pereira de Sá , Celina M. H. de Figueiredo

A data structure is presented for point location in connected planar subdivisions when the distribution of queries is known in advance. The data structure has an expected query time that is within a constant factor of optimal. More…

Computational Geometry · Computer Science 2013-03-12 Sebastien Collette , Vida Dujmovic , John Iacono , Stefan Langerman , Pat Morin

We study the $\pi^+ p$ elastic scattering process using an effective Lagrangian approach that incorporates the $s$-, $u$-, and $t$-channel amplitudes, including $\Delta^{++}(1232)$, $\Delta^{0}(1232)$, neutron, and $\rho^0$ contributions.…

High Energy Physics - Phenomenology · Physics 2025-12-09 Seung-il Nam
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