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We study numerically the ordering kinetics in a two-dimensional Ising model with random coupling where the fraction of antiferromagnetic links $a$ can be gradually tuned. We show that, upon increasing such fraction, the behavior changes in…

Statistical Mechanics · Physics 2021-01-12 Manoj Kumar , Federico Corberi , Eugenio Lippiello , Sanjay Puri

We propose a principled method for autoencoding with random forests. Our strategy builds on foundational results from nonparametric statistics and spectral graph theory to learn a low-dimensional embedding of the model that optimally…

Machine Learning · Statistics 2026-01-16 Binh Duc Vu , Jan Kapar , Marvin Wright , David S. Watson

We study the role of demographic fluctuations in typical endemics as exemplified by the stochastic SIRS model. The birth-death master equation of the model is simulated using exact numerics and analysed within the linear noise…

Statistical Mechanics · Physics 2011-06-29 Somdeb Ghose , R. Adhikari

This paper addresses optimal decoding strategies in lossy compression where the assumed distribution for compressor design mismatches the actual (true) distribution of the source. This problem has immediate relevance in standardized…

Information Theory · Computer Science 2026-02-04 Saeed R. Khosravirad , Ahmed Alkhateeb , Ingrid van de Voorde

As researchers collect increasingly large molecular data sets to reconstruct the Tree of Life, the heterogeneity of signals in the genomes of diverse organisms poses challenges for traditional phylogenetic analysis. A class of phylogenetic…

Populations and Evolution · Quantitative Biology 2015-09-11 Liang Liu , Zhenxiang Xi , Shaoyuan Wu , Charles Davis , Scott V. Edwards

For reliable transmission across a noisy communication channel, classical results from information theory show that it is asymptotically optimal to separate out the source and channel coding processes. However, this decomposition can fall…

Machine Learning · Computer Science 2019-05-15 Kristy Choi , Kedar Tatwawadi , Aditya Grover , Tsachy Weissman , Stefano Ermon

Recursive learning -- where models are trained on data generated by previous versions of themselves -- is increasingly common in large language models, autonomous agents, and self-supervised systems. However, standard performance metrics…

Machine Learning · Computer Science 2026-05-20 Zhipeng Zhang

This work addresses the problem of error concealment in video transmission systems over noisy channels employing Bregman divergences along with regularization. Error concealment intends to improve the effects of disturbances at the…

Computer Vision and Pattern Recognition · Computer Science 2016-11-11 Alessandra M. Coelho , Vania V. Estrela , Felipe P. do Carmo , Sandro R. Fernandes

Gene regulatory networks can be successfully modeled as Boolean networks. A much discussed hypothesis says that such model networks reproduce empirical findings the best if they are tuned to operate at criticality, i.e. at the borderline…

Molecular Networks · Quantitative Biology 2016-10-12 Pablo Villegas , José Ruiz-Franco , Jorge Hidalgo , Miguel A. Muñoz

Evolutionary events such as incomplete lineage sorting and lateral gene transfer constitute major problems for inferring species trees from gene trees, as they can sometimes lead to gene trees which conflict with the underlying species…

Populations and Evolution · Quantitative Biology 2013-04-23 Andreas Sand , Mike Steel

We use a natural ordered extension of the Chinese Restaurant Process to grow a two-parameter family of binary self-similar continuum fragmentation trees. We provide an explicit embedding of Ford's sequence of alpha model trees in the…

Probability · Mathematics 2009-09-25 Jim Pitman , Matthias Winkel

Reconstructing the tree of life from molecular sequences is a fundamental problem in computational biology. Modern data sets often contain a large number of genes, which can complicate the reconstruction problem due to the fact that…

Probability · Mathematics 2017-07-21 Constantinos Daskalakis , Sebastien Roch

This work considers distributed sensing and transmission of sporadic random samples. Lower bounds are derived for the reconstruction error of a single normally or uniformly-distributed finite-dimensional vector imperfectly measured by a…

Information Theory · Computer Science 2015-11-20 Ayşe Ünsal , Raymond Knopp

We consider a pruning of the inhomogeneous continuum random trees, as well as the cut trees that encode the genealogies of the fragmentations that come with the pruning. We propose a new approach to the reconstruction problem, which has…

Probability · Mathematics 2023-02-03 Nicolas Broutin , Hui He , Minmin Wang

Modern deep neural networks display striking examples of rich internal computational structure. Uncovering principles governing the development of such structure is a priority for the science of deep learning. In this paper, we explore the…

Machine Learning · Computer Science 2025-02-03 Liam Carroll , Jesse Hoogland , Matthew Farrugia-Roberts , Daniel Murfet

Recent work has shown that Transformers can perform in-context learning for linear regression under restrictive assumptions, including i.i.d. data, Gaussian noise, and Gaussian regression coefficients. However, real-world data often violate…

Machine Learning · Computer Science 2026-03-20 Hoang T. H. Cao , Hai D. V. Trinh , Tho Quan , Lan V. Truong

Poisson distributed measurements in inverse problems often stem from Poisson point processes that are observed through discretized or finite-resolution detectors, one of the most prominent examples being positron emission tomography (PET).…

Statistics Theory · Mathematics 2024-07-25 Marco Mauritz , Benedikt Wirth

There is a widespread and longstanding belief that machine learning models are biased towards the majority class when learning from imbalanced binary response data, leading them to neglect or ignore the minority class. Motivated by a recent…

Machine Learning · Statistics 2026-01-29 Nathan Phelps , Daniel J. Lizotte , Douglas G. Woolford

We consider the parameterized version of the maximum internal spanning tree problem, which, given an $n$-vertex graph and a parameter $k$, asks for a spanning tree with at least $k$ internal vertices. Fomin et al. [J. Comput. System Sci.,…

Data Structures and Algorithms · Computer Science 2014-12-30 Wenjun Li , Jianxin Wang , Jianer Chen , Yixin Cao

The sequence reconstruction problem involves a model where a sequence is transmitted over several identical channels. This model investigates the minimum number of channels required for the unique reconstruction of the transmitted sequence.…

Information Theory · Computer Science 2025-04-30 Zhaojun Lan , Yubo Sun , Wenjun Yu , Gennian Ge
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