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Data complexity is an important concept in the natural sciences and related areas, but lacks a rigorous and computable definition. In this paper, we focus on a particular sense of complexity that is high if the data is structured in a way…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Louis Mahon

Approximate message passing (AMP) is an algorithmic framework for solving linear inverse problems from noisy measurements, with exciting applications such as reconstructing images, audio, hyper spectral images, and various other signals,…

Information Theory · Computer Science 2017-02-13 Junan Zhu , Ryan Pilgrim , Dror Baron

In a previous report we have evaluated analytically the mutual information between the firing rates of N independent units and a set of multi-dimensional continuous+discrete stimuli, for a finite population size and in the limit of large…

Disordered Systems and Neural Networks · Physics 2007-05-23 Valeria Del Prete , Alessandro Treves

It is shown that coherence resonance, a phenomenon in which regularity of noise-induced oscillations in nonlinear excitable systems is maximized at a certain optimal noise intensity, can be observed in quantum dissipative systems. We…

Adaptation and Self-Organizing Systems · Physics 2021-04-12 Yuzuru Kato , Hiroya Nakao

Multitarget tracking in the interference environments suffers from the nonuniform, unknown and time-varying clutter, resulting in dramatic performance deterioration. We address this challenge by proposing a robust multitarget tracking…

Systems and Control · Electrical Eng. & Systems 2022-12-15 Xianglong Bai , Hua Lan , Zengfu Wang , Quan Pan , Yuhang Hao , Can Li

Preference handling and optimization are indispensable means for addressing non-trivial applications in Answer Set Programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in…

Logic in Computer Science · Computer Science 2011-07-29 Martin Gebser , Roland Kaminski , Torsten Schaub

Many phenomena can be modeled as network dynamics with punctuate interactions. However, most relevant dynamics do not allow for computational tractability. To circumvent this difficulty, the Poisson Hypothesis regime replaces interaction…

Probability · Mathematics 2024-03-22 Michel Davydov

Mixed integer sets have a strong modeling capacity to describe practical systems. Nevertheless, incorporating a mixed integer set often renders an optimization formulation drastically more challenging to compute. In this paper, we study how…

Optimization and Control · Mathematics 2023-12-22 Wei Wang , Bo Zeng

A method is suggested for treating those complicated physical problems for which exact solutions are not known but a few approximation terms of a calculational algorithm can be derived. The method permits one to answer the following rather…

High Energy Physics - Phenomenology · Physics 2009-10-31 V. I. Yukalov , E. P. Yukalova

A resilient state estimation scheme for uniformly observable nonlinear systems, based on a method for local identification of sensor attacks, is presented. The estimation problem is combinatorial in nature, and so many methods require…

Systems and Control · Electrical Eng. & Systems 2023-04-19 Junsoo Kim , Jin Gyu Lee , Henrik Sandberg , Karl H. Johansson

The wave properties of complex scattering systems that are large compared to the wavelength, and show chaos in the classical limit, are extremely sensitive to system details. A solution to the wave equation for a specific configuration can…

Disordered Systems and Neural Networks · Physics 2019-12-24 Shukai Ma , Bo Xiao , Ron Hong , Bisrat Addissie , Zachary Drikas , Thomas Antonsen , Edward Ott , Steven Anlage

Monitoring is an important aspect of safely deploying Large Language Models (LLMs). This paper examines activation probes for detecting ``high-stakes'' interactions -- where the text indicates that the interaction might lead to significant…

We provide a computational complexity lens to understand the power of machine learning models, particularly their ability to model complex systems. Machine learning models are often trained on data drawn from sampleable or more complex…

Machine Learning · Computer Science 2026-04-09 Lance Fortnow

Information flow provides a natural measure for the causal interaction between dynamical events. This study extends our previous rigorous formalism of componentwise information flow to the bulk information flow between two complex…

Neurons and Cognition · Quantitative Biology 2021-12-30 X. San Liang

We propose a general modeling framework for marked Poisson processes observed over time or space. The modeling approach exploits the connection of the nonhomogeneous Poisson process intensity with a density function. Nonparametric Dirichlet…

Methodology · Statistics 2011-11-02 Matthew A. Taddy , Athanasios Kottas

The intensity of a Gibbs point process is usually an intractable function of the model parameters. For repulsive pairwise interaction point processes, this intensity can be expressed as the Laplace transform of some particular function.…

Methodology · Statistics 2017-12-11 Jean-François Coeurjolly , Frédéric Lavancier

Efficient probability density estimation is a core challenge in statistical machine learning. Tensor-based probabilistic graph methods address interpretability and stability concerns encountered in neural network approaches. However, a…

Machine Learning · Computer Science 2023-12-14 Ruituo Wu , Jiani Liu , Ce Zhu , Anh-Huy Phan , Ivan V. Oseledets , Yipeng Liu

Composite systems, where couplings are of two types, a combination of strong dilute and weak dense couplings of Ising spins, are examined through the replica method. The dilute and dense parts are considered to have independent canonical…

Disordered Systems and Neural Networks · Physics 2009-11-13 Jack Raymond , David Saad

We consider the intensity pattern, generated by a monochromatic source, in a disordered cavity coupled to the environment. For weak coupling, and when the source frequency is tuned to a resonance, the intensity distribution is close to…

Condensed Matter · Physics 2009-10-28 R. Pnini , B. Shapiro

The apparent dichotomy between information-processing and dynamical approaches to complexity science forces researchers to choose between two diverging sets of tools and explanations, creating conflict and often hindering scientific…

Neurons and Cognition · Quantitative Biology 2022-01-26 Pedro A. M. Mediano , Fernando E. Rosas , Juan Carlos Farah , Murray Shanahan , Daniel Bor , Adam B. Barrett