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In reinforcement learning episodes, the rewards and punishments are often non-deterministic, and there are invariably stochastic elements governing the underlying situation. Such stochastic elements are often numerous and cannot be known in…

Machine Learning · Computer Science 2019-02-13 Nikki Lijing Kuang , Clement H. C. Leung , Vienne W. K. Sung

Specialization and diversification are two major strategies that complex systems might exploit. Given a fixed amount of resources, the question is whether to invest this in elements that respond in a correlated manner to external…

Physics and Society · Physics 2014-11-19 Gabriell Mate , Zoltan Neda

Based on the physics of stochastic processes we present a new approach for structural health monitoring. We show that the new method allows for an in-situ analysis of the elastic features of a mechanical structure even for realistic…

Data Analysis, Statistics and Probability · Physics 2013-01-08 Philip Rinn , Hendrik Heißelmann , Matthias Wächter , Joachim Peinke

Random substitutions are a natural generalisation of their classical `deterministic' counterpart, whereby at every step of iterating the substitution, instead of replacing a letter with a predetermined word, every letter is independently…

Dynamical Systems · Mathematics 2020-04-14 Dan Rust , Timo Spindeler

The dynamics of well-mixed biological populations is usually studied by mean-field methods and weak-noise expansions. Similar methods have been applied also in spatially extended problems, relying on the fact that these populations are…

Statistical Mechanics · Physics 2015-03-17 Luca Dall'Asta , Fabio Caccioli , Deborah Beghè

I study dynamic random utility with finite choice sets and exogenous total menu variation, which I refer to as stochastic utility (SU). First, I characterize SU when each choice set has three elements. Next, I prove several mathematical…

Theoretical Economics · Economics 2022-06-22 Ricky Li

Just as user preferences change with time, item reviews also reflect those same preference changes. In a nutshell, if one is to sequentially incorporate review content knowledge into recommender systems, one is naturally led to dynamical…

Information Retrieval · Computer Science 2022-03-23 Kostadin Cvejoski , Ramses J. Sanchez , Christian Bauckhage , Cesar Ojeda

We study the collective behaviour of an ensemble of coupled motile elements whose interactions depend on time and are alternatively attractive or repulsive. The evolution of interactions is driven by individual internal variables with…

Statistical Mechanics · Physics 2009-11-10 Damian H. Zanette , Alexander S. Mikhailov

We study a distributed learning process observed in human groups and other social animals. This learning process appears in settings in which each individual in a group is trying to decide over time, in a distributed manner, which option to…

Machine Learning · Computer Science 2017-05-10 L. Elisa Celis , Peter M. Krafft , Nisheeth K. Vishnoi

Given a malfunctioning system, sequential diagnosis aims at identifying the root cause of the failure in terms of abnormally behaving system components. As initial system observations usually do not suffice to deterministically pin down…

Artificial Intelligence · Computer Science 2022-08-08 Patrick Rodler , Wolfgang Schmid

Dynamical systems are used to model a variety of phenomena in which the bifurcation structure is a fundamental characteristic. Here we propose a statistical machine-learning approach to derive lowdimensional models that automatically…

Quantitative Methods · Quantitative Biology 2015-06-11 Yohei Kondo , Kunihiko Kaneko , Shuji Ishihara

We use numerical simulations to explore biases that arise in dynamical estimates of the mean mass profile for a collection of galaxy clusters that have been stacked to make a composite. There are three types of bias. One arises from…

Cosmology and Nongalactic Astrophysics · Physics 2025-06-16 Yan-Chuan Cai , Nick Kaiser , Shaun Cole , Carlos Frenk

Randomized experiments are the gold standard for evaluating the effects of changes to real-world systems. Data in these tests may be difficult to collect and outcomes may have high variance, resulting in potentially large measurement error.…

Machine Learning · Statistics 2018-06-27 Benjamin Letham , Brian Karrer , Guilherme Ottoni , Eytan Bakshy

Many real-world optimisation problems involve dynamic and stochastic components. While problems with multiple interacting components are omnipresent in inherently dynamic domains like supply-chain optimisation and logistics, most research…

Neural and Evolutionary Computing · Computer Science 2020-09-16 Ragav Sachdeva , Frank Neumann , Markus Wagner

We study a simple model of the stochastic information filtering, in a randomly organized information system. For simplest versions of the model it appears to be possible to describe the filtering dynamics in terms of the master equations.…

Disordered Systems and Neural Networks · Physics 2009-11-07 I. S. Manida , Yu. M. Pis'mak

Amorphous materials driven away from equilibrium display a diverse repertoire of complex, history-dependent behaviors. One striking feature is a failure to return to equilibrium after an abrupt change in otherwise static external…

Soft Condensed Matter · Physics 2025-06-12 Dor Shohat , Paul Baconnier , Itamar Procaccia , Martin van Hecke , Yoav Lahini

Deep metric learning maps visually similar images onto nearby locations and visually dissimilar images apart from each other in an embedding manifold. The learning process is mainly based on the supplied image negative and positive training…

Computer Vision and Pattern Recognition · Computer Science 2020-09-14 Chang-Hui Liang , Wan-Lei Zhao , Run-Qing Chen

The dynamics of a spring-block train placed on a moving conveyor belt is investigated both by simple experiments and computer simulations. The first block is connected by spring to an external static point, and due to the dragging effect of…

Chaotic Dynamics · Physics 2016-05-20 Bulcsú Sándor , Ferenc Járai-Szabó , Tamás Tél , Zoltán Néda

For three natural classes of dynamic decision problems; 1. additively separable problems, 2. discounted problems, and 3. discounted problems for a fixed discount factor; we provide necessary and sufficient conditions for one sequential…

Theoretical Economics · Economics 2024-05-24 Mark Whitmeyer , Cole Williams

We consider the problem of selecting a subset of alternatives given noisy evaluations of the relative strength of different alternatives. We wish to select a k-subset (for a given k) that provides a maximum likelihood estimate for one of…

Artificial Intelligence · Computer Science 2012-10-19 Ariel D. Procaccia , Sashank J. Reddi , Nisarg Shah