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We study model-agnostic copies of machine learning classifiers. We develop the theory behind the problem of copying, highlighting its differences with that of learning, and propose a framework to copy the functionality of any classifier…

Machine Learning · Computer Science 2020-01-13 Irene Unceta , Jordi Nin , Oriol Pujol

In modern communication systems such as the Internet, random losses of information can be mitigated by oversampling the source. This is equivalent to expanding the source using overcomplete systems of vectors (frames), as opposed to the…

Functional Analysis · Mathematics 2025-10-20 Roman Vershynin

Task replication has recently been advocated as a practical solution to reduce latencies in parallel systems. In addition to several convincing empirical studies, some others provide analytical results, yet under some strong assumptions…

Performance · Computer Science 2016-02-26 Felix Poloczek , Florin Ciucu

In this paper, we consider a series of events observed at spaced time intervals and present a method of representation of the series. To explain an idea, by dealing with a set of gene expression data, which could be obtained from…

Computational Complexity · Computer Science 2007-05-23 Gene Kim , MyungHo Kim

We present the results of detailed numerical study of a model for the sharing and sorting of informations in a community consisting of a large number of agents. The information gathering takes place in a sequence of mutual bipartite…

Physics and Society · Physics 2015-06-16 Biplab Bhattacherjee , S. S. Manna , Animesh Mukherjee

This paper presents a new foundational approach to information theory based on the concept of the information efficiency of a recursive function, which is defined as the difference between the information in the input and the output. The…

Information Theory · Computer Science 2023-08-29 Pieter Adriaans

Living systems transmit heritable information using the replicating gene sequences and the cycling regulators assembled around gene sequences. Here I develop a framework for heredity and development that includes the cycling regulators…

Other Quantitative Biology · Quantitative Biology 2020-03-03 Antony M Jose

This paper analyses a system subject to multiple dependent degradation processes. Degradation processes start at random times following a non homogeneous Poisson process and next dependently propagate. The growth of these degradation…

Probability · Mathematics 2024-01-18 Inma T. Castro , L. Landesa

Diffusion models are a class of generative models that learn to synthesize samples by inverting a diffusion process that gradually maps data into noise. While these models have enjoyed great success recently, a full theoretical…

Machine Learning · Computer Science 2023-09-22 Raja Marjieh , Ilia Sucholutsky , Thomas A. Langlois , Nori Jacoby , Thomas L. Griffiths

A reduction of a source distribution is a collection of smaller sized distributions that are collectively equivalent to the source distribution with respect to the property of decomposability. That is, an arbitrary language is decomposable…

Systems and Control · Computer Science 2018-03-30 Liyong Lin , Tomáš Masopust , W. Murray Wonham , Rong Su

In computational inverse problems, it is common that a detailed and accurate forward model is approximated by a computationally less challenging substitute. The model reduction may be necessary to meet constraints in computing time when…

Methodology · Statistics 2018-02-14 Daniela Calvetti , Matthew M. Dunlop , Erkki Somersalo , Andrew M. Stuart

An equation describing the evolution of phenotypic distribution is derived using methods developed in statistical physics. The equation is solved by using the singular perturbation method, and assuming that the number of bases in the…

Populations and Evolution · Quantitative Biology 2009-11-13 Katsuhiko Sato , Kunihiko Kaneko

Exemplar-based class-incremental learning is to recognize new classes while not forgetting old ones, whose samples can only be saved in limited memory. The ratio fluctuation of new samples to old exemplars, which is caused by the variation…

Computer Vision and Pattern Recognition · Computer Science 2022-02-22 Zhiheng Liu , Kai Zhu , Yang Cao

One of the defining features of living systems is their adaptability to changing environmental conditions. This requires organisms to extract temporal and spatial features of their environment, and use that information to compute the…

Neurons and Cognition · Quantitative Biology 2024-02-27 Maria Sol Vidal-Saez , Oscar Vilarroya , Jordi Garcia-Ojalvo

Computer modelling for evolutionary systems consists in: 1) to store in the memory the individual features of each member of a large population; and 2) to update the whole system repeatedly, as time goes by, according to some prescribed…

Statistical Mechanics · Physics 2007-05-23 Paulo Murilo Castro de Oliveira

Imitation learning aims to extract knowledge from human experts' demonstrations or artificially created agents in order to replicate their behaviors. Its success has been demonstrated in areas such as video games, autonomous driving,…

Machine Learning · Computer Science 2022-10-24 Boyuan Zheng , Sunny Verma , Jianlong Zhou , Ivor Tsang , Fang Chen

A central challenge in continual learning is forgetting, the loss of performance on previously learned tasks induced by sequential adaptation to new ones. While forgetting has been extensively studied empirically, rigorous theoretical…

Machine Learning · Computer Science 2026-04-16 Zonghuan Xu , Xingjun Ma

Suppose we have $n$ different types of self-replicating entity, with the population $P_i$ of the $i$th type changing at a rate equal to $P_i$ times the fitness $f_i$ of that type. Suppose the fitness $f_i$ is any continuous function of all…

Populations and Evolution · Quantitative Biology 2021-11-24 John C. Baez

The problem of reconstructing a sequence of independent and identically distributed symbols from a set of equal size, consecutive, fragments, as well as a dependent reference sequence, is considered. First, in the regime in which the…

Information Theory · Computer Science 2023-07-20 Nir Weinberger , Ilan Shomorony

Distributed storage systems with replication are well known for storing large amount of data. A large number of replication is done in order to provide reliability. This makes the system expensive. Various methods have been proposed over…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-01 Mit Sheth , Krishna Gopal Benerjee , Manish K. Gupta
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