18 papers · ranked by Valyu relevance
Gengsheng L. Zeng
A restricted Boltzmann machine is a fully connected shallow neural network. It can be used to solve many challenging optimization problems. The Boltzmann machines are usually considered probability models. Probability models normally use nondeterministic algorithms to solve their parameters. The Hopfield network which…
Artur Czumaj, Peter Davies-Peck, Merav Parter
In this paper, we study the power and limitations of component-stable algorithms in the low-space model of massively parallel computation (MPC). Recently Ghaffari, Kuhn and Uitto (FOCS 2019) introduced the class of component-stable low-space MPC algorithms, which are, informally, those algorithms for which the outputs…
Travis Sanchez, Karin Bosh, Ted Enamorado, Tigran Avoundjian + 6 more
'Julia C Dombrowski' 'Matthew R Golden' 'James P Hughes' 'Brandon L Guthrie' 'Janet Baseman' 'Mauricio Sadinle'] Background Many public health departments use record linkage between surveillance data and external data sources to inform public health interventions. However, little guidance is available to inform these…
Susanne Albers, Maximilian Janke
Makespan minimization on identical machines is a fundamental problem in online scheduling. The goal is to assign a sequence of jobs to m identical parallel machines so as to minimize the maximum completion time of any job. Already in the 1960s, Graham showed that Greedy is $2-1/m$-competitive. The best deterministic…
Ming-Yan Gong, Bin Lyu, Chee Kiat Seow, Henrik Hesse + 3 more
'Soon Yim Tan' 'Yunjia Wang'] The existing expectation maximization (EM) and space-alternating generalized EM (SAGE) algorithms are only applied to direction of arrival (DOA) estimation in known noise. In this paper, the two algorithms are designed for DOA estimation in unknown uniform noise. Both the deterministic and…
Wolfram Barfuss
A dynamical systems perspective on multi-agent learning, based on the link between evolutionary game theory and reinforcement learning, provides an improved, qualitative understanding of the emerging collective learning dynamics. However, confusion exists with respect to how this dynamical systems account of…
Benjamin D. Johnson, James P. Crutchfield, Christopher J. Ellison, Carl S. McTague + 1 more
'Carl S. McTague' 'Nikolai Leonenko'] We show how to efficiently enumerate a class of finite-memory stochastic processes using the causal representation of $ϵ$-machines. We characterize $ϵ$-machines in the language of automata theory and adapt a recent algorithm for generating accessible deterministic finite automata…
Sander Borst, Daniel Dadush, Sophie Huiberts, Danish Kashaev
Explorable heap selection is the problem of selecting the nth smallest value in a binary heap. The key values can only be accessed by traversing through the underlying infinite binary tree, and the complexity of the algorithm is measured by the total distance traveled in the tree (each edge has unit cost). This problem…
Michał Ćwik, Jerzy Józefczyk
An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete…
Hiroki Takizawa, Jiachen Yang
Pure strategy board games such as chess are popular intellectual activities, and solving them is a challenging task in computer science. In addition to traditional games, many new board games have gained popularity in recent years. Ostle is one such unsolved game published in 2017. It is based on simple rules but is…
Véronique Millette, Natalie Baddour
Background Heart signals represent an important way to evaluate cardiovascular function and often what is desired is to quantify the level of some signal of interest against the louder backdrop of the beating of the heart itself. An example of this type of application is the quantification of cavitation in mechanical…
Kun Tu, Dariusz Puchala, Jun Chen, Sadaf Salehkalaibar
In this paper, we address the problem of m-gram entropy variable-to-variable coding, extending the classical Huffman algorithm to the case of coding m-element (i.e., m-grams) sequences of symbols taken from the stream of input data for $m>1$. We propose a procedure to enable the determination of the frequencies of the…
Mengqi Zhang, Guangqiang Teng, Xiaoyu Lei, Boris Ryabko
Lei proposed an algorithm Algorithm $A_{3}$ in 2023 to generate an exact discrete uniform distribution from an unknown biased Bernoulli source. The present paper does not claim a new extraction algorithm. Its contributions are analytical: first, we provide a Fourier-analytic proof of the uniformity mechanism based on…
Cliff C. Kerr, Salvador Dura-Bernal, Tomasz G. Smolinski, George L. Chadderdon + 2 more
'George L. Chadderdon' 'David P. Wilson' 'Lars Kaderali'] When standard optimization methods fail to find a satisfactory solution for a parameter fitting problem, a tempting recourse is to adjust parameters manually. While tedious, this approach can be surprisingly powerful in terms of achieving optimal or near-optimal…
Stefan Kiefer, Richard Mayr, Mahsa Shirmohammadi, Patrick Totzke
We study countably infinite Markov decision processes with Büchi objectives, which ask to visit a given subset of states infinitely often. A question left open by T.P. Hill ([10]) is whether there always exist $\varepsilon$-optimal Markov strategies, i.e., strategies that base decisions only on the current state and on…
Matheus Sant’Ana Lima, Seyedali Mirjalili
Distributed Systems architectures are becoming the standard computational model for processing and transportation of information, especially for Cloud Computing environments. The increase in demand for application processing and data management from enterprise and end-user workloads continues to move from a single-node…
Dennis Komm, Rastislav Královič, Richard Královič, Tobias Mömke
We study the relationship between the competitive ratio and the tail distribution of randomized online problems. To this end, we identify a broad class of online problems for which the existence of a randomized online algorithm with constant expected competitive ratio r implies the existence of a randomized online…
György Dósa, Armin Fügenschuh, Zhiyi Tan, Zsolt Tuza + 1 more
'Krzysztof Węsek'] We consider a semi-online version of the problem of scheduling a sequence of jobs of different lengths on two uniform machines with given speeds 1 and s. Jobs are revealed one by one (the assignment of a job has to be done before the next job is revealed), and the objective is to minimize the…