25 papers · ranked by Valyu relevance
Adil Yousif, Samar M. Alqhtani, Mohammed Bakri Bashir, Awad Ali + 9 more
'Rafik Hamza' 'Alzubair Hassan' 'Tawfeeg Mohmmed Tawfeeg' 'Haipeng Dai' 'Xianjun Deng' 'Xiaolong Xu' 'Ning Wang' 'Zhenzhe Zheng' 'Weijun Wang'] The Internet of Things (IoT) is defined as interconnected digital and mechanical devices with intelligent and interactive data transmission features over a defined network. The…
van Melkebeek, Dieter
We show for several computational problems how classical greedy algorithms for special cases can be derived in a simple way from dynamic programs for the general case: interval scheduling (restricted to unit weights), knapsack (restricted to unit values), and shortest paths (restricted to nonnegative edge lengths).…
Evans Teiko Tetteh, Beata Zielosko, Zoran H. Perić, Vlado Delić + 3 more
This study introduces a greedy algorithm for deriving decision rules from decision tree ensembles, targeting enhanced interpretability and generalization in distributed data environments. Decision rules, known for their transparency, provide an accessible method for knowledge extraction from data, facilitating…
Jeffrey Keithley, Akash Choudhuri, Bijaya Adhikari, Sriram V. Pemmaraju + 1 more
'Sriram V. Pemmaraju' 'Jennifer A. Flegg'] As observed in the case of COVID-19, effective vaccines for an emerging pandemic tend to be in limited supply initially and must be allocated strategically. The allocation of vaccines can be modeled as a discrete optimization problem that prior research has shown to be…
Salim Bouamama, Christian Blum, Pedro Pinacho-Davidson, Viorel Minzu
Finding dominating sets in graphs is very important in the context of numerous real-world applications, especially in the area of wireless sensor networks. This is because network lifetime in wireless sensor networks can be prolonged by assigning sensors to disjoint dominating node sets. The nodes of these sets are…
Guangling Sun, Rui Qi, Yulong Liu, Feng Xu + 1 more
Urbanization has led to accelerated traffic congestion, posing a significant obstacle to urban development. Traditional traffic signal scheduling methods are often inefficient and cumbersome, resulting in unnecessary waiting times for vehicles and pedestrians, exacerbating the traffic situation. To address this issue…
Guangyi Zhang, Nikolaj Tatti, Aristides Gionis
Submodular maximization has been the backbone of many important machine-learning problems, and has applications to viral marketing, diversification, sensor placement, and more. However, the study of maximizing submodular functions has mainly been restricted in the context of selecting a set of items. On the other hand…
Joan Vendrell Gallart, Alan Kuhnle, Solmaz Kia
This paper introduces Rewired Sequential Greedy (ResQue Greedy), an enhanced approach for submodular maximization under cardinality constraints. By integrating a novel set curvature metric within a lattice-based framework, ResQue Greedy identifies and corrects suboptimal decisions made by the standard sequential greedy…
Ajay Subbaroyan, Priyotosh Sil, Olivier C. Martin, Areejit Samal
Boolean models are a well-established framework to model developmental gene regulatory networks (DGRN) for acquisition of cellular identity. During the reconstruction of Boolean DGRNs, even if the network structure is given, there is generally a very large number of combinations of Boolean functions (BFs) that will…
Niklas Haas, Sören Schmitt, Rob van Stee
We consider the online buffer minimization in multiprocessor systems with conflicts problem (in short, the buffer minimization problem) in the recently introduced flow model. In an online fashion, workloads arrive on some of the n processors and are stored in an input buffer. Processors can run and reduce these…
Alen Alexanderian
where f : P( V ) → R is a non-negative monotone submodular function with the property that f(∅) = 0. Solving such problems by an exhaustive search is extremely challenging. This would require n k evaluations of f, which is prohibitive even for modest values of n and k. 3 In this note, we discuss approximate 3 For…
Ran Zhang, Xiaohan Li, Caihua Wan, Raik Hoffmann + 14 more
Combinatorial optimization underpins applications in artificial intelligence, logistics, and network design, yet classical techniques such as greedy search and dynamic programming struggle to balance efficiency and solution quality at scale. We present a probabilistic framework that embeds true random number generators…
Qianxiang Ai, Joshua Schrier
In a recent paper in this journal (Chem. Mater. 2022, 34, 2545-2552), Twyman et al. studied the environmental stability of crystals by introducing a greedy heuristic algorithm for determining possible oxidation reactions. We show how the problem can be solved exactly, with less code and comparable computational time by…
Steven Chaplick, Martin Frohn, Steven Kelk, Johann Lottermoser + 1 more
Independent Set on Interval and Chordal Graphs Authors: ['Steven Chaplick' 'Martin Frohn' 'Steven Kelk' 'Johann Lottermoser' 'Matúš Mihaľák'] Abstract. In this article we prove that the minimum-degree greedy algorithm, with adversarial tie-breaking, is a (2/3)-approximation for the Maximum Independent Set problem on…
Zhang, Liding, Ling, Yao + 8 more
—Bidirectional motion planning often reduces planning time compared to its unidirectional counterparts. It requires connecting the forward and reverse search trees to form a continuous path. However, this process could fail and restart the asymmetric bidirectional search due to the limitations of lazyreverse search. To…
Sebastian Schmidt, Shahbaz Khan, Jarno Alanko, Alexandru I. Tomescu
Kmer-based methods are widely used in bioinformatics, which raises the question of what is the smallest practically usable representation (i.e. plain text) of a set of kmers. We propose a polynomial algorithm computing a minimum such representation (which was previously posed as a potentially NP-hard open problem), as…
Bendegúz Sulyok, Gergely Palla
Finding the optimal embedding of networks into low-dimensional hyperbolic spaces is a challenge that received considerable interest in recent years, with several different approaches proposed in the literature. In general, these methods take advantage of the exponentially growing volume of the hyperbolic space as a…
Authors not listed
The identification of kinetically feasible reaction pathways that connect a reactant to its product, including numerous intermediates and transition states, is crucial for predicting chemical reactions and elucidating reaction mechanisms. However, as molecular systems become increasingly complex or larger, the number…
Yukun Yang, Wolfgang Maass
Most current methods for goal-directed action selection in the face of changing goals and contingencies require DNNs or LLMs. Therefore they are less suited for implementation in edge devices, where low energy-consumption is imperative. The brain shows that similar functionality can be produced with just 20W, even with…
Authors not listed
For applications in gas sensing, purification, and capture, we often wish to search a large set of metal-organic frameworks (MOFs) for the top-K in terms of their Henry coefficient of an adsorbate. A molecular simulation to predict the Henry coefficient of a MOF constitutes a Monte Carlo integration where each sample…
Paul Francoeur, Daniel Penaherrera, David Koes
The immense size of chemical space, the relative scarcity of high quality data, and the cost of running experiments to accurately measure molecular properties makes active learning (AL) an attractive approach to efficiently explore the space and train high-quality models for molecular property prediction. While AL is…
Kevin Y. Chen
Finding the shortest path between two points in a graph is a fundamental problem that has been well-studied over the past several decades. Shortest path algorithms are commonly applied to modern navigation systems, so our study aims to improve the efficiency of an existing algorithm on large-scale Euclidean networks.…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Eva Herencsárová, Broňa Brejová
In many bioinformatics applications the task is to identify biologically significant locations in an individual genome. In our work, we are interested in finding high-density clusters of such biologically meaningful locations in a graph representation of a pangenome, which is a collection of related genomes. Different…
Jonas Verhellen
Computer-assisted design of small molecules has experienced a resurgence in academic and indus- trial interest due to the widespread use of data-driven techniques such as deep generative models. While the ability to generate molecules that fulfill required chemical properties is encouraging, the use of deep learning…