Related papers: A Method for Accelerating the HITS Algorithm
This paper addresses the use of Big Data and machine learning based analytics to the real-time management of Internet scale Quality-of-Service Route Optimisation with the help of an overlay network. Based on the collection of large amounts…
Drift analysis is a powerful tool for analyzing the time complexity of evolutionary algorithms. However, it requires manual construction of drift functions to bound hitting time for each specific algorithm and problem. To address this…
Motif discovery in DNA sequences is a challenging task in molecular biology. In computational motif discovery, Planted (l, d) motif finding is a widely studied problem and numerous algorithms are available to solve it. Both hardware and…
The goal of a decision-based adversarial attack on a trained model is to generate adversarial examples based solely on observing output labels returned by the targeted model. We develop HopSkipJumpAttack, a family of algorithms based on a…
Vector-based algorithms are novel algorithms in optimal any-angle path planning that are motivated by bug algorithms, bypassing free space by directly conducting line-of-sight checks between two queried points, and searching along obstacle…
The problem of mining Correlated Heavy Hitters (CHH) from a two-dimensional data stream has been introduced recently, and a deterministic algorithm based on the use of the Misra--Gries algorithm has been proposed by Lahiri et al. to solve…
The computation of determinants or their signs is the core procedure in many important geometric algorithms, such as convex hull, volume and point location. As the dimension of the computation space grows, a higher percentage of the total…
Hypergraphs are data structures capable of capturing supra-dyadic relations. We can use them to model binary relations, but also to model groups of entities, as well as the intersections between these groups or the contained subgroups. In…
Similarity search over a bipartite graph aims to retrieve from the graph the nodes that are similar to each other, which finds applications in various fields such as online advertising, recommender systems etc. Existing similarity measures…
Carefully balancing load in distributed stream processing systems has a fundamental impact on execution latency and throughput. Load balancing is challenging because real-world workloads are skewed: some tuples in the stream are associated…
The evaluation of hyperparameters, neural architectures, or data augmentation policies becomes a critical model selection problem in advanced deep learning with a large hyperparameter search space. In this paper, we propose an efficient and…
Bipartite graphs are widely used to model relationships between entities of different types, where nodes are divided into two disjoint sets. Similarity search, a fundamental operation that retrieves nodes similar to a given query node,…
Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used…
Recent works have shown that quantum computers can polynomially speed up certain SAT-solving algorithms even when the number of available qubits is significantly smaller than the number of variables. Here we generalise this approach. We…
PageRank is a well-known centrality measure for the web used in search engines, representing the importance of each web page. In this paper, we follow the line of recent research on the development of distributed algorithms for computation…
The ability to detect, in real-time, heavy hitters is beneficial to many network applications, such as DoS and anomaly detection. Through programmable languages as P4, heavy hitter detection can be implemented directly in the data-plane,…
With cyber incidents and data breaches becoming increasingly common, being able to predict a cyberattack has never been more crucial. The ability of Network Anomaly Detection Systems (NADS) to identify unusual behavior makes them useful in…
Geographically locating an IP address is of interest for many purposes. There are two major ways to obtain the location of an IP address: querying commercial databases or conducting latency measurements. For structural Internet nodes, such…
The Whittle index for restless bandits (two-action semi-Markov decision processes) provides an intuitively appealing optimal policy for controlling a single generic project that can be active (engaged) or passive (rested) at each decision…
Community and cluster detection is a popular field of social network analysis. Most algorithms focus on static graphs or series of snapshots. In this paper we present an algorithm, which detects communities in dynamic graphs. The method is…