Asynchronous games on Petri nets and ATL

We define a game on distributed Petri nets, where several players interact with each other, and with an environment . The players, or users, have perfect knowledge of the current state, and pursue a common goal . Such goal is expressed by Alternating-time Temporal Logic (ATL) The users have a winning strategy if they can cooperate to reach their goal, no matter how the environment behaves .…

The Paradox of Second Order Homophily in Networks

Homophily — the tendency of nodes to connect to others of the same type — is a central issue in the study of networks . Here we take a local view of homophily, defining notions of first-order homophilies of a node (its individualtendency to link to similar others) The gap in averages defies simple intuitiveexplanations, applies to globally heterophilous networks and isreminiscent of but structurally distinct from the Friendship Paradox .…

EnergySaver Software Manual

Energy Saver is a software that monitors electric energy consumption from data capture to consumption forecast for the following month . It uses Open Source technologies applied to the internet of Things (IoT), embedded systems, and Long Short-Term Memory NeuralNetworks (LSTM) The software has as its objective the monitoring of electricenergy consumption .…

Architecture of Automated Crypto Finance Agent

We present the cognitive architecture of an autonomous agent for active portfolio management in decentralized finance . It involves activities such as asset selection, portfolio balancing, liquidity provision, and trading . Partial implementation of the architecture is provided and supplied with preliminary results .…

The COVID 19 infodemic does not affect vaccine acceptance

How does information consumption affect behaviour in the context of theCOVID-19 pandemic? A popular hypothesis states that the so-called infodemics have substantial impact on orienting individual decisions . A competing hypothesis stresses that exposure to vast amounts of even contradictoryinformation has little effect on personal choices .…

Applying Declarative Analysis to Software Product Line Models An Industrial Study

Software Product Lines (SPLs) are families of related software products developed from a common set of artifacts . Most existing analysis tools can be applied to a single product at a time, but not to an entire SPL . In this paper, we take an existing declarative analysis (behaviouralteration) written in Grok, port it to Datalog, and apply it to a set of automotive software product lines from General Motors .…

Separated Red Blue Center Clustering

We study a generalization of $k$-center clustering, first introduced byKavand et. al., where instead of one set of centers, we have two types of centers . Each red center is at least $alpha$distant from each blue center, and the goal is to minimize the covering radius .…

A method for decompilation of AMD GCN kernels to OpenCL

Decompilers are useful tools for software analysis and support in the absence of source code . None of the existing tools support modern AMD GPU architectures such as AMD GCN and RDNA . We aim at developing the first assembly decompiler tool for a modernAMD GPU architecture that generates code in the OpenCL language .…

The Paradox of Second Order Homophily in Networks

Homophily — the tendency of nodes to connect to others of the same type — is a central issue in the study of networks . Here we take a local view of homophily, defining notions of first-order homophilies of a node (its individualtendency to link to similar others) The gap in averages defies simple intuitiveexplanations, applies to globally heterophilous networks and isreminiscent of but structurally distinct from the Friendship Paradox .…

Using a template engine as a computer algebra tool

This paper proposes a library and scripts for automated generation of routine functions inthe Julia programming language for a set of numerical schemes of Runge-Kuttamethods . The proposed approach allows us to use asingle template for editing, instead of modifying each individual function to be compared .…

Near Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time

In the numerical linear algebra community, it is thought that to obtain nearly-optimal bounds for various problems such as rank computation and finding a linearly independent subset of columns, regression, low rankapproximation, maximum matching on general graphs and linear matroid union, onewould need to resolve the logarithmic factors in the sketching dimension for existingconstant factor approximation oblivious subspace embeddings .…

Automating Induction by Reflection

In first-orderlogic induction requires an infinite number of axioms, which is not a feasible input to a computer-aided theorem prover requiring a finite input . In this work we introduce a new method, inspired by the field of axiomatictheories of truth, that allows to express schematic inductive definitions .…

Lossy Kernelization of Same Size Clustering

In this work, we study the $k$-median clustering problem with an additionalequal-size constraint on the clusters, from the perspective of parameterizedpreprocessing . Our main result is the first lossy ($2$-approximate) polynomial kernel for this problem, parameterized by the cost of clustering .…

A Refined Approximation for Euclidean k Means

In the Euclidean $k$-Means problem we are given a collection of $n$ points$D$ and a positive integer $k$. This problem is known to be APX-hard and the current best approximationratio is a primal-dual $6.357$ approximation . In this note we show how a minor modification of Ahmadian et al.’s…

Neural Architecture Search using Covariance Matrix Adaptation Evolution Strategy

Evolution-based neural architecture search requires high computational resources, resulting in long search time . In this work, we propose a framework of applying the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) to theneural architecture search problem called CMANAS . We also used an architecture-fitness table (AF table) for keepingrecord of the already evaluated architecture, thus further reducing the searchtime .…

Local Search for Weighted Tree Augmentation and Steiner Tree

We present a technique that allows for improving on some relative greedy algorithms by well-chosen (non-oblivious) local search algorithms . Relativegreedy procedures are a particular type of greedy algorithm that start with asimple, though weak, solution, and iteratively replace parts of this startingsolution by stronger components .…

Two Sided Matching Meets Fair Division

We introduce a new model for two-sided matching which allows us to borrow popular fairness notions from the fair division literature such asenvy-freeness up to one good and maximin share guarantee . We show that (a slight strengthening of) DEF1 cannot always be achieved, but in the special case where both sides have identical preferences, the round-robin algorithm with a carefully designed ordering achieves it .…

Sparse Fourier Transform by traversing Cooley Tukey FFT computation graphs

In the Sparse Fast Fourier Transform (Sparse FFT) problem, one is given oracle access to a $d-dimensional vector $x$ of size $N$ and is asked to compute the best $k$-term approximation of its Discrete Fourier transform . This is in sharp contrast with the classical FFT algorithm of Cooley and Tukey, which is stable and completely insensitive to the dimension of the input vector .…

Resonant tunnelling diode nano optoelectronic spiking nodes for neuromorphic information processing

In this work, we introduce an optoelectronic spiking artificial neuroncapable of operating at ultrafast rates ($\approx$ 100 ps/optical spike) and with low energy consumption ($<$ pJ/spike) The proposed system combines anexcitable resonant tunnelling diode (RTD) element exhibiting negativedifferential conductance, coupled to a nanoscale light source (forming a masternode) or a photodetector . We also demonstrate an optically-interconnectedspiking neural network model for processing of spatiotemporal data at over 10Gbps with high inference accuracy . These results demonstrate thepotential and viability of RTD spiking nodes for low footprint, low energy, …

Preference Incorporation into Many Objective Optimization An Outranking based Ant Colony Algorithm

In this paper, we enriched Ant Colony Optimization (ACO) with intervaloutranking to develop a novel multiobjective ACO optimizer . This proposal is suitable if the preferences of the Decision Maker (DM) can be modeled through outranking relations . IO-ACO is the firstant-colony optimizer that embeds an outranking model to bear vagueness andill-definition of DM preferences .…

MAGE Nearly Zero Cost Virtual Memory for Secure Computation

Secure Computation (SC) is a family of cryptographic primitives for computing on encrypted data in single-party and multi-party settings . SC is beingincreasingly adopted by industry for a variety of applications . MAGE calculates the memory access pattern ahead of time and uses it to produce a memory management plan .…

Spectral Processing and Optimization of Static and Dynamic 3D Geometries

Geometry processing of 3D objects is of primary interest in many areas of computer vision and graphics, including robot navigation, 3D objectrecognition, classification, feature extraction, etc. The aim of this thesis is topresent algorithms, mainly inspired by the spectral analysis, subspacetracking, etc, that can be used and facilitate low-level 3Dgeometry processing, pattern recognition tasks and high-level applications, such as registration and identification of 3 D objects in partially scanned and cluttered scenes, taking into consideration different 3D models such as static and dynamic point clouds, static anddynamic 3D meshes .…

MAGE Nearly Zero Cost Virtual Memory for Secure Computation

Secure Computation (SC) is a family of cryptographic primitives for computing on encrypted data in single-party and multi-party settings . SC is beingincreasingly adopted by industry for a variety of applications . MAGE calculates the memory access pattern ahead of time and uses it to produce a memory management plan .…

Optimal Scoring Rule Design

This paper introduces an optimization problem for proper scoring rule design . We propose an efficient algorithm to compute an optimal scoring rule when the collection of distributions is finite . We alsoprove the optimality of the log scoring rule over a smaller set of functionsfor categorical distributions with Dirichlet priors .…

Deterministic and Las Vegas Algorithms for Sparse Nonnegative Convolution

In this paper we present the first deterministic near-linear-time algorithm for computing sparse nonnegative convolutions . This immediately gives improveddeterministic algorithms for the state-of-the-art of output-sensitive SubsetSum, block-mass pattern matching, $N-fold Boolean convolution, and others,matching up to log-factors the fastest known randomized algorithms for these problems .…

Potential UAV Landing Sites Detection through Digital Elevation Models Analysis

In this paper, a simple technique for Unmanned Aerial Vehicles (UAVs)potential landing site detection using terrain information throughidentification of flat areas, is presented . The algorithm utilizes digitalelevation models (DEM) that represent the height distribution of an area . Flatareas which constitute appropriate landing zones for UAVs in normal oremergency situations result by thresholding the image gradient magnitude of the digital surface model .…

Combatting Gerrymandering with Social Choice the Design of Multi member Districts

Every representative democracy must specify a mechanism under which voters choose their representatives . The most common mechanism in the U.S. –winner-take-all single-member districts — both enables substantial partisangerrymandering and constrains `fair’ redistricting . We study the design of multi-memberdistricts (MMDs) in which each district elects multiple representatives, potentially through a non-winner-takes-all voting rule .…

A Refined Approximation for Euclidean k Means

In the Euclidean $k$-Means problem we are given a collection of $n$ points$D$ and a positive integer $k$. This problem is known to be APX-hard and the current best approximationratio is a primal-dual $6.357$ approximation . In this note we show how a minor modification of Ahmadian et al.’s…

MAGE Nearly Zero Cost Virtual Memory for Secure Computation

Secure Computation (SC) is a family of cryptographic primitives for computing on encrypted data in single-party and multi-party settings . SC is beingincreasingly adopted by industry for a variety of applications . MAGE calculates the memory access pattern ahead of time and uses it to produce a memory management plan .…

EPTAS for stable allocations in matching games

Gale-Shapley introduced a matching problem between two sets of agents whereeach agent on one side has a preference over the agents of the other side . Shapley-Shubik, Demange-Gale, and many others extended the model by allowing monetary transfers . In thispaper, we study an extension where matched couples obtain their payoffs as the outcome of a strategic game .…