## Learning sums of powers of low degree polynomials in the non degenerate case

We develop algorithms for writing a polynomial as sums of powers of lowdegree polynomials . The set ofdegenerate $Q_i$’s (i.e., inputs for which the algorithm does not work) form anon-trivial variety . The algorithm is based on a scheme for obtaining a learning algorithm for an arithmetic circuit model from a lower bound for the same model, provided certain non-degeneracy conditions hold .…

## Extended source imaging a unifying framework for seismic medical imaging

We present three imaging modalities that live on the crossroads of seismicand medical imaging . From the seismic perspective, we underlinethe importance to work with the correct physics and spatially varying velocityfields . Medical imaging, on the other hand, opens the possibility for newimaging modalities where outside stimuli, such as laser or radar pulses, cannot only be used to identify optical or thermal contrasts but that outside stimuli can also be used as a tool to insonify the medium so that images of the whole specimen can in principle be created .…

## The stray and demagnetizing field from a homogeneously magnetized tetrahedron

The stray- and demagnetization tensor field for a homogeneously magnetizedtetrahedron is found analytically . The tetrahedrons are a special case of fourtriangular faces with constant magnetization-charge surface density . The tensor fields are implemented in the opensource micromagnetic and magnetostatic simulation framework MagTense .…

## The magnetic field from a homogeneously magnetized cylindrical tile

The magnetic field of a homogeneously magnetized cylindrical tile geometry,i.e. an angular section of a finite hollow cylinder, is found . The field is the product between a tensor field describing the geometrical part of the problem and a column vector holding the magnetization of the tile .…

## Modular topology optimization with Wang tilings An application to truss structures

Modularity is appealing for solving many problems in optimization . We tackle the emerging bilevel optimization problem with a combination of meta-heuristics and mathematical programming . The best designs obtained by our method exhibited decreased compliance: from 56% to 69% compared to the PUC designs .…

## Non maximal sensitivity to synchronism in periodic elementary cellular automata exact asymptotic measures

In [11] and [13] the authors showed that elementary cellular automata rules0, 3, 8, 12, 15, 28, 32, 34, 44, 51, 60, 128, 136, 140, 160, 162, 170, 200 and204 . In this work we present exact measurements of the sensitivity to synchronism for these rules, as functions of the size .…

## On the Linguistic Capacity of Real Time Counter Automata

Counter machines have achieved a newfound relevance to the field of naturallanguage processing (NLP) Recent work suggests some strong-performing neural networks utilize their memory as counters . We prove that counter languages are closed under complement, union, intersection, and many common set operations .…

## Line Art Correlation Matching Network for Automatic Animation Colorization

Automatic animation line art colorization is a challenging computer vision problem . There exists a strict requirement for the color and style consistencybetween frames . Existing methods simply input the previous frame as a reference to color the next line art, which will mislead the colorization due to the spatial misalignment of the previous colored frame and the next frame .…

## MLCVNet Multi Level Context VoteNet for 3D Object Detection

In this paper, we address the 3D object detection task by capturingmulti-level contextual information with the self-attention mechanism andmulti-scale feature fusion . We introduce three context modules into the voting and classifying stages of VoteNet to encode contextual information at different levels .…

## Optimal protocols for the most difficult repeated coordination games

Choice Matching Games (CM-games) are a simple yet fundamental type of WLC-games, where the goal of the players is to pick the same choice from a finite set of initiallyindistinguishable choices . We give a complete classification of optimalexpected and guaranteed coordination times in two-player CM-games and show that the corresponding optimal protocols are unique in every case – except in theCM-game with four choices, which we analyse separately .…

## Optimal Bidding Strategies for Online Ad Auctions with Overlapping Targeting Criteria

We analyze the problem of how to optimally bid for ad spaces in online adauctions . We show that anoptimal bidding strategies decomposes the problem into disjoint sets of campaigns and targeting groups . Pure bidding strategies that use only a single bid value for each campaign are not optimal when supply curves are not continuous .…

## Trakhtenbrot s Theorem in Coq A Constructive Approach to Finite Model Theory

We study finite first-order satisfiability (FSAT) in the constructive setting of dependent type theory . Employing synthetic accounts of enumerability anddecidability, we give a full classification of FSAT depending on thefirst-order signature of non-logical symbols . All our results are mechanised in the framework of a growing Coqlibrary of synthetic undecidability proofs .…

## First Order Rewritability of Ontology Mediated Queries in Linear Temporal Logic

We investigate ontology-based data access to temporal data . We considertemporal ontologies given in linear temporal logic LTL interpreted overdiscrete time (Z, 1, or FO(RPR) We obtain similar hierarchies for more expressive types of queries: positiveLTL-formulas, monotone MFO(<)- and arbitrary MFO (<)-formulas) Our results lay foundations for investigating ontology based access using combinations of temporal and description logics over two-dimensional temporaldata . …

## Computing Tropical Prevarieties with Satisfiability Modulo Theories SMT Solvers

A novel way to use SMT (Satisfiability Modulo Theories) solvers to computethe tropical prevariety (resp. equilibrium) of a polynomial system is presented . The new method is benchmarked against a naive approach that usespurely polyhedral methods . It turns out that the SMT approach is faster thanthe polyhedral approach for models that would otherwise take more than oneminute to compute, in many cases by a factor of 60 or more, and in the worstcase is only slower by two .…

## Prolog Technology Reinforcement Learning Prover

The core of the toolkitis a compact and easy to extend Prolog-based automated theorem prover calledplCoP . plCoP builds on the leanCoP Prolog implementation and adds learning-guided Monte-Carlo Tree Search as done in the rlCoP system . Weargue that the Prolog setting is suitable for combining statistical andsymbolic learning methods .…

## Resilience in multi robot multi target tracking with unknown number of targets through reconfiguration

We address the problem of maintaining resource availability in a networked multi-robot team performing distributed tracking of unknown number of targets in an environment . We use the trace of a robot’s sensor measurement noise covariancematrix to quantify its sensing quality .…

## Composite Travel Generative Adversarial Networks for Tabular and Sequential Population Synthesis

Agent-based transportation modelling has become the standard to simulatetetravel behaviour, mobility choices and activity preferences . We present a novel deep generative model to estimate the underlying joint distribution of a population, that is capable of reconstructing compositesynthetic agents having tabular (e.g.…

## Dyslexia and Dysgraphia prediction A new machine learning approach

Between 5% to 10% of the world population is subject to dysgraphia, dyslexia and dyspraxia . The model is trained on simple features obtained by analysing the pictures and audio files . It suggests the possibility to screen dyslexic/dysgraphic via non-invasive methods in an accurate way as soon as enough data is available .…

## Evaluation of Generalizability of Neural Program Analyzers under Semantic Preserving Transformations

Despite the growing popularity of neuralprogram analyzers, the extent to which their results are generalizable is unknown . We perform a large-scale evaluation of the generalizability of two popular neural program analyzers using seven semantically-equivalenttransformations of programs . The results provide the initial stepping stones for quantifying robustness in neural programanalyzers, we say .…

## Speeding up Logic Design and Refining Hardware EDA Flow by Exploring Chinese Character based Graphical Representation

Electrical design automation (EDA) techniques have deeply influenced the computer hardware design, especially in the field of very large scaleIntegration (VLSI) circuits . The popularity of FPGA, ASIC and SOC applications have been dramatically increased due to the well developed EDAtool chains .…

## Efficient Near Complete and Often Sound Hybrid Dynamic Data Race Prediction extended version

Dynamic data race prediction aims to identify races based on a single programrun represented by a trace . The challenge is to remain efficient while being assound and as complete as possible . Efficient means a linear run-time asotherwise the method unlikely scales for real-world programs .…

## A Study on the Challenges of Using Robotics Simulators for Testing

Robotics simulation plays an important role in the design, development, andverification and validation of robotic systems . Recent studies have shown that simulation may be used as a cheaper, safer, and more reliable alternative to field testing . This is particularly important in the context of continuous integration pipelines, where integratedautomated testing is key to reducing costs while maintaining system safety .…

## Ownership at Large Open Problems and Challenges in Ownership Management

Software-intensive organizations rely on large numbers of software assets of different types, e.g., source-code files, tables in the data warehouse, andsoftware configurations . The problem of finding the most suitable owners for an asset is essentially a program comprehension problem .…

## Effective Removal of Operational Log Messages an Application to Model Inference

Model inference aims to extract accurate models from execution logs of software systems . In low-quality logs,transactional and operational messages are randomly interleaved, leading to the inclusion of operational behaviors into a system model . In this paper, we propose LogCleaner, a novel technique for removingoperational logs messages .…

## An efficient deception architecture for cloud based virtual networks

Miserydigraphs can delay access to targets deep in a cloud-based virtual network . Full implementation of the architecture in Amazon WebServices imposes modest performance delays in the request processing, while delaying stealth intrusions in the network . This work presents and analyzes a high-throughputarchitecture for misery digraphs, embarking on implementation details and performance analysis .…

## Reduction Methods on Probabilistic Control flow Programs for Reliability Analysis

Modern safety-critical systems require reliability evaluation methods that go beyond static static methods . We propose two automated reduction methods for probabilistic programs that operate on a purely syntactic level: reset valueoptimization and register allocation optimization . We show effectiveness of our implementation of the reduction methods.…

## A Higher Structure Identity Principle

Structure Identity Principle states that any property ofset-level structures (e.g., groups, rings, fields) definable inUnivalent Foundations is invariant under isomorphism . We prove a version of this principle for a wide range of higher-categorical structures, adaptingFOLDS-signatures to specify a general class of structures .…

## On the Optimal Interaction Range for Multi Agent Systems Under Adversarial Attack

The interactionrange, which defines the set of neighbors for each agent, plays a key role in influencing connectivity of the underlying network . We find that for many cases of interestthe optimal interaction range is one that forces the network to break up into a handful of disconnected graphs, each containing a subset of agents .…

## Fundamental Performance Limitations for Average Consensus in Open Multi Agent Systems

We derive fundamental performance limitations for intrinsic average consensus problems in open multi-agent systems . Algorithms solving such problems in opensystems are poised to never converge because of the permanent variations in the composition, size and objective pursued by the agents of the system .…

## A Demonstration of Issues with Value Based Multiobjective Reinforcement Learning Under Stochastic State Transitions

We report a previously unidentified issue with model-free, value-based approaches to multiobjective reinforcement learning in the context of environments with stochastic state transitions . We discuss several alternative methods which may be more suitable for maximising SER in MOMDPs with Stochastic transitions .…

## Analysis of Social Media Data using Multimodal Deep Learning for Disaster Response

Multimedia content in social media platforms provides significant information during disaster events . The types of information shared include reports ofinjured or deceased people, infrastructure damage, and missing or found people, among others . In this paper, we propose to use both text and image modalities of social media data to learn a joint representation using state-of-the-art deep learning techniques .…

## Interactive distributed cloud based web server systems for the smart healthcare industry

The work aims to investigate the possible contemporary interactive cloudbased solutions in the fields of the applied medicine for the smart Healthcare . A new method of numerical calculus is proposed for calculating the volume — the method of spheres, as well as a proposal for paralleling the algorithm on graphic accelerators in a linearlyhomogeneous computing environment using the block decomposition methods .…

## Quantum Approximation for Wireless Scheduling

This paper proposes a quantum approximate optimization algorithm (QAOA)method for wireless scheduling problems . The QAOA is one of the promisinghybrid quantum-classical algorithms for many applications and it provides highly accurate optimization solutions in NP-hard problems . This paper verifies the novelty of the proposed QAOS via simulations implemented by Cirq and TensorFlow-Quantum.…

## Accelerating Filesystem Checking and Repair with pFSCK

Current file system checkers fail to exploit CPU parallelism and highthroughput offered by modern storage devices . pFSCK is a tool that redesigns C/R to enable fine-grained parallelism atthe granularity of inodes without impacting the correctness of C/Rs’ functionality . Evaluation shows more than 2.6x gains of e2fsck and more than 1.8x over XFS’s checker that provides coarse-granated parallelism.…

## A Fortran Keras Deep Learning Bridge for Scientific Computing

The Fortran-Keras Bridge (FKB) is a two-way bridge connecting learning resources with those where they are scarce . FKB enables a hyperparameter search of one hundredplus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to be transferred and used in Fortran .…

## Test Automation Process Improvement in a DevOpsTeam Experience Report

A Finnish software company builds Windows software and exists in F-Secure’s TAPI culture . The team reports high satisfaction and maturity in test automation for continuous development . Critical success factors have a major impact on successfully carrying out its TAPI, e.g.,…

## Code Completion using Neural Attention and Byte Pair Encoding

In this paper, we aim to do code completion based on implementing a NeuralNetwork from Li et. al.. Our contribution is that we use an encoding that isin-between character and word encoding called Byte Pair Encoding (BPE) We usethis on the source code files treating them as natural text without first going through the abstract syntax tree (AST) We have implemented two models: anattention-enhanced LSTM and a pointer network .…

## Gelato Feedback driven and Guided Security Analysis of Client side Web Applications

GELATO proposes a feedback-driven security-aware guided crawler that is able to analyze complex frameworks automatically . It also proposes a new lightweight client-side taint analysis that outperforms the start-of-the-art tools, requires no modification to browsers, and reports non-trivial taintflows on modern JavaScript applications .…

## An Analysis of Python s Topics Trends and Technologies Through Mining Stack Overflow Discussions

Python is a popular, widely used, and general-purpose programming language . Programming in areas such as mathematics, data science,statistics, machine learning, natural language processing (NLP) are the most popular areas in the Python community . Python provides the alternative to populartechnologies offered by common programming languages like Java .…

## A Comparison of Big step Semantics Definition Styles

Formal semantics provides rigorous, mathematically precise definitions of programming languages . In this paper we investigate some of the approaches that share their roots with traditional relational big-step semantics . We present an example language forcomparing the semantics: a sequential subset of Core Erlang, a functionalprogramming language, which is used in the intermediate steps of the Erlang/OTPcompiler .…

## Standardizing and Benchmarking Crisis related Social Media Datasets for Humanitarian Information Processing

Time-critical analysis of social media streams is important for humanitarian organizations to plan rapid response during disasters . We consolidate labelsof eight annotated data sources and provide 166.1k and 141.5k tweets forinformativeness and humanitarian classification tasks, respectively . Theconsolidation results in a larger dataset that affords the ability to trainmore sophisticated models .…

## Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence

Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to roads, bridges, and buildings . This work analyzes the use of social media imagery to perform rapid damage assessment during a real-world disaster .…

## A Tailored NSGA III Instantiation for Flexible Job Shop Scheduling

A customized multi-objective evolutionary algorithm (MOEA) has been combined with NSGA-III to solve benchmark FJSPs . It uses smartinitialization approaches to enrich the first generated population, and proposes various crossover operators to create a better diversity of offspring . MIP-EGO configurator, which can tune algorithm parameters, is adopted to automatically tune operator probabilities .…

## dMFEA II An Adaptive Multifactorial Evolutionary Algorithm for Permutation based Discrete Optimization Problems

The emerging research paradigm coined as multitasking optimization aims to solve multiple optimization tasks concurrently by means of a single search process . The exploitation of complementarities among the tasks to be solved is crucial, which is often achieved via the transfer of genetic material, thereby forging the Transfer Optimization field .…

## Knowledge Elicitation using Deep Metric Learning and Psychometric Testing

Knowledge present in a domain is well expressed as relationships betweencorresponding concepts . In zoology, animal species form complexhierarchies; in genomics, the different (parts of) molecules are organized ingroups and subgroups based on their functions . In this paper, we provide amethod for efficient hierarchical knowledge elicitation (HKE) from expertsworking with high-dimensional data such as images or videos .…

## Dichotomy for Graph Homomorphisms with Complex Values on Bounded Degree Graphs

The complexity of graph homomorphisms has been a subject of intense study . We prove that the complexity dichotomy of [6] extends to boundeddegree graphs . We also prove that either $G \mapsto Z_{\mathbfA}(G) is computable in polynomial-time for every$G$or for some$Delta 0$it is #P-hard over (simple) graphs$G) The tractability criterion on this dichotomy isexplicit, and can be decided in a size of $mathbf A$ .…

## Counting Small Induced Subgraphs Satisfying Monotone Properties

Given a graph property, the problem asks, oninput a graph $G$ and a positive integer $k$, to compute the number of inducedsubgraphs of size $k$ that satisfy $Phi$. The search for explicitcriteria on this problem was started by Jerrum and Meeks [J.…

## Tensor Network Rewriting Strategies for Satisfiability and Counting

We provide a graphical treatment of SAT and SAT on equal footing . Instances of SAT can be represented as tensor networks in a standard way . These tensornetworks are interpreted by diagrams of the ZH-calculus . We find that forclasses known to be in P, such as $2$SAT and $3$SAT, the existence of appropriate rewrite rules allows for efficient simplification of the diagram, producing the solution in polynomial time .…

## The quantum query complexity of composition with a relation

The negative weight adversary method is known to characterize the bounded-error quantum query complexity of any function $g$ and obeys a perfect composition theorem . A relation is efficiently verifiable if $f_a$ is an efficientlyverifiable relation $f$ is $f\subseteqeq \{0,1\}^n \times [K]$ for $a$a \in [K)$for every$a .…

## Cross domain Correspondence Learning for Exemplar based Image Translation

We present a framework for exemplar-based image translation, which synthesizes a photo-realistic image from the input in a distinct domain . The output has the style (e.g., color, texture) in consistency with thesemantically corresponding objects in the exemplar . Our method is superior to state-of-the-art methods in terms of imagequality significantly .…