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 .…

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 .…

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 .…

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 .…

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 .…

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 .…

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 .…

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 .…

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.…

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 .…

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 .…

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 .…

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 $mathbf A$ .…

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 .…