Towards an Automatic Proof of Lamport s Paxos

Lamport’s celebrated Paxos consensus protocol is generally viewed as a hard-to-understand algorithm . We take a step towards automatically proving the safety of Paxos by taking advantage of three structural features in its specification . We note that these structural features are not specific to Paxos and that IC3PO can serve as an automatic general-purpose protocol verification tool .…

Second Order Specifications and Quantifier Elimination for Consistent Query Answering in Databases

Repairs are consistent instances that minimally differ from the original inconsistent instance . Consistent answers to a query from a possibly inconsistent database are answers that are simultaneously retrieved from every possible repair of the database . In this paper we show how to use the repair programs to transform the problem ofconsistent query answering into a problem of reasoning w.r.t.…

When Should You Defend Your Classifier A Game theoretical Analysis of Countermeasures against Adversarial Examples

Adversarial machine learning, i.e. increasing the robustness of machinelearning algorithms against so-called adversarial examples, is now an established field . Yet, newly proposed methods are evaluated and compared underunrealistic scenarios where costs for adversary and defender are not considered . We propose the advanced adversarial classification game, which incorporates all relevant parameters of an adversary and a defender inadversarial classification .…

Developer Operations and Engineering Multi Agent Systems

EngineeringMulti-Agent Systems (EMAS) and Developer Operations (DevOps) industry bestpractice . EMAS and the agent-oriented programming paradigm helpinstill autonomy into software artifacts . DevOps facilitates organizational autonomy of software teams, as well as technological automation of testing, deployment, and operations pipelines .…

Simulation and estimation of an agent based market model with a matching engine

An agent-based model with interacting low frequency liquidity takers and high-frequency liquidity providers acting collectively as market makers can be used to provide realistic simulated price impact curves . We argue that the reactive nature of market agents may be a fundamental property of financial markets and when accountedfor can allow for parsimonious modelling without recourse to additional sources of noise .…

VerSaChI Finding Statistically Significant Subgraph Matches using Chebyshev s Inequality

Approximate subgraph matching is an important primitive for many applications like question answering, community detection, and motif discovery . We proposeVerSaChI for finding the top-k most similar subgraphs based on 2-hop label andstructural overlap similarity with the query . The similarity is characterizedusing Chebyshev’s inequality to compute the chi-square statistical significance .…

Publisher References in Bibliographic Entity Descriptions

This paper describes a method for improved access to publisher references in linked data RDF editors using data mining techniques . The corpus is comprised of clusteredsets of publishers and publisher locations from the library MARC21 records found in the POD Data Lake, an Ivy+ Library Consortium metadata sharing initiative .…

Exact enumeration of satisfiable 2 SAT formulae

The Implication generating function is inspired by the Graphic generating function used in digraph enumeration . We obtain exact expressions counting the satisfiable 2-SAT formulae and describe the structure of associated implication digraphs . We expect these exactformulae to be amenable to rigorous asymptotic analysis using complex analytictools .…

On Incorrectness Logic and Kleene Algebra With Top and Tests

Kleene algebra with tests (KAT) is a foundational equational framework for reasoning about programs . We show that KAT cannot directly express incorrectnesslogic . The main reason for this limitation can be traced to the fact KATcannot express explicitly the notion of codomain, which is essential to expressincorrectness triples .…

Efficient Communication in Multi Agent Distributed Reinforcement Learning

We present in this work an approach to reduce the communication ofinformation needed on a multi-agent learning system inspired by Event TriggeredControl (ETC) techniques . We consider a baseline scenario of a distributedQ-learning problem on a Markov Decision Process (MDP) Following an event-basedapproach, N agents explore the MDP and communicate experiences to a centrallearner only when necessary, which performs updates of the actor Q functions .…

Timed Automata Robustness Analysis via Model Checking

Timed automata (TA) have been widely adopted as a suitable formalism to modeltime-critical systems . However, the exact timing constants are often uncertain during the design phase . Even if the TA initially satisfies the specification, it can be the case that just a slight perturbation during the implementationcauses a violation of the specification .…

Self Sovereign Identity A Systematic Map and Review

Self-Sovereign Identity is a user-centric identity model . In this model, the user maintains and controls their data . When requested by a service provider, user data is sent directly by the user, without the intermediation of third parties . This model has attracted the attention of researchers and organizations around the world.…

Worst Case Efficient Dynamic Geometric Independent Set

We present data structures that maintain a constant-factor approximatemaximum independent set for broad classes of fat objects in $d$ dimensions . This gives the first results for dynamic independent set in a wide variety ofgeometric settings, such as disks, fat polygons, and their high-dimensionalequivalents .…

Spatially and color consistent environment lighting estimation using deep neural networks for mixed reality

The representation of consistent mixed reality (XR) environments requires adequate real and virtual illumination composition in real-time . This paper presents a CNN-based model to estimate complex lighting for mixed reality environments with no previous information about the scene . We propose using a highly optimized deep neural networkarchitecture, with a reduced number of parameters, that can learn high complex lighting scenarios from real-world high-dynamic-range (HDR) environment images .…

Worst Case Efficient Dynamic Geometric Independent Set

We present data structures that maintain a constant-factor approximatemaximum independent set for broad classes of fat objects in $d$ dimensions . This gives the first results for dynamic independent set in a wide variety ofgeometric settings, such as disks, fat polygons, and their high-dimensionalequivalents .…

On correctness and completeness of an n queens program

Thom Fr\”uhwirth presented a short, elegant and efficient Prolog program for the n queens problem . However the program may be seen as rather tricky and onemay not be convinced about its correctness . This paper explains the program in a declarative way, and provides proofs of its correctness and completeness .…

Promoting Mental Well Being for Audiences in a Live Streaming Game by Highlight Based Bullet Comments

Game live streaming is becoming a popular theme for academicresearch . The enjoyment emerged while watching game live streaming also benefits the audience’s mental health . Many e-sports live streaming channels do not have a commentator for entertaining viewers . This paper proposes a method for generating bullet comments for live-streaming games based on highlights (i.e.,…

CollaborER A Self supervised Entity Resolution Framework Using Multi features Collaboration

CollaborER is self-supervised entity resolution framework viamulti-features collaboration . It is capable of (i) obtaining reliable ER results with zero human annotations and (ii) discovering adequate tuples’features in a fault-tolerant manner . CollaborER consists of two phases, i.e., automatic label generation (ALG) and collaborative ER training (CERT) In thefirst phase, ALG is proposed to generate a set of positive tuples pairs and aset of negative tuples .…

Solving the Funarg Problem with Static Types

The difficulty associated with storing closures in a stack-based environment is known as the funarg problem . This is not a problem for most computing systems as there is an abundance of memory . But embedded systems often have limited memory resources where heap allocation may cause memory fragmentation .…

Writing R Extensions in Rust

This paper complements “Writing R Extensions,” the official guide for writingR extensions, for those interested in developing R packages using Rust . Ithighlights idiosyncrasies of R and Rust that must be addressed by any integration . This paper introduces the “cargo” framework, atransparent Rust-based API which wraps commonly-used parts of R’s API with minimal overhead and allows a programmer to easily add additional wrappers .…

Statistically Near Optimal Hypothesis Selection

Hypothesis Selection is a fundamental distribution learning problem . The goal is to output adistribution $q$ such that $q is close to $opt$ with a (nearly) optimal sample complexity of~$\tilde O(\logn/\epsilon^2)$ This is the first algorithm that simultaneously achieves the best approximation factor and sample complexity .…

Higher Order Concurrency for Microcontrollers

We introduce a virtual machine that provides a message-passing based concurrency model, originally introduced by Reppy, formicrocontroller programming . This model treats synchronous operations as first-class values, akin to the treatment offirst-class functions in functional languages . It abstracts away unsafe memory operations, common in shared-memoryconcurrency models, thereby making microcontroller programs safer, composableand easier-to-maintain .…

Improving Thread Modular Abstract Interpretation

We give thread-modular non-relational value analyses as abstractions of alocal trace semantics . The semantics as well as the analyses are formulated by means of global invariants and side-effecting constraint systems . We show that these two analyses areincomparable w.r.t. precision and provide a refinement which improves on both precision-wise .…

DeepEigen Learning based Modal Sound Synthesis with Acoustic Transfer Maps

We present a novel learning-based approach to compute the eigenmodes andacoustic transfer data for the sound synthesis of arbitrary solid objects . Our approach combines two network-based solutions to formulate a completelearning-based 3D modal sound model . This includes a 3D sparse convolutionnetwork as the eigendecomposition solver and an encoder-decoder network for the prediction of the Far-Field Acoustic Transfer maps (FFAT Maps) We compare its accuracy and efficiency with physically-based sound synthesis methods .…

Distant Representatives for Rectangles in the Plane

The input to the distant representatives problem is a set of $n$ objects inthe plane . The goal is to find a representative point from each object while maximizing the distance between the closest pair of points . We also prove lower bounds on the approximation factors that can beachieved in polynomial time (unless P = NP) We give polynnomine time constant-factorapproximation algorithms .…

Autocomplete Repetitive Stroking with Image Guidance

Image-guided drawing can compensate for the lack of skills but often requires a significant number of repetitive strokes to create textures . Existingautomatic stroke synthesis methods are usually limited to predefined styles or indirect manipulation that may break the spontaneous flow of drawing .…

Statistically Near Optimal Hypothesis Selection

Hypothesis Selection is a fundamental distribution learning problem . The goal is to output adistribution $q$ such that $q is close to $opt$ with a (nearly) optimal sample complexity of~$\tilde O(\logn/\epsilon^2)$ This is the first algorithm that simultaneously achieves the best approximation factor and sample complexity .…

Hybrid dynamical type theories for navigation

We present a hybrid dynamical type theory equipped with useful primitives for organizing and proving safety of navigational control algorithms . This typetheory combines the framework of Fu–Kishida–Selinger for constructing lineardependent type theories from state-parameter fibrations . We also define aconjectural embedding of a fragment of linear-time temporal logic within ourtype theory .…

ARCH Animation Ready Clothed Human Reconstruction Revisited

ARCH++ is an image-based method to reconstruct 3D avatars witharbitrary clothing styles . Our reconstructed avatars are animation-ready and highly realistic, in both the visible regions from input views and the unseen regions . We introduce an end-to-end point based geometryencoder to better describe the semantics of the underlying 3D human body, inreplacement of previous hand-crafted features .…