Facilitating Meta Theory Reasoning Invited Paper

Structural proof theory is praised for being a symbolic approach to reasoning . For this to be possible, proof systems must be designed as a set of rules . Therefore, one must consider all ways these rules can interact and prove that they satisfy certain properties which makes them “well-behaved” Meta-theory proofs typically involve many cases on structures with lots ofsymbols .…

Touring the MetaCoq Project Invited Paper

MetaCoq aims to provide the first fully-certified realistic implementation of a type checker for the full calculus underlying the Coq proofassistant . We show how theoretical tools such as bidirectional type-checking, Tait-Martin-L\”of/Takahashi’s confluence proof technique and monadic anddependently-typed programming can help construct the following artefacts: aspecification of Coq’s syntax and type theory, the Polymorphic Cumulative CumulativeCalculus of (Co)-Inductive Constructions (PCUIC); a monad for the manipulation of raw syntax and interaction with Coq system; a verification of PCUIC’smetatheory, whose main results are the confluence of reduction, typepreservation and principality of typing; a realistic, correct and completetype-checker for PCIC .…

Verified Mutable Data Structures

Formal verification is the only form of sofware testing that can guarantee the absence of bugs . The implementation we propose is based on the LongMap of the Scala standard library with some minor adaptations . We give the specification withrespect to an implementation of a map based on a list of tuples, that we .plement…

Adelfa A System for Reasoning about LF Specifications

We present a system called Adelfa that provides mechanized support for reasoning about specifications developed in the Edinburgh Logical Framework orLF . Typing judgements in LF are represented by atomic formulas in L_LF and quantification is permitted overcontexts and terms that appear in such formulas .…

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 .…

DxHash A Scalable Consistent Hash Based on the Pseudo Random Sequence

Consistent hasing has played a fundamental role as a data router and a loadbalancer in various fields, such as distributed database, cloud infrastructure, and peer-to-peer network . The existing consistent hashing schemescan’t meet the requirements simultaneously, including full consistency,scalability, small memory footprint, low update time and low query complexity .…

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 .…

In Bed Person Monitoring Using Thermal Infrared Sensors

The world is expecting an aging population and shortage of healthcareprofessionals . This poses the problem of providing a safe and dignified lifefor the elderly . Technological solutions involving cameras can contribute to safety, comfort and efficient emergency responses, but they are invasive ofprivacy .…

On the Extended TSP Problem

We initiate the theoretical study of Ext-TSP, a problem that originates inthe area of profile-guided binary optimization . Given a graph $G=(V, E)$ withpositive edge weights $w: E \rightarrow R^+$ and a non-increasing discountfunction $f(\cdot)$ such that $f(1) = 1$ for $i k$ for someparameter $k$ That is part of the problem definition .…

Robust Risk Sensitive Reinforcement Learning Agents for Trading Markets

Trading markets are inherently a multiagent domain composed of many actors taking actions and changing theenvironment . To tackle these type of scenarios agents need to exhibit certaincharacteristics such as risk-awareness, robustness to perturbations and lowlearning variance . We propose a family of algorithms that use risk-averse functions and variance reduction techniques .…

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 .…

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 .…

Tableaux for Free Logics with Descriptions

The paper provides a tableau approach to definite descriptions . We focus on formalizations of the so-called minimal free description theory (MFD) The tableau systems formalise MFD based on PFL (positive free logic), NFL (negative free logic) and PQFL (the quasi-free counterparts of the former ones) Also the logic NQFLm is taken into account, which is equivalent to the logic of definedness applied in computer science and constructivemathematics for dealing with partial functions .…

Interacting Safely with an Unsafe Environment

We give a presentation of Pure type systems where contexts need not bewell-formed . We show that this presentation is equivalent to the usual one . The main motivation for this presentation was that, when we extend Pure type systemswith computation rules, we want to declare constants before the computation rules that are needed to check the type .…

A Functional Programming Language with Versions

Modern software development heavily uses versioned packages, but programming languages rarely support the concept of versions in their semantics . This paper proposes a programming language that intrinsically supports versions . The proposed core calculus, called Lambda VL, has versioned values, each containing different values under different versions .…

Pseudo labelling Enhanced Media Bias Detection

This paper proposes a simple but effective data augmentation method . It uses pseudo-labelling to select samples from noisy distantsupervision datasets . The result shows that the proposed methodimproves the accuracy of biased news detection models . The proposed method shows that it can be used to improve news detection accuracy .…

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 .…

Touring the MetaCoq Project Invited Paper

MetaCoq aims to provide the first fully-certified realistic implementation of a type checker for the full calculus underlying the Coq proofassistant . We show how theoretical tools such as bidirectional type-checking, Tait-Martin-L\”of/Takahashi’s confluence proof technique and monadic anddependently-typed programming can help construct the following artefacts: aspecification of Coq’s syntax and type theory, the Polymorphic Cumulative CumulativeCalculus of (Co)-Inductive Constructions (PCUIC); a monad for the manipulation of raw syntax and interaction with Coq system; a verification of PCUIC’smetatheory, whose main results are the confluence of reduction, typepreservation and principality of typing; a realistic, correct and completetype-checker for PCIC .…

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 .…

Learning to Limit Data Collection via Scaling Laws Data Minimization Compliance in Practice

Data minimization is a legal obligation defined in the European Union’s General Data Protection Regulation (GDPR) as the responsibility to process anadequate, relevant, and limited amount of personal data in relation to aprocessing purpose . However, unlike fairness or transparency, the principle has not seen wide adoption for machine learning systems due to a lack ofcomputational interpretation .…

On the Complexity of SPEs in Parity Games

We study the complexity of problems related to subgame-perfect equilibria(SPEs) in infinite duration non zero-sum multiplayer games . We present new complexity results that closegaps in the literature . Our techniques are based on a recent characterizationof SPEs in prefix-independent games that is grounded on the notions ofrequirements and negotiation, and according to which the plays supported by SPEs are exactly the plays consistent with the requirement that is the leastfixed point of the negotiation function .…

Nearest neighbor Methods and their Applications in Design of 5G Beyond Wireless Networks

Nearest neighbor (NN) methods are frequently employed for solving classification problems using supervisedlearning . Froman application standpoint, this article explores the challenges related to the5G and beyond wireless networks which can be solved using NN classificationtechniques . The article concisely introduces the theoretical background,algorithmic, and implementation aspects along with the key applications .…

More Robust Dense Retrieval with Contrastive Dual Learning

ContrastiveDual Learning for Approximate Nearest Neighbor (DANCE) is an effective training paradigm for dense retrieval . DANCE incorporates an additionaldual training object of query retrieval, inspired by the classic informationretrieval training axiom, query likelihood . With contrastive learning, the dualtraining object of DANCE learns more tailored representations for queries and documents to keep the embedding space smooth and uniform, thriving on theranking performance of Dance on the MS MARCO document retrieval task .…