## How Good Is a Strategy in a Game With Nature

The usual probabilistic semantics very quickly leads toundecidability when considering either infinite game graphs orimperfect-information . We propose two alternative semantics that leads todecidability where probabilism one fails: one based on counting and onebased on topology . We consider games with two antagonistic players and a third,unpredictable and uncontrollable player, that we call Nature .…

## Automata for Hyperlanguages

Hyperproperties lift conventional trace properties from a set of executiontraces to sets of execution traces . We introduce hyperautomata for emhyperlanguages, which are languages over sets of words . We show that while nonemptiness is undecidable ingeneral, it is decidable for several fragments of NFH .…

## Real Time Visualization in Non Isotropic Geometries

Non-isotropic geometries are of interest to low-dimensional topologists,physicists and cosmologists . However, they are challenging to comprehend andvisualize . We present novel methods of computing real-time native geodesicrendering . Our methods can be applied not only tovisualization, but also are essential for potential applications in machinelearning and video games .…

## A Bridge between Polynomial Optimization and Games with Imperfect Recall

We show that solving games with imperfect recall is as hard as solving certain problems of the firstorder theory of reals . We establish square root sum hardness even for the class of A-loss games . On the positive side, we find restrictions on games and strategies motivated by Bridge bidding that give polynomial-timecomplexity .…

## My Fair Bandit Distributed Learning of Max Min Fairness with Multi player Bandits

N cooperative but non-communicating players where each plays one outof M arms for T turns . Players have different utilities for each arm,representable as an NxM matrix . These utilities are unknown to the players . In each turn players select an arm and receive a noisy observation of their utility for it .…

## Online Stochastic Max Weight Matching prophet inequality for vertex and edge arrival models

We provide prophet inequality algorithms for online weighted matching ingeneral (non-bipartite) graphs . The weight of each edge is drawn independently from an a-priori known probability distribution . We introduce a novel unified framework of batched prophet inequalities that captures online settings where elements arrive in batches .…

## Finite Time Last Iterate Convergence for Multi Agent Learning in Games

In this paper, we consider multi-agent learning via online gradient descent in a class of games called $lambda$-cocoercive games . We characterize the finite-time last-iterate convergence rate for joint OGD learning on these games . Further, we develop a fully adaptive algorithm that does not require any knowledge of problem parameter (e.g.…

## A spatio temporalisation of ALC D and its translation into alternating automata augmented with spatial constraints

The aim of this work is to provide a family of theories for spatial change in general and for motion of spatial scenes in particular . We consider a spatio-temporalisation MTALC(Dx), of the well-knownALC family of Description Logics . The roles split into m+n immediate-successor(accessibility) relations, which are serial, irreflexive and antisymmetric .…

## Buchi automata augmented with spatial constraints simulating an alternating with a nondeterministic and deciding the emptiness problem for the latter

The aim of this work is to thoroughly investigate Buchi automata augmentedwith spatial constraints . The input trees of such an automaton are infinitek-ary Sigma-trees, with the nodes standing for time points . Theconstraints, from an RCC8-like spatial Relation Algebra (RA) x, are used to impose spatial constraints on objects of the spatial scene .…

## FMore An Incentive Scheme of Multi dimensional Auction for Federated Learning in MEC

Promising federated learning coupled with Mobile Edge Computing (MEC) is considered as one of the most promising solutions to the AI-driven serviceprovision . In MEC, edgenodes would not like to voluntarily participate in learning, and they differ inthe provision of multi-dimensional resources .…

## A characterization of proportionally representative committees

A well-known axiom for proportional representation is Proportionality ofSolid Coalitions . We characterize committees satisfying PSC as possible outcomes of the Minimal Demand rule .…

## Compactly Representing Uniform Interpolants for EUF using conditional DAGS

The concept of a uniform interpolant for a quantifier-free formula from agiven formula with a list of symbols, while well-known in the logic literature,has been unknown to the formal methods and automated reasoning community . The first algorithm is non-deterministic andgenerates a uniforminterpolant expressed as a disjunction of conjunction ofliterals .…

## Concurrent Kleene Algebra with Observations from Hypotheses to Completeness

Concurrent Kleene Algebra (CKA) extends basic Kleene algebra with a parallelcomposition operator . However, CKA fundamentally misses tests, which are needed to model standardprogramming constructs such as conditionals and $\mathsf{while}$-loops . In this paper we provide a solution in the form of ConcurrentKleeneAlgebra with Observations .…

## DECIBEL Improving Audio Chord Estimation for Popular Music by Alignment and Integration of Crowd Sourced Symbolic Representations

Automatic Chord Estimation (ACE) is a fundamental task in Music InformationRetrieval (MIR) The task consists of segmenting a music recording or score and assigning a chord label to each segment . DECIBEL improves all tested state-of-the-art ACEmethods by over 3 percent on average .…

## Multi Representation Knowledge Distillation For Audio Classification

The framework takes multiple representations as the input to train themodels in parallel . The complementary information provided by different representations is shared by knowledge distillation . The proposed approach can improve the classificationperformance and achieve state-of-the-art results on both acoustic sceneclassification tasks and general audio tagging tasks .…

## Modeling the Invariance of Virtual Pointers in LLVM

Devirtualization is a compiler optimization that replaces indirect (virtual)function calls with direct calls . It is particularly effective in languages such as Java or C++, in which virtual methods are abundant . We present a novel abstract model to express the lifetimes of C++ dynamicobjects and invariance of virtual table pointers in the LLVM intermediaterepresentation .…

## PBS Calculus A Graphical Language for Coherent Control of Quantum Computations

The PBS-calculus is inspired by quantum optics, in particular the polarising beam splitter (PBS for short) We formalise the syntax and semantics of the PBS-diagrams . We equip the language with an equationaltheory, which is proved to be sound and complete .…

## Hysteresis and disorder induced order in continuous kinetic like opinion dynamics in complex networks

In this work we tackle a kinetic-like model of opinions dynamics in anetworked population endued with a quenched plurality and polarization . We consider pairwise interactions that are restrictive, which ismodeled with a smooth bounded confidence . Our results show the interestingemergence of nonequilibrium hysteresis and heterogeneity-assisted ordering .…

## Adversarial Impacts on Autonomous Decentralized Lightweight Swarms

The decreased size and cost of Unmanned Aerial Vehicles (UAVs) has enabled the use of swarms of unmanned autonomous vehicles to accomplish a variety of tasks . This work investigates the influencesthat can compromise the functionality of an autonomous swarm leading to cascading vulnerabilities .…

## Fine Grained Instance Level Sketch Based Video Retrieval

Existing sketch-analysis work studies sketches depicting static objects or scenes . In this work, we propose a novel cross-modal retrieval problem offine-grained instance-level sketch-based video retrieval (FG-SBVR) We show that this model significantly outperforms anumber of existing state-of-the-art models designed for video analysis.…

## Blind Omnidirectional Image Quality Assessment with Viewport Oriented Graph Convolutional Networks

Quality assessment of omnidirectional images has become increasingly urgent due to the rapid growth of virtual reality applications . We propose a novel Viewportoriented Graph Convolution Network (VGCN) for blind omniddirectional imagequality assessment (IQA) The proposed graph is inspired by the characteristics of the human vision system (HVS) and theviewing process of Omnidirectionable contents .…

## Exponential Automatic Amortized Resource Analysis

Automatic amortized resource analysis (AARA) is a type-based technique forinferring concrete (non-asymptotic) bounds on a program’s resource usage . The soundness of exponential AARA is proved with respect to anoperational cost semantics . A key idea is theuse of the Stirling numbers of the second kind as the basis of potentialfunctions, which play the same role as the binomial coefficients in polynomialAARA .…

## Symbolic Execution Game Semantics

We present a framework for symbolically executing and model checkinghigher-order programs with external (open) methods . We combine traditional symbolic executiontechniques with operational game semantics to build a symbolic executionsemantics that captures arbitrary external behaviour . This yields a bounded technique by imposing bounds on the depth of recursion and callbacks .…

## Hyperbolic Minesweeper is in P

We show that, while Minesweeper is NP-complete, its hyperbolic variant is inP . Our proof does not rely on the rules of the game, but is valid for any puzzle based on satisfying local constraints .…

## Geometric rank of tensors and subrank of matrix multiplication

The geometric rank is an upper bound on the subrank of tensors and the independence number of hypergraphs . We prove it is smaller than the slice rank of Tao, and relategeometric rank to the analytic rank of Gowers and Wolf in an asymptotic fashion .…

## Temporal Constraint Satisfaction Problems in Fixed Point Logic

Finite-domain constraint satisfaction problems are either solvable by Datalog, or not even expressible in fixed-point logic with counting . For infinite-domain CSPs, the situation is more complicated even if the template structure of the CSP is model-theoretically tame . We prove that there is no Maltsev condition that characterizes Dalog already for theCSPs of first-order reducts of (Q; <) We also prove that many of the equivalent conditions in the finite fail to capture expressibility in Datalogs or fixed point logic . The border between the two regimes coincides with an important dichotomy in universalalgebra; in particular, the border can be described by a strong height-one …

## Gowers norms for automatic sequences

We show that any automatic sequence can be separated into a structured part and a Gowers uniform part in a way that is considerably more efficient than the Arithmetic Regularity Lemma . For sequences produced bystrongly connected and prolongable automata, the structured part is rationallyalmost periodic, while for general sequences the description is marginally more complicated .…

## Algorithms and Lower Bounds for de Morgan Formulas of Low Communication Leaf Gates

The class $FORMULA[s] \circ \mathcal{G}$ consists of Boolean functionscomputable by size-$s$ de Morgan formulas . We give lower bounds and (SAT, Learning,and PRG) algorithms . We show: (1) The Generalized Inner Product function $GIP^k_n$ cannot be computed in $formulA[n^{1.99}]\circ . (2) There is a PRG of seed length$n/2 + O\left(\sqrt{s} \cdotR^{(2)(\mathcal {G}))\right) The Minimum Circuit Size Problem is not in $FORMula[n\circ XOR$.…

## The Complexity of Aggregates over Extractions by Regular Expressions

Regular expressions with capture variables, also known as “regex formulas,” extract relations of spans (intervals identified by their start and endindices) from text . Fagin et al. introduced regular documentspanners which are the closure of regex formulas under Relational Algebra .…

## Combining Partial Specifications using Alternating Interface Automata

In interface theory and model-based testing withinputs and outputs, conjunctive operators have been introduced . In the theory of alternatingautomata, conjunction and non-determinism are core aspects . Alternating automata have not been considered in the context of inputs and outputs .…

## From Stateless to Stateful Priorities Technical Report

We present the notion of stateful priorities for imposing preciserestrictions on system actions, in order to meet safety constraints . Given a system modeled as a network of discrete automata and anerror constraint, we present algorithms which use those inputs to synthesizestateful priorities .…

## Equivalence Testing of Weighted Automata over Partially Commutative Monoids

We study testing of automata over partiallycommutative monoids (pc monoids) and show efficient algorithms in specialcases, exploiting the structure of the underlying non-commutation graph of themonoid . We obtain the first deterministic quasi-polynomial time algorithms formultiplicity equivalence testing of $k$-tape automata and for equivalencetesting of deterministic $k-taped automata for constant$k\$.…

## On polynomial recursive sequences

Thesesequences arise naturally in the study of nonlinear extensions of weightedautomata, where (non)expressiveness results translate to class separations . Atypical example of a polynomial recursive sequence is b_n=n!. Our main result is that the sequence u_n =n^n is not polynomorphic .…

## A Survey on Deep Geometry Learning From a Representation Perspective

Researchers have now achieved great success on dealing with 2D images using deep learning . In recent years, 3D computer vision and Geometry Deep Learning has gained more and more attention . Many advanced techniques for 3D shapes have been proposed for different applications .…

## Distributed No Regret Learning in Multi Agent Systems

In this tutorial article, we give an overview of new challenges and results on distributed no-regret learning in multi-agent systems . Four emerging gamecharacteristics—dynamicity, incomplete and imperfect feedback, boundedrationality, and heterogeneity—that challenge canonical game models are explored . For each of the four characteristics, we illuminate its implications and ramifications in game modeling .…