District Fair Participatory Budgeting

Participatory budgeting is a method used by city governments to select public projects to fund based on residents’ votes . Decision making that only takes globalsocial welfare into account can be unfair to districts . We propose a notion offairness that guarantees each district at least as much welfare as it would have received in a district-level election .…

Edge Deletion to Restrict the Size of an Epidemic

The goal is to remove minimum number ofedges such that the resulting graph does not contain any $F\in \mathcal{F}$ as a subgraph . For the parameter treewidth, the question of whether the problem isFPT has remained open . Here we give a negative answer by showing that theproblem is W[1] hard when .…

Validation Obligations A Novel Approach to Check Compliance between Requirements and their Formal Specification

Traditionally, practitioners use formal methods pre-dominately for one half of the quality-assurance process: verification . The other half — validation (do we build the right software?) — has comparatively little attention . The proposed approach — “validation obligations” — is based on the simple ideathat both verification and validation are an integral part of all refinementsteps of a system .…

Recognizability of languages via deterministic finite automata with values on a monoid General Myhill Nerode Theorem

This paper deals with the problem of recognizability of functions l: Sigma*–M that map words to values in the support set M of a monoid (M,.,1) These functions are called M-languages . The characterization of an M-language l is based on providing aright congruence on Sigma* that is defined through l .…

Neural BRDF Representation and Importance Sampling

We present a compact neuralnetwork-based representation of BRDF data that combines high accuracy with efficient practical rendering via built-in interpolation of reflectance . We encode BRDFs as lightweight networks, and propose a trainingscheme with adaptive angular sampling, critical for the accurate reconstruction of specular highlights .…

b Surf Interactive Bézier Splines on Surfaces

B\’ezier curves provide the basic building blocks of graphic design in 2D . We show that directextensions of the De Casteljau and Bernstein evaluation algorithms to themanifold setting are fragile, and prone to discontinuities when controlpolygons become large . Conversely, approaches based on subdivision are robust and can be implemented efficiently .…

Differentiable Implicit Soft Body Physics

Differentiable soft-body physics simulator can be composed with neural networks as a differentiable layer . We present an energy-based approach that allows us to compute these derivativesautomatically and in a matrix-free fashion via reverse-mode automaticdifferentiation . We demonstrate the effectiveness of our differentiablesimulator in policy optimization for locomotion tasks and show that it achieves better sample efficiency than model-free reinforcement learning .…

3D Custom Fit Garment Design with Body Movement

We propose an interactive design tool for creating custom-fitgarments based on 3D body scans of the intended wearer . Our method explicitlyincorporates transitions between various body poses to ensure a better fit and freedom of movement . We alternate between cloth simulation stepsand rest shape adjustment steps based on stretch to achieve the final shape of the garment .…

Regret stability and fairness in matching markets with bandit learners

We consider the two-sided matching market with bandit learners . In the standard matching problem, users and providers are matched to ensure incentive compatibility via the notion of stability . While some agents incur low regret under these matchings, others can incur high regret .…

A Logic for Conditional Local Strategic Reasoning

We study and formalise thereasoning of an agent, or of an external observer, about the expected choices of action of the other agents based on their objectives . To formalize such reasoning we extend Pauly’s Coalition Logic with three newmodal operators of conditional strategic reasoning .…

A Survey on Synchronous Augmented Virtual and Mixed Reality Remote Collaboration Systems

A total of 82 unique systems for remote collaboration are discussed, including more than 100 publications and 25 commercial systems . A thorough overview of existing systems is given, categorising their main contributions in order to help researchers working in different fields by providing concise information about specifictopics such as avatars, virtual environment, visualisation styles and interaction .…

The vote Package Single Transferable Vote and Other Electoral Systems in R

The vote package in R implements the plurality (orfirst-past-the-post), two-round runoff, score, approval and single transferablevote (STV) electoral systems . It also implements a new variant of STV, in which a minimum number of candidates from a specified group are required to be elected .…

Detecting corruption in single bidder auctions via positive unlabelled learning

Single-bidder rate is a proxy of corruption in public procurement . But it is not evidence of a corrupt auction, but an uncompetitive auction . Uncompetitive auction could arise due to a corrupt procurer attempting to conceal the transaction, but it could also be a result of geographicisolation, monopolist presence, or other structural factors .…

Artificial intelligence in communication impacts language and social relationships

Artificial intelligence (AI) is now widely used to facilitate social interaction, but its impact on social relationships and communication is not well understood . We study the social consequences of one of the most pervasive AI applications: algorithmic response suggestions .…

Personalized Embedding based e Commerce Recommendations at eBay

Recommender systems are an essential component of e-commerce marketplaces, helping consumers navigate massive amounts of inventory and find what they need . In this paper, we present an approach for generating personalized item recommendations by learning to embed items and users in the same vector space .…

Fairness Through Regularization for Learning to Rank

Previous work on fair ranking has mostly focused on application-specific fairness notions, often tailored to online advertising . In thiswork, we show how to transfer numerous fairness notions from binaryclassification to a learning to rank context . An extensive experimental evaluation shows that our method canimprove ranking fairness substantially with no or only little loss of model quality .…

Robust Generalization and Safe Query Specialization in Counterfactual Learning to Rank

Counterfactual Learning to Rank (LTR) methods often optimizetabular models that memorize the optimal ranking per query . Feature-based models provide robust performance across many queries, but available features often limit the rankings the model can predict . In contrast, tabular models converge on any possible ranking through memorization .…

Freudian and Newtonian Recurrent Cell for Sequential Recommendation

A sequential recommender system aims to recommend attractive items to users based on behaviour patterns . We propose a novel recurrent cell, namely FaNC, from Freudian and Newtonian perspectives . FaNCdivides user’s state into conscious and unconscious states, and the user’s decision process is modelled by Freud’s two principles: the pleasure principleand reality principle .…

An Affective Aware Pseudo Association Method to Connect Disjoint Users Across Multiple Datasets An Enhanced Validation Method for Text based Emotion Aware Recommender

The approach interconnects users with different user IDs across different datasets through the most similar users’ emotion vectors (UVECs) We found themethod improved the evaluation process of assessing the top-N recommendation sobjectively. We advocate an emotionaware Pseudo Association Method to associate users across different data files.…

Millimeter Wave MIMO based Depth Maps for Wireless Virtual and Augmented Reality

Augmented and virtual reality systems (AR/VR) are rapidly becoming key components of the wireless landscape . For immersive AR/VR experience, thesedevices should be able to construct accurate depth perception of the surrounding environment . The performance of these depth cameras,however, has clear limitations in several scenarios, such as the cases withshiny objects, dark surfaces, and abrupt color transition among otherlimitations .…

Polynomial Approximations of Conditional Expectations in Scalar Gaussian Channels

We consider a channel $Y=X+N$ where $X$ is a random variable satisfying$\mathbb{E}[|X|]<\infty$ and $N$ is an independent standard normal random variable . We show that the minimum mean-square error estimator of $X$X from $Y,$ which is given by the conditional expectation $Y$ is apolynomial . We also prove that the higher-order derivatives of $y$y \mapsto \mid Y=y]$areexpressible as multivariate polynomials in the functions$y = y for $k\in \mathbb {N}.$ These expressions yield bounds on the $2$-norm of thederivatives of the …

Theoretical and Experimental Perspectives of Quantum Verification

In this perspective we discuss verification of quantum devices in the context of specific examples, formulated as proposed experiments . We focus in particular onprotocols using randomized measurements, and we propose establishing a centraldata repository, where existing experimental devices and platforms can be compared .…

Near field Tracking with Large Antenna Arrays Fundamental Limits and Practical Algorithms

Applications towards 6G have brought a huge interest towards arrays with a huge number of antennas . Plane wave approximation is often not accurate because the system mayoperate in the near-field propagation region (Fresnel region) where theelectromagnetic field wavefront is spherical .…

On the Performance of the Primary and Secondary Links in a 3 D Underlay Cognitive Molecular Communication

Molecular communication often involves coexisting links where certain links have priority over others . Mutual influence of FARs existing in the samecommunication medium results in competition for capturing the information-carrying molecules . We show that the simple transmit control strategy at the secondarytransmitter can improve the performance of the overall system .…

Fisher Information and Mutual Information Constraints

We show that if the statisticalmodel has a sub-Gaussian score function, the trace of the Fisherinformation matrix for estimating $X$ from $Y$ can scale at most linearly . We apply this result to obtainminimax lower bounds in distributed statistical estimation problems, and obtaina tight preconstant for Gaussian mean estimation .…

Lenient Regret and Good Action Identification in Gaussian Process Bandits

In this paper, we study the problem of Gaussian process (GP) bandits underrelaxed optimization criteria stating that any function value above a certain threshold is “good enough” We provide upper bounds on the lenient regret for GP-UCB and anelimination algorithm .…

Rate Splitting Multiple Access for Multigateway Multibeam Satellite Systems with Feeder Link Interference

This paper studies the precoder design problem of achieving max-min fairness(MMF) amongst users in multigateway multibeam satellite communication system . We propose a beamforming strategy based on a transmission scheme known as rate-splitting multiple access . RSMA relies on multi-antenna rate splitting at the transmitter and .successive…

Massive MIMO under Double Scattering Channels Power Minimization and Congestion Controls

This paper considers a massive MIMO system under the double scattering channels . We derive a closed-form expression of the uplink ergodic spectralefficiency (SE) by exploiting the maximum-ratio combining technique . We then formulate and solve a total uplinkdata power optimization problem that aims at simultaneously satisfying therequired SEs from all the users with limited power resources .…

Proof Artifact Co training for Theorem Proving with Language Models

PACT is a general methodology forextracting abundant self-supervised data from kernel-level proof terms for training . We instrument Lean with aneural theorem prover driven by a Transformer language model . We show that PACTimproves theorem proving success rate on a held-out suite of test theorems from32\% to 48\% .…

Zero one laws for provability logic Axiomatizing validity in almost all models and almost all frames

Halpern and Kapron proved zero-one laws for classes ofmodels corresponding to modal logics K, T, S4, and S5 . As the number ofelements of finite models increases, every formula holds either in almost all or in almost no models of that size .…

A formal proof of modal completeness for provability logic

This work presents a formalized proof of modal completeness for G\”odel-L\”obprovability logic (GL) in the HOL Light theorem prover . We describe the code wedeveloped, and discuss some details of our implementation . We also propose areflection on our own experience in using this specific theorem provers for this task, with an analysis of pros and cons of reasoning within andabout the formal system for GL we implemented in our code .…

Interpreting a concurrent λ calculus in differential proof nets extended version

In this paper, we show how to interpret a language featuring concurrency,references and replication into proof nets . We prove a simulation and adequacy theorem . A key element in our translation are routing areas, a family of nets used to implement communication primitives .…

Common Information Belief based Dynamic Programs for Stochastic Zero sum Games with Competing Teams

Decentralized team problems where players have asymmetric information about the state of the underlying stochastic system have been actively studied, butgames between such teams are less understood . We provide bounds on the upper (min-max) and lower (max-min) values of the game .…

Automated and Distributed Statistical Analysis of Economic Agent Based Models

We propose a novel approach to the statistical analysis of simulation models . Our main goal is to provide a fullyautomated and model-independent tool-kit to inspect simulations and performcounterfactual analysis . Our approach: (i) is easy-to-use by the modeller, (ii)improves reproducibility of results, (iii) optimizes running time given themodeller’s machine, (iv) automatically chooses the number of requiredsimulations and simulation steps to reach user-specified statisticalconfidence .…

A Subcell Finite Volume Positivity Preserving Limiter for DGSEM Discretizations of the Euler Equations

In this paper, we present a positivity-preserving limiter for nodalDiscontinuous Galerkin disctretizations of the compressible Euler equations . We show that our strategy is able to ensurerobust simulations with positive density and pressure when using the standardand the split-form DGSEM .…

Performance of nonconforming spectral element method for Stokes problems

The numerical method is nonconforming and higher order spectral element functions are used . The normal equations in the least-squares formulation are solved efficiently using preconditioned conjugate gradient method . Various testcases are considered including the Stokes problem on curvilinear domains,Stokes problem with mixed boundary conditions and a generalized stokes problemin \mathbb{R}^{3} to verify the accuracy of the method .…

Novel multi step predictor corrector schemes for backward stochastic differential equations

Novel multi-step predictor-corrector numerical schemes have been derived for approximating decoupled forward-backward stochastic differential equations . The stability and high order rate of convergence of the schemes are proved . Numerical experiments are given to illustrate the stability and convergence rates of the proposed methods .…

Higher order generalized α methods for parabolic problems

High-ordertime integrators can deliver the optimal performance of highly-accurate androbust spatial discretizations such as isogeometric analysis . We propose a new class of high-order time-marching schemes with dissipationuser-control and unconditional stability for parabolic equations . The method delivers unconditional stability and second-orderaccuracy in time and controls the numerical dissipation in the discretespectrum’s high-frequency region .…

Divergence conforming methods for transient doubly diffusive flows A priori and a posteriori error analysis

The analysis of the double-diffusion model and $\mathbf{H}(\mathrm{div)$-conforming method is extended to the time-dependentcase . The resulting methods are applied to simulatethe sedimentation of small particles in salinity-driven flows . The methodconsists of Brezzi-Douglas-Marini approximations for velocity and compatible piecewise discontinuous pressures .…

Numerical analysis of a new formulation for the Oseen equations in terms of vorticity and Bernoulli pressure

A variational formulation is introduced for the Oseen equations written interms of vor\-ti\-city and Bernoulli pressure . The velocity is fully decoupledusing the momentum balance equation, and it is later recovered by apost-process . A finite element method is also proposed, consisting of inequal-order N\’ed\’elec finite elements and piecewise continuous polynomials for the vorticity and the pressure, respectively .…

Deep Reinforcement Learning for Combinatorial Optimization Covering Salesman Problems

This paper introduces a new deep learning approach to approximately solve theCovering Salesman Problem (CSP) In this approach, given the city locations of a CSP as input, a deep neural network model is designed to directly output the solution . It is trained using the deep reinforcement learning withoutsupervision .…

Searching for Designs in between

Evolutionary methods in design and art are increasing in diversity and popularity . We use a biologically-inspired generativesystem capable of producing 3D objects that can be exported directly as 3Dprinting toolpath instructions . For the search stage of our system we combinethe use of the CMA-ES algorithm for optimisation and linear interpolation between generated objects for feature exploration .…

Anomaly Detection through Transfer Learning in Agriculture and Manufacturing IoT Systems

IoT managers have to judiciously detect failures(anomalies) in order to reduce their cyber risk and operational cost . In agriculture the data is often sparse, due to the vast areas of farms and the requirement to keep the cost of monitoring low .…

End to End Delay Guaranteed SFC Deployment A Multi level Mapping Approach

Network Function Virtualization (NFV) enables service providers to maximiz business profit via resource-efficient QoS provisioning for customerrequested Service Function Chains (SFCs) In recent applications, end-to-enddelay is one of the crucial QoS requirement needs to be guaranteed in SFC deployment . A two-level mapping algorithm is developed, that at thefirst level, maps the functions of the SFCs to virtual network functioninstances; in the second level, deploys the instances in the physicalnetwork .…

The Benefit of the Doubt Uncertainty Aware Sensing for Edge Computing Platforms

State-of-the-artuncertainty estimation techniques are computationally expensive when applied to resource-constrained devices . Our aim is to enable already trained deep learning modelsto generate uncertainty estimates on resource-limited devices at inference time . We demonstrate that it yields better performance and flexibility over previous work based on multilayerperceptrons to obtain uncertainty estimates .…

Talking After Lights Out An Ad Hoc Network for Electric Grid Recovery

When the electric grid in a region suffers a major outage, e.g., after acatastrophic cyber attack, a “black start” may be required . To ensure safe and effective black start, the grid control center hasto be able to communicate with field personnel and with supervisory control and SCADA systems .…

In this paper, we propose the use of two Passive Optical Network (PON)-based architectures to connect free-space Optical Wireless Communication(OWC) Access Points (APs) within a room . We optimizethrough a Mixed Linear Integer Programming (MILP) model the assignment of mobile OWC users to more than one AP to improve the resilience of the fronthaul network .…

kPAM 2 0 Feedback Control for Category Level Robotic Manipulation

In this paper, we explore generalizable, perception-to-action roboticmanipulation for precise, contact-rich tasks . In particular, we contribute aframework for closed-loop robotic manipulation that automatically handles acategories of objects . We first augment keypoints with orientation information . We propose a novel object-centric action representation in terms of regulating the linear/angularvelocity or force/torque of these oriented keypoints .…

Speculative Path Planning

Speculative Path Planning aims to accelerate thesearch when there are abundant idle resources . The key idea of our approach ispredicting future state expansions relying on patterns among expansions andaggressively parallelize the computations of prospective states . This method allows us to maintain the same search order as of vanilla A* andsafeguard any optimality guarantees .…

Robotic Tool Tracking under Partially Visible Kinematic Chain A Unified Approach

A particle filter method is presented and tested in simulation and on two real world robots to estimate the LumpedError . The Lumped Error is the result of Lumping Error since it lumps together the errors ofcalibration and joint angle measurements .…