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 .…

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 .…

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 .…

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 .…

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 …

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 .…

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 .…

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 .…

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 .…

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 .…

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 .…

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 .…

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 .…

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 .…