Universally Optimal Distributed Algorithms for Known Topologies

Many distributed optimization algorithms achieve existentially-optimal running times . Still, most networks of interest allow forexponentially faster algorithms . We resolve these 25-year-old open problems in the known-topology setting . We provide several (equivalent) graph parameters and show theyare tight universal lower bounds for the above problems .…

Linear and Sublinear Time Spectral Density Estimation

We analyze the popular kernel polynomial method (KPM) for approximating the spectral density (eigenvalue distribution) of a symmetric (or Hermitian) matrix . We prove that a simple and practicalvariant of the KPM algorithm can approximate the accuracy in the Wasserstein-1 distance with roughly $O(n/\text{poly}(\epsilon)$ matrix-vector multiplications with $A$ This yields a provable linear timeresult for the problem .…

Determinisability of register and timed automata

We draw the complete decidability/complexitylandscape of the deterministic membership problem, in the setting of both register and timed automata . We prove that the problem is decidable when the input automaton is a one-clocknondeterministic timed automaton without epsilon transitions . We show that in all the other cases the problem in all other cases is undecidable, i.e.…

Congruence Relations for Büchi Automata

We revisit congruence relations for B\”uchi automata, which play acentral role in automata-based verification . The size of the classicalcongruence relation is in $3^{\mathcal{O}(n^2) We present improvedcongruences relations that can be exponentially more compact than the classical one . We further give asymptotically optimal Congruence Relations of size $2^{\Mathcal{{O }(n \log n)$ .…

Appearance Driven Automatic 3D Model Simplification

We present a suite of techniques for jointly optimizing triangle meshes andshading models to match the appearance of reference scenes . This capability has a number of uses, including appearance-preserving simplification of extremely complex assets, conversion between rendering systems, and even conversion between geometric scene representations .…

De rendering the World s Revolutionary Artefacts

Recent works have shown exciting results in unsupervised image de-rendering– learning to decompose 3D shape, appearance, and lighting from single-imagecollections without explicit supervision . We propose a method, termed RADAR, that can recover environment illumination and surface materials from realsingle-image collections, relying neither on explicit 3D supervision, nor on multi-view or multi-light images .…

Field Convolutions for Surface CNNs

We present a novel surface convolution operator acting on vector fields that is based on a simple observation . Instead of combining neighboring features with respect to a single coordinate parameterization, we have every neighbor describe the position of the point within its own frame .…

Beaming Displays

Existing near-eye display designs struggle to balance between multipletrade-offs such as form factor, weight, computational requirements, and batterylife . In this work, we address these trade-offs by,adoxically, removing the display . We present the beaming displays, a new type of near eye display system that uses aprojector and an all passive wearable headset .…

Reconstructing Recognizable 3D Face Shapes based on 3D Morphable Models

Many recent works have reconstructed distinctive 3D face shapes by combining shape parameters of the same identity and separating those of different people based on parametric models . However, despite the high accuracy in the face recognition task using these shape parameters, the visual discrimination of face shapes reconstructed from those parameters is unsatisfactory .…

Riggable 3D Face Reconstruction via In Network Optimization

This paper presents a method for riggable 3D face reconstruction frommonocular images . It jointly estimates a personalized face rig and per-imageparameters including expressions, poses, and illuminations . By estimating apersonalized face rig, our method goes beyond static reconstructions andenables downstream applications such as video retargeting .…

PlasticineLab A Soft Body Manipulation Benchmark with Differentiable Physics

PasticineLab includes a diverse collection of soft bodymanipulation tasks . In each task, the agent uses manipulators to deform theplasticine into the desired configuration . The underlying physics engines support differentiable elastic and plastic deformation using the DiffTaichisystem . We expect that PlasticineLab will encourage the development of novel algorithmsthat combine differentiable physics and RL for more complex physics-based skilllearning tasks .…

Top Score in Axelrod Tournament

The focus of the project will be an examination of obtaining the highest score in the Axelrod Tournament . The initial design of a strategy consisted of looking at the Cooperation rates of the top strategies . The eight-state FSM strategy was then evolved again using a full evolutionary algortihm process, which lasted 500 generations .…

What are Table Cartograms Good for Anyway An Algebraic Analysis

Table cartogram is a graphic which visualizes tabular data by bringing the areas of a grid of quadrilaterals into correspondence with the input data, like a heat map that has been “area-ed” rather than colored . Table cartograms are best suited to relatively small tables with ordinal axes for somecomparison and outlier identification tasks .…

Experiences with User Studies in Augmented Reality

The research field of augmented reality (AR) is of increasing popularity . To produce further advances in AR, it is not only necessary to create new systems or applications, but also to evaluate them . A better understanding offactors that could influence the design and results of user experience studies can help us to make them more robust and dependable in the future .…

Massive Access in Media Modulation Based Massive Machine Type Communications

The massive machine-type communications (mMTC) paradigm based on mediamodulation in conjunction with massive MIMO base stations (BSs) is emerging as a viable solution to support the massive connectivity for the future Internet-of-Things . This paper considers the DADD problem for both uncoded and coded media modulationbased mMTC with a slotted access frame structure, where the device activityremains unchanged within one frame .…

Optimal Resource Allocation for Full Duplex IoT Systems Underlaying Cellular Networks with Mutual SIC NOMA

Device-to-device (D2D) and non-orthogonal multiple access (NOMA) arepromising technologies to meet the challenges of the next generations of mobilecommunications in terms of network density and diversity for internet of things(IoT) services . This paper tackles the problem of maximizing the D2Dsum-throughput in an IoT system underlaying a cellular network, through optimalchannel and power allocation .…

One bit Spectrum Sensing with the Eigenvalue Moment Ratio Approach

One-bit analog-to-digital converter (ADC) performing signal sampling as anextreme simple comparator is an overwhelming technology for spectrum sensing . We propose a novel one-bit sensing approach based on the eigenvaluemoment ratio (EMR) which has been proved to be highly efficient for conventional multi-antenna spectrum sensing in $\infty$-bit situation .…

Securing NOMA Networks by Exploiting Intelligent Reflecting Surface

This paper investigates the security enhancement of an intelligent reflectingsurface (IRS) assisted non-orthogonal multiple access (NOMA) network . It proposes a novel ring-penaltybased successive convex approximation (SCA) algorithm to design powerallocation and phase shifts jointly . Numerical resultsvalidate the advantages of the proposed algorithms over the baseline schemes .…

Displacement Driven Approach to Nonlocal Elasticity

This study presents a physically consistent displacement-driven reformulation of the concept of action-at-a-distance, which is at the foundation of nonlocalelasticity . The (total) strain energy is guaranteed to be convex and positive-definite without imposing any constrainton the symmetry of the kernels .…

Learning to Coordinate via Multiple Graph Neural Networks

MGAN for collaborative multi-agentreinforcement learning is a new algorithm that combines graph convolutionalnetworks and value-decomposition methods . MGAN learns the representation of agents from different perspectives through multiple graph networks, and realizes the proper allocation of attention between all agents .…

Sound Probabilistic Inference via Guide Types

Probabilistic programming languages aim to describe and automate Bayesianmodeling and inference . Modern languages support programmable inference, which allows users to customize inference algorithms by incorporating guide programs . For Bayesian inference to be sound, guide programs must be compatible with model programs .…

Parameterized Complexity of Elimination Distance to First Order Logic Properties

The elimination distance to some target graph property P is a general graphmodification parameter introduced by Bulian and Dawar . We initiate the study ofelimination distances to graph properties expressible in first-order logic . Wedelimit the problem’s fixed-parameter tractability by identifying sufficientand necessary conditions on the structure of prefixes of first order logicformulas .…

On Salum s Algorithm for mathrm X3SAT

Latif Salum purports to give a polynomial-time algorithm that solves the $\mathrm{NP}-complete problem . The algorithm fixes the polarity of a variable, carries out simplifications over the resulting formula . One thing this algorithm does not do is backtrack. We give an illustrative counterexample showing why this algorithm is flawed .…

Hybrid QSS and Dynamic Extended Term Simulation Based on Holomorphic Embedding

Power system simulations that extend over a time period of minutes, hours, oreven longer are called extended-term simulations . Extended-term simulation is needed for many power system analysis tasks (e.g., resilience analysis, renewable energyintegration, cascading failures) The conventional approaches are insufficient for dealing with the extended-time simulation of multi-timescaleprocesses .…

Rethinking the Backdoor Attacks Triggers A Frequency Perspective

Backdoor attacks have been considered a severe security threat to deeplearning . Such attacks can make models perform abnormally on inputs with triggers and still retain state-of-the-art performance on cleandata . Many current backdoor attacks exhibit severe high-frequency artifacts, which persistacross different datasets and resolutions .…

An Object Detection based Solver for Google s Image reCAPTCHA v2

Previous work showed that reCAPTCHA v2’s image challenges could be solved byautomated programs armed with Deep Neural Network (DNN) image classifiers andvision APIs provided by off-the-shelf image recognition services . We propose afully automated object detection based system with an online success rate of 83.25%, the highestsuccess rate to date, and it takes only 19.93 seconds (including network delays) on average to crack a challenge .…

Prism Private Verifiable Set Computation over Multi Owner Outsourced Databases

Prism is a secret sharing based approach to compute privateset operations (i.e., intersection and union), as well as aggregates overoutsourced databases belonging to multiple owners . Prism enables data owners topre-load the data onto non-colluding servers and exploits the additive and multiplicative properties of secret-shares to compute the above-listedoperations in (at most) two rounds of communication between the servers and the querier .…

Decentralized Cross Network Identity Management for Blockchain Interoperation

Interoperation for data sharing between permissioned blockchain networksrelies on networks’ abilities to independently authenticate requests andvalidate proofs accompanying the data . This requires counterparty networks to know the identities andcertification chains of each other’s members . But permissioned networks are ad hoc consortia of existing organizations, whose network affiliations may not be well-known or well-established even though their individual identities are .…