On the Application of BAC NOMA to 6G umMTC

This letter studies the application of backscatter communications (BackCom)assisted non-orthogonal multiple access (BAC-NOMA) to the envisionedsixixth-generation (6G) ultra-massive machine type communications (umMTC) Inparticular, the proposed BAC-nOMA transmission scheme can realize simultaneousenergy and spectrum cooperation between uplink and downlink users . Computer simulations areprovided to demonstrate the superior performance of BAC NOMA .…

Tightening the Dependence on Horizon in the Sample Complexity of Q Learning

Q-learning seeks to learn the optimal Q-function of a Markov decisionprocess (MDP) in a model-free fashion . To yield an entrywise $\varepsilon$-accurate estimate of the optimal function, state-of-the-arttheory requires at least an order of $\frac{|\mathcal{S}||\mathCal{A}|}{(1-\gamma)$ (up to somelogarithmic factor) for any $0 <1, leading to an order-wiseimprovement in terms of the effective horizon $1-1- \gamma . Our finding unveils the effectiveness of vanilla Q-learning, which matches that of speedy Q- learningwithout requiring extra computation and storage . A key ingredient of ouranalysis lies in the establishment of novel error decompositions andrecursions . …

On Graph Matching Using Generalized Seed Side Information

The graph matchingproblem emerges naturally in various applications such as social networkde-anonymization, image processing, DNA sequencing, and natural language processing . In this paper, matching pairs of stocahstically generated graphs in the presence of generalized seed side-information is considered . The objective is to leverage thecorrelation among the edges of the graphs along with the side information provided in the form of ambiguity sets to recover the labels of the vertices in the second graph .…

A Computability Perspective on Verified Machine Learning

There is a strong consensus that combining the versatility of machinelearning with the assurances given by formal verification is highly desirable . Weconsider this question from the (unexpected?) perspective of computableanalysis . This allows us to define the computational tasks underlying verifiedML in a model-agnostic way, and show that they are in principle computable .…

Complete Bidirectional Typing for the Calculus of Inductive Constructions

This article presents a bidirectional type system for the Calculus ofInductive Constructions (CIC) It introduces a novel judgement intermediate between the usual inference and checking, dubbed constrained inference, to handle the presence of computation in types . The key property is the completeness of the system with respect to the usual undirected one, which has been proven in Coq as a part of the MetaCoq project .…

Intelligent Software Web Agents A Gap Analysis

Semantic web technologies have shown their effectiveness, especially when it comes to knowledge representation, reasoning, and data integrations . However, the original semantic web vision, whereby machine readable web data could beautomatically actioned upon by intelligent software web agents, has yet to berealised .…

Interview Hoarding

Many centralized matching markets are preceded by interviews between the participants . We study the impact on the final match of an increase to thenumber of interviews one side of the market can participate in. Our motivationis the match between residents and hospitals where, due to the COVID-19pandemic, interviews for the 2020-21 season of the NRMP match have switched to a virtual format.…

Fair Robust Assignment using Redundancy

We study the consideration of fairness in redundant assignment formulti-agent task allocation . Solving this problem optimally is NP-hard . We exploit properties ofsupermodularity to propose a polynomial-time, near-optimal solution . Empirically, our algorithm outperforms benchmarks, scales to large problems, and provides improvements in both fairness and average utility.…

Deep learning architectural designs for super resolution of noisy images

Advances in deep learning have led to significant improvements insingle image super-resolution research . However, state-of-the-art methods often fail atconstructing high-resolution images from noisy versions of theirlow-resolution counterparts . In-network design obtains the strongest results when the typeof image corruption is aligned in the training and testing dataset, for any choice of denoiser .…

From perspective maps to epigraphical projections

The projection onto the epigraph or a level set of a closed proper convexfunction can be achieved by finding a root of a scalar equation . The approach is based on the variational-analytic properties of general convexoptimization problems that are (partial) infimal projections of the sum of the function in question and the perspective map of a convex kernel .…

Low precision logarithmic number systems Beyond base 2

Logarithmic number systems (LNS) are used to represent real numbers in many applications using a constant base raised to a fixed-point exponent making its distribution exponential . This greatly simplifies hardware multiply, divide andsquare root . LNS with base-2 is most common, but in this paper we show that for low-precision LNS the choice of base has a significant impact .…

Numerical investigation of Mach number consistent Roe solvers for the Euler equations of gas dynamics

Traditional approaches to prevent the carbuncle phenomenon in gasdynamics simulations increase the viscosity on entropy and shear waves nearshocks . The goal is to achieve what, in thispaper, we call Mach number consistency . We take the simple approach that was used for the proof of concepttogether with the simple model for the increased numerical viscoity on linearwaves .…

A fast and scalable computational framework for goal oriented linear Bayesian optimal experimental design Application to optimal sensor placement

Optimal experimental design (OED) is a principled framework for maximizing information gained from limited data in inverse problems . We develop a fast andscalable computational framework for goal-oriented OED of large-scale Bayesianlinear inverse problems that finds sensor locations to maximize the expectedinformation gain (EIG) for a predicted quantity of interest .…

A space time discretization of a nonlinear peridynamic model on a 2D lamina

Peridynamics is a nonlocal theory for dynamic fracture analysis consisting in a second order in time partial integro-differential equation . We implement a spectral method for the space discretization based on the Fourier expansion of the solution . This computational approach takes advantages from theconvolutional form of the peridynamic operator and from the use of the discreteFourier transform .…

Exactness and Convergence Properties of Some Recent Numerical Quadrature Formulas for Supersingular Integrals of Periodic Functions

In a recent work, we developed three compact numerical quadratureformulas for finite-range periodic supersingular integrals $I[f[f]=t/n$ with $h=T/n . We prove that these formulas have spectral accuracy . We also prove that, when $u(z)$ is analytic in astrip $Im, the errors in all three formulas are $O(e^{-2n\pi\sigma/T)$ as$n\to\infty$ for all practical purposes .…

Robust Hybrid High Order method on polytopal meshes with small faces

We design a Hybrid High-Order scheme for the Poisson problem that is robust on polytopal meshes in the presence of small edges/faces . We stategeneral assumptions on the stabilisation terms involved in the scheme, underwhich optimal error estimates are established with multiplicative constants that do not depend on the maximum number of faces in each element, or the relative size between an element and its faces .…

Well posedness theory for nonlinear scalar conservation laws on networks

We consider nonlinear scalar conservation laws posed on a network . We establish $L^1$ stability, and thus uniqueness, for weak solutions satisfying the entropy condition . We demonstrate themethod’s properties through several numerical experiments . In one important case — for monotone fluxes with an upwinddifference scheme — we show that the set of (discrete) stationary solutions is sufficiently large to suit our general theory .…

Visualizing hierarchies in scRNA seq data using a density tree biased autoencoder

Single cell RNA sequencing (scRNA-seq) data makes studying the development of cells possible at unparalleled resolution . Given that many cellulardifferentiation processes are hierarchical, their scRNA-sequencing data is expected to be approximately tree-shaped in gene expression space . Inference andrepresentation of this tree-structure in two dimensions is highly desirable forbiological interpretation and exploratory analysis .…

Neural Architecture Search as Program Transformation Exploration

Improving the performance of deep neural networks is important to both the compiler and neural architecture search (NAS) communities . We express neural architectureoperations as program transformations whose legality depends on a notion ofrepresentational capacity . This allows them to be combined with existing transformations into a unified optimization framework .…

High Order Control Lyapunov Barrier Functions for Temporal Logic Specifications

Recent work has shown that stabilizing an affine control system to a desired state while optimizing a quadratic cost subject to state and controlconstraints can be reduced to a sequence of Quadratic Programs . In this paper, we generalize HOCBFs to High OrderControl Lyapunov-Barrier Functions (HOCLBFs) We also show that the proposed HOCLFs can be used to guarantee the Boolean satisfaction of Signal TemporalLogic (STL) formulae over the state of the system .…

Customizable Stochastic High Fidelity Model of the Sensors and Camera onboard a Low SWaP Fixed Wing Autonomous Aircraft

The navigation systems of autonomous aircraft rely on the readings provided by a suite of onboard sensors to estimate the aircraft state . Anaccurate representation of the behavior and error sources of each of thesesensors, together with the images generated by the cameras, in indispensable for flight simulation and the evaluation of novel inertial or visual navigational algorithms .…