Auto FuzzyJoin Auto Program Fuzzy Similarity Joins Without Labeled Examples

Fuzzy similarity join is an important database operator widely used in practice . We study the problem of “auto-program” fuzzy-joins . We develop an unsupervised framework that can infer suitable fuzzy-join programson given input tables . Using this framework users only need to provide two input tables $L$ and $R$ and a desired precision target $tau$ (say 0.9) The proposed\textsc{Auto-FuzzyJoin} significantly outperforms existing un-supervised approaches, and is surprisingly competitive even against supervised approaches such as Magellan and DeepMatcher .…

Adaptive Coding for Matrix Multiplication at Edge Networks

Edge computing is emerging as a new paradigm to allow processing data at theedge of the network . Coded computation advocates mixing data in sub-tasks by employing erasure codes and offloading them to other devices for computation . We show that ACM^2 improves the task completion delay significantly as compared to existing coded matrix multiplication algorithms .…

On the Termination of Some Biclique Operators on Multipartite Graphs

We define a new graph operator, called the weak-factor graph, which comes from the context of complex network modelling . We show that the multipartite graph on which the series terminates has a nice combinatorial structure: we exhibit a bijection between its vertices and the chains of the inclusion order on the intersections of the maximal cliques of the input graph .…

Fair Share Allocations for Agents with Arbitrary Entitlements

We consider the problem of fair allocation of indivisible goods to $n$agents, with no transfers . When agents have equal entitlements, the wellestablished notion of the maximin share (MMS) serves as an attractive fairnesscriterion . We introduce a new notion of a share, the AnyPrice share (APS) that is appropriate for settings witharbitrary entitlements .…

LCD Codes from tridiagonal Toeplitz matrice

Double Toeplitz (DT) codes are codes with a generator matrix of the form$(I,T)$ with $T$ a constant on the diagonals parallel to the main . When $T$. is tridiagonal and symmetric we determine itsspectrum explicitly by using Dickson polynomials . Using a special concatenation process, weconstruct optimal or quasi-optimal examples of binary and ternary LCD codes .…

Channel Estimation for Underwater Acoustic OFDM Communications An Image Super Resolution Approach

In this paper, we devoteto design a well-performing and pilot-saving neural network for the channelestimation in underwater acoustic (UWA) orthogonal frequency divisionmultiplexing (OFDM) communications . By considering the channel estimationproblem as a matrix completion problem, we interestingly find it mathematicallyequivalent to the image super-resolution problem arising in the field of imageprocessing .…

Quantum interpolating ensemble Average entropies and orthogonal polynomials

The density matrix formalism is a fundamental tool in studying various problems in quantum information processing . The most well-known and physically relevant measures are the Hilbert-Schmidtensemble and the Bures-Hall ensemble . In this work, we propose a generalizedensemble of density matrices, termed quantum interpolating ensemble, which isable to interpolate between these two seemingly unrelated ensembles .…

Multilevel approximation of Gaussian random fields Covariance compression estimation and spatial prediction

Centered Gaussian random fields (GRFs) indexed by compacta such as smooth,bounded Euclidean domains or smooth, compact and orientable manifolds are determined by their covariance operators . We prove that a tapering strategy by thresholding applied on finitesections of the bi-infinite precision and covariance matrices results inoptimally numerically sparse approximations .…

Multilinear POD DEIM model reduction for 2D and 3D nonlinear systems of differential equations

We are interested in the numerical solution of coupled nonlinear partialdifferential equations (PDEs) in two and three dimensions . We take advantage of the Kronecker structure arising in standard space discretizations of the differential operators . We discuss how to integrate the reduced order model and, in particular, how to solve the tensor-valued linear system arising at eachtimestep of a semi-implicit time discretization scheme .…

Synthesis with Asymptotic Resource Bounds

We present a method for synthesizing recursive functions that satisfy both afunctional specification and an asymptotic resource bound . Our method can synthesizeprograms with complex resource bounds, such as a sort function that hascomplexity O(nlog(n) Ourtool, SynPlexity, was able to synthesize complex divide-and-conquer programsthat cannot be synthesized by prior solvers .…

Rapidly exploring Random Forest Adaptively Exploits Local Structure with Generalised Multi Trees Motion Planning

Rapidly-exploring RandomForest (RRF*) is a generalised multi-trees motion planner . It adaptively learns to deploy Bayesian local sampling strategy in regions deemed to be bottlenecks . Local sampling exploits the local-connectivity of spaces via Markov Chain random sampling . RRF* learns region that is difficult to perform tree extensions and adaptively deploys local sampling in those regions to maximise the benefit of exploiting local structure .…

Decentralized 2 Robot Transportation with Local and Indirect Sensing

In this paper, we propose a leader-follower hierarchical strategy for tworobots collaboratively transporting an object in a partially known environment . Both robots sense the local surrounding environment and react to obstacles in their proximity . At any given time step, the leader solves a model predictivecontrol (MPC) problem with its known set of obstacles and plans a feasible path to complete the task .…

When Being Soft Makes You Tough A Collision Resilient Quadcopter Inspired by Arthropod Exoskeletons

Flying robots are usually rather delicate, and require protective enclosures when facing the risk of collision . Inspired byarthropods’ exoskeletons, we design a simple, easily manufactured, semi-rigid structure with flexible joints that can withstand high-velocity impacts . With an exoskeleton, the protective shell becomes part of the main robot structure, minimizing its loss in payload capacity .…

Robopheus A Virtual Physical Interactive Mobile Robotic Testbed

The Robopheus constructs a bridge that connects the traditional physicalhardware and virtual simulation testbeds . The virtual world’s learned models are leveraged to approximate the robot dynamics online on the physicalside . Significantly, the physical-virtual interaction design increases thetrajectory accuracy of a real robot by 300%, compared with that of not using the interaction.…

Learning When to Quit Meta Reasoning for Motion Planning

Anytime motion planners are widely used in robotics . But the relationship between their solution quality and computation time is not wellunderstood . We propose data-driven learning methods, model-based and model-free meta-reasoning, that are applicable to differentenvironment distributions . We design a convolutional neuralnetwork-based optimal solution predictor that predicts the optimal path length from a given 2D workspace image .…

Learn to Differ Sim2Real Small Defection Segmentation Network

Recent studies on deep-learning-based small defection segmentation approaches tend to be limited by fixed context . This eventually leads to thelimitation in practical robotic applications where contexts keep varying . Instead of training a network context by context and hoping it generalize, why not stop misleading it with any limited context and start training it with pure simulation?…

MetaView Few shot Active Object Recognition

In robot sensing scenarios, instead of passively utilizing human captured views, an agent should be able to actively choose informative viewpoints of a3D object as discriminative evidence to boost the recognition accuracy . Thistask is referred to as active object recognition .…

Perception Framework through Real Time Semantic Segmentation and Scene Recognition on a Wearable System for the Visually Impaired

Thissystem runs on a wearable belt with an Intel RealSense LiDAR camera and an Nvidia Jetson AGX Xavier processor . It can accompany visually impairedpeople and provide assistive scene information in their navigation tasks . The system is based on the compact ResNet backbone, our designed network architecture hastwo paths with shared parameters .…

HTMD Net A Hybrid Masking Denoising Approach to Time Domain Monaural Singing Voice Separation

The HTMD-Net combines alightweight masking component and a denoising module, based on skipconnections, in order to refine the source estimated by the masking procedure . The method achieves competitiveperformance compared to methods based purely on masking when trained under the same conditions, especially regarding the behavior during silent segments, while achieving higher computational efficiency .…

Teaching Model based Requirements Engineering to Industry Professionals An Experience Report

The use of conceptual models to foster requirements engineering has been proposed and evaluated as beneficial for several decades . We report lessons learned from a training program for teaching industry professionals model-based requirements engineering . From these findings we provide guidelines for educators designing requirements engineering courses for industry professionals, we say .…

The Automatic Quasi clique Merger algorithm AQCM

The Automatic Quasi-clique Merger algorithm is a new algorithm adapted from work published under the name QCM . The AQCM algorithm performs hierarchical clustering in any data set for which there is an associated similarity measure quantifying thesimilarity of any data i and j j .…

Learning Distributed Stabilizing Controllers for Multi Agent Systems

We address the problem of model-free distributed stabilization ofheterogeneous multi-agent systems using reinforcement learning (RL) The first algorithm solves a centralized linearquadratic regulator (LQR) problem without knowing any initial stabilizing gain in advance . The second algorithm builds upon the results of the first algorithm, and extends it to distributed stabilization .…

LQG control over unreliable channels Full Proof

In this paper LQG control over unreliable communication links is derived . Communication channels between the controller and theactuators and between the sensors and the controller are unreliable . The focus is to derive and present afull mathematical proof to derive the optimal control sequence.…

Markov Cricket Using Forward and Inverse Reinforcement Learning to Model Predict And Optimize Batting Performance in One Day International Cricket

In this paper, we model one-day international cricket games as Markovprocesses . We use Monte-Carlo learning to fit anonlinear approximation of the value function for each state of the game using a score-based reward model . We show that, when used as a proxy for remainingscoring resources, this approach outperforms the state-of-the-artDuckworth-Lewis-Stern method used in professional matches by 3 to 10 fold .…

An eigen decomposition based closed form solution for the Discrete Lyapunov and Stein Equations

A simple closed-form solution to the discrete Lyapunov equation (DLE) is established for certain families of matrices . This solution is expressed interms of the eigen decomposition (ED) for which closed-formed solutions are known . The proposed explicit solution’s complexity is of the same order asiterative solutions and significantly smaller than known closed form solutions .…

Resource Distribution Under Spatiotemporal Uncertainty of Disease Spread Stochastic versus Robust Approaches

Speeding up testing and vaccination is essential to controlling thecoronavirus disease 2019 (COVID-19) pandemic that has became a global health crisis . In this paper, we develop mathematical frameworks for optimizinglocations of distribution centers and plans for distributing resources such astest kits and vaccines under spatiotemporal uncertainties of infection and demand trends .…