Federated Singular Vector Decomposition

FedSVD protects raw data through a singular valueinvariance mask, which can be further removed from the SVD results . The reconstruction error is around 0.000001% of the raw data,validating the lossless property of FedSvd . The scalability of the algorithm is nearly the same as the standalone SVD algorithm, says the authors .…

The State of AI Ethics Report Volume 4

The State of AI Ethics aims to help anyone, from machine learning experts to humanrights activists and policymakers, quickly digest and understand the latest developments in the field . Report distills the research and reporting surrounding various domains related to the ethics of AI, with aparticular focus on four key themes: Ethical AI, Fairness & Justice, Humans &Tech, and Privacy .…

Numerical differentiation on scattered data through multivariate polynomial interpolation

We discuss a pointwise numerical differentiation formula on multivariatescattered data . The formula is based on the coefficients of local polynomial interpolation atDiscrete Leja Points . Error bounds and sensitivity estimates to perturbations are provided . Several numerical tests are presented to show the accuracy of the approximation of partial derivatives of any order compatible with thefunction regularity .…

Non cumulative measures of researcher citation impact

The most commonly used publication metrics for individual researchers are the total number of publications, and Hirsch’s $h$-index . Most other author-level measures in the literature share this cumulative property . By contrast, we aim to studynon-cumulative measures that answer the question “in terms of citation impact,what have you done lately?”…

Dark Patterns Electronic Medical Records and the Opioid Epidemic

Dark patterns have emerged as a set of methods to exploit cognitive biases . These patterns can have consequences that might range fromconvenience to global disasters . We present a case of a drug company and anelectronic medical record vendor who colluded to modify the medical record’s interface to induce clinicians to increase the prescription of extended-releaseopioids .…

MedSensor Medication Adherence Monitoring Using Neural Networks on Smartwatch Accelerometer Sensor Data

Poor medication adherence presents serious economic and health problems including compromised treatment effectiveness, medical complications, and billions of dollars in wasted medicine or procedures . There is an urgent need to leverage light, smart, and minimally obtrusive technology such assmartwatches to develop user tools to improve medication use and adherence .…

Classifying concepts via visual properties

The methodology is based on Ranganathan’s original faceted approach,contextualized to the problem of classifying substance concepts . The keynovelty is that the hierarchy is built exploiting the visual properties ofsubstance concepts, while the linguistically defined properties ofclassification concepts are only used to describe substance concepts.…

Wilf classes of non symmetric operads

Two operads are said to belong to the same Wilf class if they have the samegenerating series . If an operad has afinite Groebner basis, then the monomial basis of the operad forms anunambiguous context-free language . We discuss the deterministicgrammar which defines the language .…

A Phase Transition in Large Network Games

In this paper, we use a model of large random network game to explore the conditions under which the Nash equilibrium (NE) of the game is affected by a perturbation . We use a phase transition phenomenon observed in finite rankdeformations of large .…

Improved Product Based High Dimensional Expanders

High-dimensional expanders generalize the notion of expander graphs to higher-dimensional simplicial complexes . Noelementary combinatorial construction with near-optimal expansion is known . Our construction achieves a spectral gap of $Omega ($Omega) for randomwalks on the $k$-dimensional faces, which is only quadratically worse than the optimal bound of $Theta (Theta) The construction is based on a high-dimensional variant of a tensor product .…

The Černy Conjecture for aperiodic automata

A word w is called a synchronizing (recurrent, reset) word of a deterministicfinite automaton (DFA) if w brings all states of the automaton to some state . Cernyconjectured in 1964 that every n-state synchronizing DFA possesses asynchronizing word of length at most (n -1)2.…

Block Convolution Towards Memory Efficient Inference of Large Scale CNNs on FPGA

Block convolution is a hardware-friendly, simple, yet efficient convolution operation that can avoid the off-chip transfer of intermediate feature maps atrun-time . The fundamental idea is to eliminate thedependency of feature map tiles in the spatial dimension when spatial tiling is used, which is realized by splitting a feature map into independent blocks sothat convolution can be performed separately on individual blocks .…

End to End Unsupervised Document Image Blind Denoising

Most available image denoising methods are supervised where the pairs of noisy/clean pages are required . However, this assumption is rarely met in real settings . Here, we propose a unified end-to-end unsupervised deep learning model, for the firsttime, that can effectively remove multiple types of noise, including salt \&pepper noise, blurred and/or faded text, as well as watermarks .…

Separating Sessions Smoothly

Hypersequent GV (HGV) is a modular and extensible corecalculus for functional programming with session types that enjoy deadlockfreedom, confluence, and strong normalisation . HGV exploits hyper-environments, which are collections of type environments, to ensure that structuralcongruence is type preserving . As a consequence we obtain a tight operationalcorrespondence between HGV and HCP, a hypersequent-based process-calculusinterpretation of classical linear logic .…

A fast Petrov Galerkin spectral method for the multi dimensional Boltzmann equation using mapped Chebyshev functions

Numerical approximation of the Boltzmann equation presents a challenging problem due to its high-dimensional, nonlinear, and nonlocal collision operator . The Petrov-Galerkin spectral method uses Chebyshev functions to achieve desired convergence and conservation properties . We demonstrate the superior accuracy of the proposed method in comparison to the Fourier spectral method with the help of the then-uniform fast Fourier transform (NuffT) The basis functions (bothtest and trial functions) are carefully chosen to be carefully chosen .…

Subgrid multiscale stabilized finite element analysis of non Newtonian Casson model fully coupled with Advection Diffusion Reaction equations

Casson fluid flow model tightly coupled with variable coefficients ADR ($VADR$) equation . Casson viscositycoefficient is taken to be dependent upon solute mass concentration . This paper presents the stability and convergence analyses of the stabilized finiteelement solution . The proposed expressions of the stabilization parameters help in obtaining optimal order of convergences .…

High Order Quadrature on Multi Component Domains Implicitly Defined by Multivariate Polynomials

A high-order quadrature algorithm is presented for computing integrals overcurved surfaces and volumes whose geometry is implicitly defined by levelsets of multivariate polynomials . Complexgeometry is automatically handled by the algorithm, including, e.g., multi-component domains, tunnels, and junctions arising from multiplepolynomial level sets, as well as self-intersections, cusps, and other kinds of singularities .…

Criticality and Popularity in Social Networks

I find that several models for information sharing in social networks can beinterpreted as age-dependent multi-type branching processes . This allows to characterize criticality in(real and random) social networks . For random networks, I develop amoment-closure method that handles the high-dimensionality of these models: By modifying the timing of sharing with followers, all users can be represented by a single representative, while leaving the total progeny unchanged .…

Projector Guided Non Holonomic Mobile 3D Printing

Fused deposition modeling (FDM) using mobile robots instead of thegantry-based 3D printer enables additive manufacturing at a larger scale with higher speed . This introduces challenges including accurate localization, control of the printhead, and design of a stable mobile manipulator with lowvibrations and proper degrees of freedom .…

Free Energy Node Embedding via Generalized Skip gram with Negative Sampling

A widely established set of unsupervised node embedding methods can beinterpreted as consisting of two distinctive steps: definition of asimilarity matrix based on graph of interest followed by explicit orimplicit factorization of such matrix . We propose a matrixfactorization method based on a loss function that generalizes that of theskip-gram model with negative sampling to arbitrary similarity matrices .…

Diversity in Kemeny Rank Aggregation A Parameterized Approach

A recent trend of research in artificial intelligence, called solutiondiversity, has focused on the development of notions of optimality that may be more appropriate in settings where subjectivity is essential . When combined with techniques from parameterized complexity theory, theparadigm of diversity of solutions offers a powerful algorithmic framework to address problems of practical relevance .…

Conelikes and Ranker Comparisons

The computation of pointlikes can beinterpreted as the algebraic counterpart of the covering problem . This leadsto the notion of conelikes for the corresponding algebraic framework . We apply this framework to the Trotter-Weil hierarchy and both the full and the half levels of the $\text{FO}^2$ quantifier alternation hierarchy .…

VSGM Enhance robot task understanding ability through visual semantic graph

In recent years, developing AI for robotics has raised much attention . The interaction of vision and language of robots is particularly difficult . Giving robots an understanding of visual semantics and languagesemantics will improve inference ability . In this paper, we propose a novelmethod-VSGM (Visual Semantic Graph Memory), which uses the semantic graph to obtain better visual image features, improve the robot’s visual understandingability.…

Digital competency of educators in the virtual learning environment a structural equation modeling analysis

This study integrates the educators digital competency (DC), as an individualcharacteristic construct of the task-technology fit (TTF) theory, to examine abetter fit between Moodle using and teaching task . The Task-Technology Fit was also found as an influential construct, which positively and significantly affected both Moodles utilization and teachers task performance .…

Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs

Support for lower precision computation is becoming more common inaccelerator hardware due to lower power usage, reduced data movement and increased computational performance . However, computational science and engineering (CSE) problems require double precision accuracy in several domains . We seek the best methods for incorporating multiple precisions into theGMRES linear solver; these include iterative refinement and parallelizablepreconditioners .…

Private Hierarchical Clustering in Federated Networks

Analyzing structural properties of social networks has many applications . However, these applications are not supported by federated social networks that allow users to store their social links locally on their end devices . The private hierarchical clustertrees enable a service provider to query the community structure around a user at various granularities without the users having to share their raw contact information .…

Can We Break Symmetry with o m Communication

All known algorithms need at least $Omega(m)$ communication for coloring and MIS . We study the communication cost (or message complexity) of these problems . We ask: Can we solve problems such as coloringand MIS using sublinear, i.e., $o(m), communication, and if so under whatconditions?…

Three prophylactic interventions to counter fake news on social media

Fake news on Social Media undermines democratic institutions and processes . We propose interventions that focus on individual user empowerment, and social media structural change that is prophylactic (pre exposure), rather than therapeutic (post exposure) We propose three interventions i) psychologicalinoculation, ii) fostering digital and media literacy and i) imposition of user transaction costs .…

The State of AI Ethics Report January 2021

Montreal AI Ethics Institute’s The State of AI Ethics captures the most relevant developments in AI Ethics since October 2020 . Report includes exclusive content written by world-class AI Ethics experts from universities, research institutes,consulting firms, and governments . Unique to this report is “The Abuse andMisogynoir Playbook,” written by Dr.…

CoTexT Multi task Learning with Code Text Transformer

CoTexT is a transformer-based architecture encoder-decoder model that learns the representative context between naturallanguage (NL) and programming language (PL) through multi-task learning . It achieves state-of-the-art on all downstream tasks such as code summarizing/documentation, codegeneration, defect detection, code debugging, etc. We evaluate multi-tasks on different generation and classification tasks on CodeXGLUE and it achieves state of the art on alldownstream tasks .…