## 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 .…

## Predicting Flight Delay with Spatio Temporal Trajectory Convolutional Network and Airport Situational Awareness Map

To model and forecast flight delays accurately, it is crucial to harness various vehicle trajectory and contextual sensor data on airport tarmac areas . These heterogeneous sensor data, if modelled correctly, can be used to generate a situational awareness map .…

## Numerical computation of periodic solutions of renewal equations from population dynamics

We describe a piecewise collocation method for computing periodic solutions of renewal equations . Then, we rigorously prove its convergence under the framework proposed in [S. Maset, Numer. Math.,133 (2016), pp. 525–555] We show some numerical experiments on models frompopulations dynamics which confirm the order of convergence obtained theoretically .…

## 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 .…

## Tool and Domain Agnostic Parameterization of Style Transfer Effects Leveraging Pretrained Perceptual Metrics

Current deep learning techniques for style transfer would not be optimal for design support since their “one-shot” transfer does not fit exploratory design processes . To overcome this gap, we propose parametric transcription, which transcribes an end-to-end style transfer effect into parameters available in existing content editing tools .…

## 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 .…

## Reduced Sum Implementation of the BURA Method for Spectral Fractional Diffusion Problems

The numerical solution of spectral fractional diffusion problems in the form${\mathcal A}^\alpha u = f$ is studied . The BURA method has almost optimal computational complexity, assuming that anoptimal PCG iterative solution method is applied to the involved auxiliarylinear systems .…

## 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 .…

## Upscaling between an Agent Based Model Smoothed Particle Approach and a Continuum Based Model for Skin Contractions

Skin contraction is an important biophysical process that takes place duringand after the recovery of deep tissue injury . This process is mainly caused by fibroblasts (skin cells) thatexert pulling forces on the surrounding extracellular matrix (ECM) Modelling is done in multiple scales: agent-based modelling on the microscale and continuum-based .…

## 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 .…

## FRaGenLP A Generator of Random Linear Programming Problems for Cluster Computing Systems

The FRaGenLP algorithm forgenerating random linear programming problems of large dimension $n$ on clustercomputing systems . The algorithm uses two likeness metrics toprevent the addition of a new random inequality that is similar to one already present in the constraint system .…

## Endless Loops Detecting and Animating Periodic Patterns in Still Images

We present an algorithm for producing a seamless animated loop from a single image . The algorithm detects periodic structures, such as the windows of abuilding or the steps of a staircase, and generates a non-trivial displacement vector field that maps each segment of the structure onto a neighboring segment .…

## Do We Really Need to Learn Representations from In domain Data for Outlier Detection

Unsupervised outlier detection, which predicts if a test sample is an outlier, is an importantbut challenging task . Recently, methods based on the two-stage frameworkachieve state-of-the-art performance on this task . The framework leverages self-supervised representation learning algorithms to train a feature extractoron inlier data .…

## 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 .…

## Unsupervised learning of text line segmentationby differentiating coarse patterns

Unsupervised deep learning solutions for textline segmentation are beginning to gain popularity . The benefit of our approach is zero manual labelling effort . We use an unsupervised learning method that embeds document image patches to a compact Euclidean space where distancescorrespond to a coarse text line pattern similarity .…

## Birds of a Feather Capturing Avian Shape Models from Images

Animals are diverse in shape, but building a deformable shape model for a newspecies is not always possible due to the lack of 3D data . We present a method to capture new species using an articulated template and images of that species .…

## Unsupervised Discriminative Learning of Sounds for Audio Event Classification

Recent progress in network-based audio event classification has shown the benefit of pre-training models on visual data such as ImageNet . While this process allows knowledge transfer across different domains, training a model on large-scale visual datasets is time consuming .…

## Robust partial Fourier reconstruction for diffusion weighted imaging using a recurrent convolutional neural network

A neural networkarchitecture is derived which alternates between data consistency operationsand regularization implemented by recurrent convolutions . The proposed method is trained on DW liver data of 60 volunteers and evaluated on retrospectively andprospectively sub-sampled data of different anatomies and resolutions .…

## 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 .…