## New Type I Binary 72 36 12 Self Dual Codes from Composite Matrices and R1 Lifts

In this work, we define three composite matrices derived from group rings . We find 30 new Type I binary self-dual codes with parameters [36, 18, 6 or 8]. Many of these codes turn out to have weight enumerators with parameters that were not known in the literature before .…

## Exponential Savings in Agnostic Active Learning through Abstention

We show that in pool-based active classification without assumptions on the underlying distribution, if the learner is given the power to abstain from somepredictions by paying the price marginally smaller than the average loss $1/2$ of a random guess, exponential savings in the number of label requests are possible whenever they are possible in the corresponding realizable problem .…

## Multi access Coded Caching from a New Class of Cross Resolvable Designs

Multi-access coded caching schemes from cross resolvable designs (CRD) have been reported recently . In this paper a new class of CRDs is presented and it is shown that the multi-accesscoded cachingschemes derived from these CRDs perform better than the Maddah-Ali-Niesenscheme in the entire memory regime .…

## Statistical Characterization of Wireless MIMO Channels in Mode Stirred Enclosures

We present the statistical characterization of a 2×2 Multiple-InputMultiple-Output wireless link operated in a mode-stirred enclosure . It is found that the severe multipath fading supported by a highlyreflecting environment creates unbalance between the two channels, even in presence of substantial losses .…

## On the Purity of Resolutions of Stanley Reisner Rings Associated to Reed Muller Codes

Following Johnsen and Verdure (2013), we can associate to any linear code $C$an abstract simplicial complex and in turn a Stanley-Reisner ring $R_C$ . The question of purity of the minimalfree resolution was considered by Ghorpade and Singh (2020) They showed that the resolution is pure insome cases and it is not pure in many other cases .…

## A Quantum Interpretation of Bunched Logic for Quantum Separation Logic

We propose a model of the substructural logic of Bunched Implications (BI) that is suitable for reasoning about quantum states . We develop a program logic where pre- and post-conditions are BI formulas describing quantumstates . We exercise logic for proving the security of quantum one-time pad and secret sharing .…

## Superconvergence of discontinuous Galerkin method for scalar and vector linear advection equations

In this paper, we use Fourier analysis to study the superconvergence of thesemi-discrete discontinuous Galerkin method for scalar linear advectionequations in one spatial dimension . The error bounds and asymptotic errors are demonstrated by various numerical experiments . We then extend the analysis to vector conservation laws, solved using theLax-Friedrichs flux .…

## Learning elliptic partial differential equations with randomized linear algebra

Given input-output pairs of an elliptic partial differential equation (PDE) in three dimensions, we derive the first theoretically-rigorous scheme for learning the associated Green’s function $G$ The quantity $0<\epsilon<1$characterizes the quality of the training dataset . Along the way, we extend therandomized singular value decomposition algorithm for learning matrices toHilbert--Schmidt operators and characterize quality of covariance kernels for PDE learning . …

## Computation of multi degree Tchebycheffian B splines

Multi-degree Tchebycheffian splines are splines with pieces drawn fromextended (complete) Tche bycheff spaces . These are a natural extension of multi-degree polynomial splines . Wepresent a practical framework to compute MDTB-splines, and provide anobject-oriented implementation in Matlab . The implementation supports the construction, differentiation, and visualization of MDTB splines whose piecesbelong to TcheByCheff spaces that are null-spaces of constant-coefficientlinear differential operators .…

## Solving the linear semiclassical Schrödinger equation on the real line

The numerical solution of a linear Schr\”odinger equation in thesemiclassical regime is very well understood in a torus $\mathbb{T}^d$ A raft of modern computational methods are precise and affordable, while conserving energy and resolving high oscillations very well . This is far from the case with regard to its solution in a setting more suitable for many applications .…

## A perimeter decreasing and area conserving algorithm for surface diffusion flow of curves

A fully discrete finite element method, based on a new weak formulation and anew time-stepping scheme, is proposed for the surface diffusion flow of closed curves in the two-dimensional plane . It is proved that the proposed method can preserve two geometric structures simultaneously at the discrete level, i.e.…

## A parallel in time two sided preconditioning for all at once system from a non local evolutionary equation with weakly singular kernel

In this paper, we study a parallel-in-time (PinT) algorithm for all-at-oncesystem from a non-local evolutionary equation with weakly singular kernel . We propose to use a two-sided preconditioning technique for theall at-once discretization of the equation . This is the first attempt to develop a PinTpreconditioning technique that has fast and exact implementation and that the .responding…

## An efficient mapped WENO scheme using approximate constant mapping

We present a novel mapping approach for WENO schemes through the use of anapproximate constant mapping function . The new mapping approach maintains almost all advantages of the WENo-PM6 scheme, including low dissipation and high resolution, while decreases the number of mathematical operations .…

## Demonstrating the Evolution of GANs through t SNE

Generative Adversarial Networks (GANs) are powerful generative models thatachieved strong results, mainly in the image domain . Evolutionary algorithms, such as COEGAN, were recently proposed as a solution to improve the GAN training . We propose an evaluation method based on t-distributed Stochastic NeighbourEmbedding (t-SNE) to assess the progress of GANs and visualize the distributionlearned by generators in training .…

## The Connection Between Approximation Depth Separation and Learnability in Neural Networks

Westudy shows that learnability with deep networks of a target function depends on the ability of simpler classes to approximate the target . We also show that a class offunctions can be learned by an efficient statistical query algorithm if and only if it can be approximated in a weak sense by some kernel class .…

## Niching Diversity Estimation for Multi modal Multi objective Optimization

Niching is an important and widely used technique in evolutionarymulti-objective optimization . Its applications mainly focus on maintaining diversity and avoiding early convergence to local optimum . In MMOPs, a solution in the objective space may have multipleinverse images in the decision space, which are termed as equivalent solutions .…

## A SDN OpenFlow Framework for Dynamic Resource Allocation based on Bandwidth Allocation Model

Bandwidth AllocationModels (BAMs) are an alternative to support this new trend . The communication network context in actual systems like 5G, cloud and IoT(Internet of Things) presents an ever-increasing number of users,applications, and services that are highly distributed . Resource allocation in this context requires dynamic, efficient, and customized solutions .…

## If you ve got it flaunt it Making the most of fine grained sentiment annotations

Fine-grained sentiment analysis attempts to extract sentiment holders,targets and polar expressions and resolve the relationship between them . We conclude that jointly predicting target and polarity BIO labels improves target extraction, and that augmenting the input text with goldexpressions generally improves targeted polarity classification .…

## Speech Recognition by Simply Fine tuning BERT

We propose a simple method for automatic speech recognition (ASR) by fine-tuning BERT . BERT is a language model (LM) trained on large-scaleunlabeled text data and can generate rich contextual representations . Our assumption is that given a history context sequence, a powerful LM can narrow the range of possible choices and the speech signal can be used as a simpleclue .…

## Fake it Till You Make it Self Supervised Semantic Shifts for Monolingual Word Embedding Tasks

The use of language is subject to variation over time as well as across social groups and knowledge domains, leading to differences even in themonolingual scenario . Such variation in word usage is often called lexicalsemantic change (LSC) The goal of LSC is to characterize and quantify languagevariations with respect to word meaning, to measure how distinct two languagesources are .…

## Machine Translationese Effects of Algorithmic Bias on Linguistic Complexity in Machine Translation

Machine Translation (MT) and Natural LanguageProcessing (NLP) have shown that existing models amplify biases observed in the training data . We hypothesize that the’algorithmic bias’, i.e. an exacerbation of frequently observed patterns incombination with a loss of less frequent ones, not only exacerbates societalbiases present in current datasets but could also lead to an artificiallyimpoverished language: ‘machine translationese’ We assess the linguisticrichness (on a lexical and morphological level) of translations created by different data-driven MT paradigms – phrase-based statistical (PB-SMT) andneural MT (NMT) Our experiments show that there is a .…

## EmpathBERT A BERT based Framework for Demographic aware Empathy Prediction

Affect preferences vary with user demographics, and tapping into demographicinformation provides important cues about the users’ language preferences . We propose EmpathBERT, ademographic-aware framework for empathy prediction based on BERT . Through comparative experiments, we show that EmpathberT surpasses traditional machine learning and deep learning models .…

## Triple M A Practical Neural Text to speech System With Multi guidance Attention And Multi band Multi time Lpcnet

Triple M is a practical neuraltext-to-speech system, named Triple M . It consists of a seq2seq model with multi-guidance attention and a multi-band multi-time LPCNet . The former usesalignment results of different attention mechanisms to guide the learning of the basic attention mechanism .…

## ShufText A Simple Black Box Approach to Evaluate the Fragility of Text Classification Models

Recently, deep learning approaches based on CNN, LSTM, andTransformers have been the de facto approach for text classification . We propose a simple black box technique ShutText to present the shortcomings of the model . Thisinvolves randomly shuffling the words in a sentence and evaluating the classification accuracy .…

## Taxonomic survey of Hindi Language NLP systems

Natural Language processing (NLP) represents the task of automatic handling of natural human language by machines . Hindi is the official language of India with nearly 691 million users in India and 366 million in rest of world . There is large spectrum of possible applications of NLP which help in automating tasks like translating text from one language to other, retrieving and summarizing data from very hugerepositories, spam email filtering, identifying fake news in digital media, find political opinions and views of people on various government policies, provide effective medical assistance based on past history records of patient etc.…

## Can We Automate Scientific Reviewing

The rapid development of science and technology has been accompanied by anexponential growth in peer-reviewed scientific publications . The review of each paper is a laborious process that must be carried out by subject matter experts . We discuss the possibility of using state-of-the-art natural language processing (NLP) models to generate first-pass peer reviews for scientific papers .…

## Efficient CNN Building Blocks for Encrypted Data

Machine learning on encrypted data can address concerns related toprivacy and legality of sharing sensitive data with untrustworthy service providers . Fully Homomorphic Encryption (FHE) is a promising technique toenable machine learning and inferencing while providing strict guarantees against information leakage .…

## SteemOps Extracting and Analyzing Key Operations in Steemit Blockchain based Social Media Platform

SteemOps is a new dataset that organizes over 900million operations from Steemit into three sub-datasets . The dataset is designed to facilitate future studies aimed at providing insights on emerging blockchain-based social media platforms . We describe the dataset schema and its usage in detail and outline various potential research directions based onSteemOps .…

## Zur Integration von Post Quantum Verfahren in bestehende Softwareprodukte

PQC algorithms are being standardized to address the emerging threat to conventional asymmetric algorithms from quantum computing . These new algorithms must then be integrated into existing protocols, applications and infrastructures . Integration problems are to be expected, due toincompatibilities with existing standards and implementations on the one hand, but also due to a lack of knowledge among software developers about how to handle the algorithms .…