## A Provably Componentwise Backward Stable O n 2 QR Algorithm for the Diagonalization of Colleague Matrices

The roots of a monic polynomial expressed in a Chebyshev basis are known to be the eigenvalues of the so-called colleague matrix . In this manuscript, we describe an $O(n^2)$ explicitstructured QR algorithm for colleague matrices . We prove that it is componentwise backward stable, in the sense that the backward error in the colleague matrix can be represented as relative perturbations to its components .…

## On Unbiased Estimation for Discretized Models

In this article, we consider computing expectations w.r.t. probabilitymeasures which are subject to discretization error . Examples include partiallyobserved diffusion processes or inverse problems, where one may have todiscretize time and/or space, in order to practically work with the probabilityof interest .…

## Convergence in the maximum norm of ADI type methods for parabolic problems

Results on unconditional convergence in the Maximum norm for ADI-typemethods are quite difficult to get, mainly when thenumber of space dimensions $m$ is greater than two . Such a result is obtained under quite general conditions on the PDE problem in case that Dirichlet boundary conditions are imposed .…

## Augmenting Part of speech Tagging with Syntactic Information for Vietnamese and Chinese

Word segmentation and part-of-speech tagging are two critical preliminary steps for downstream tasks in Vietnamese natural language processing . In reality, people tend to consider also the phrase boundary when performing wordsegmentation and . part of speech tagging rather than solely process word by word from left to right .…

## A Computation Offloading Model over Collaborative Cloud Edge Networks with Optimal Transport Theory

As novel applications spring up in future network scenarios, the requirements on network service capabilities for differentiated services or burst servicesare diverse . Migrating computing tasks to the edge and cloudfor computing requires a comprehensive consideration of energy consumption, bandwidth, and delay .…

## Investigating Moral Foundations from Web Trending Topics

Moral foundations theory helps understand differences in morality across cultures . In this paper, we propose a model to predict moral foundations (MF) from social media trending topics . We also investigate whether differences inMF influence emotional traits .…

## Multichannel LSTM CNN for Telugu Technical Domain Identification

Domain Identification plays a significant role in Machine Translation, Text Summarization, Question Answering,Information Extraction, and Sentiment Analysis . System got 69.9% of the F1score on the test dataset and 90.01% on the validation set . This architecture was used and evaluated in the context of the ICONshared task TechDOfication 2020 (task h) Thematic keywords give a compressedrepresentation of the text, and usually, Domain Identification is used in machine translation .…

## Approximation of Manifold valued Functions

We consider the approximation of manifold-valued functions by embedding them into a higher dimensional space, applying a vector-valuedapproximation operator and projecting the resulting vector back to themanifold . We provide explicitconstants that depend on the reach of the embedded manifold .…

## Classification of the streaming approximability of Boolean CSPs

A Boolean constraint satisfaction problem (CSP) is amaximization problem specified by a constraint $f:\{-1,1\}^k\to\{0,1$ The goal is to compute the maximum number of constraints that can be satisfied by a Boolean assignment to the $n$~variables . In this work we completely characterize the approximability of all BooleanCSPs in the streaming model .…

## Learning to Fairly Classify the Quality of Wireless Links

Machine learning (ML) has been used to develop increasingly accurate link quality estimators for wireless networks . We propose a newtree-based link quality classifier that meets high performance and fairlyclassifies the minority class and, at the same time, incurs low training cost .…

## False Relay Operation Attacks in Power Systems with High Renewables

Inertia of the power grids is declining, which results in a faster drop insystem frequency in case of load-generation imbalance . Power grids with renewables are moresusceptible to FRO attacks and the inertia of synchronous generators plays acritical role in reducing the success of FRo attacks in power grids .…

## Topology Learning Aided False Data Injection Attack without Prior Topology Information

False Data Injection (FDI) attacks against powersystem state estimation are agrowing concern for operators . The attack is based on a combinestopology learning technique, based only on branch and buspowerflows, and attacker-side pseudo-residual assessment to performstealthy FDIattacks with high confidence .…

## Software Engineering for Robotic Systems a systematic mapping study

This study aims to identify, classify andevaluate the current state-of-the-art Software Engineering for Robotic Systems(SERS) We systematically selected and analyzed 50 primary studies extracted from an automated search on Scopus digital library and manual search on the two editions of the RoSE workshop .…

## Auto Detection of Tibial Plateau Angle in Canine Radiographs Using a Deep Learning Approach

Stifle joint issues are a major cause of lameness in dogs and it can be asignificant marker for various forms of diseases or injuries . A known TibialPlateau Angle (TPA) helps in the reduction of the diagnosis time of the cause .…

## The rich still get richer Empirical comparison of preferential attachment via linking statistics in Bitcoin and Ethereum

Bitcoin and Ethereum transactions present one of the largest real-world complex networks that are publicly available for study . Preference attachment continues to be a key factor in the evolution of both the Bitcoin and . Ethereum, the second most important cryptocurrency, continues to evolve, authors say .…

## Scaling Distributed Ledgers and Privacy Preserving Applications

This thesis proposes techniques aiming to make blockchain technologies andsmart contract platforms practical by improving their scalability, latency, andprivacy . This thesis starts by presenting the design and implementation ofChainspace, a distributed ledger that supports user defined smart contracts and executes user-supplied transactions .…

## Symmetric distinguishability as a quantum resource

We develop a resource theory of symmetric distinguishability . We study the resource theory for two different classes of free operations . The optimal rate of converting oneelementary source to another is equal to the ratio of their quantum Chernoff divergences .…

## A Multi Objective Optimization Framework for URLLC with Decoding Complexity Constraints

Stringent constraints on both reliability and latency must be guaranteed inultra-reliable low-latency communication (URLLC) To fulfill these constraints with computationally constrained receivers, optimal transmission parameters need to be studied in detail . For this purpose, a multi-objective optimization problem (MOOP) is formulated .…

## Abelian Neural Networks

We study the problem of modeling a binary operation that satisfies somealgebraic requirements . We first construct a neural network architecture for Abelian group operations and derive a universal approximation property . Then,we extend it to Abelian semigroup operations using the characterization ofassociative symmetric polynomials .…

## Parameterized Temperature Scaling for Boosting the Expressive Power in Post Hoc Uncertainty Calibration

Standard deepneural networks typically yield uncalibrated predictions, which can be betransformed into confidence scores using post-hoc calibration methods . We address the problem of uncertainty calibration and introduce a novel method, Parametrized Temperature Scaling (PTS) We show that our novel accuracy-preserving approach consistently outperforms existing algorithms across a large number of modelarchitectures, datasets and metrics .…

## Analyzing Confidentiality and Privacy Concerns Insights from Android Issue Logs

Post-release user feedback plays an integral role in improving software quality and informing new features . Confidentiality and privacy concernsvaried in severity, and were most prevalent over Jelly Bean releases . Community users also expressed divergent preferences for new security features, ranging from more relaxed to very strict .…

## Learning optimal multigrid smoothers via neural networks

Multigrid methods are one of the most efficient techniques for solving linearsystems arising from Partial Differential Equations (PDEs) and graph Laplacians . The CNNs are trained on small-scale problems from a given type of PDEs based on a supervised lossfunction derived from multigrid convergence theories .…

## Kernel based framework to estimate deformations of pneumothorax lung using relative position of anatomical landmarks

Lungs in the pneumothorax state during surgery have a large volumechange from normal lungs, making it difficult to build a mechanical model . The proposed method used a few landmarks to capture the partialdeformation between the 3D surface mesh obtained from preoperative CT and the .intraoperative…

## MAPFAST A Deep Algorithm Selector for Multi Agent Path Finding using Shortest Path Embeddings

Solving the Multi-Agent Path Finding (MAPF) problem optimally is known to beNP-Hard for both make-span and total arrival time minimization . There is no dominatingoptimal MAPF algorithm that works well in all types of problems and no standard guidelines for when to use which algorithm .…

## LRG at SemEval 2021 Task 4 Improving Reading Comprehension with Abstract Words using Augmentation Linguistic Features and Voting

SemEval-2021 Task-4: Reading Comprehension of Abstract Meaning . Given a fill-in-the-blank-type question and a corresponding context, the task is to predict the most suitableword from a list of 5 options . We use encoders of transformers-based models pre-trained on themasked language modelling (MLM) task .…

## Theoretical Understandings of Product Embedding for E commerce Machine Learning

Product embeddings have been heavily investigated in the past few years, serving as the cornerstone for a broad range of machine learning applications in e-commerce . Little is known on how and why they work from the theoretical standpoint, but little is known about them from a theoretical standpoint .…

## From Universal Language Model to Downstream Task Improving RoBERTa Based Vietnamese Hate Speech Detection

Fine-tuning a pre-trained language model on much smaller datasets requires a carefully-designed pipeline to mitigate problems of the datasets such as lack of training data and imbalanced data . We propose a pipeline to adapt the general-purpose RoBERTa language model to aspecific text classification task: Vietnamese Hate Speech Detection .…

## Generating and Blending Game Levels via Quality Diversity in the Latent Space of a Variational Autoencoder

The MAP-Elites QD algorithm uses the learned latent space of the VAE as the search space for levels . The latent space captures the properties of the games whose levels we want to generate and blend, while MAP-elites searches this latent space to find a diverse set of levels optimizing a given objective such as playability .…

## Optimal Control Policies to Address the Pandemic Health Economy Dilemma

Non-pharmaceutical interventions (NPIs) are effective measures to contain apandemic. Yet, such control measures commonly have a negative effect on the economy . Here, we propose a macro-level approach to support resolving thisHealth-Economy Dilemma (HED) This study contributes to pandemicmodeling and simulation by providing a novel concept that elaborates onintegrating economic aspects while exploring the optimal moment to enable NPIs.…

## Mobile Recharger Path Planning and Recharge Scheduling in a Multi Robot Environment

In many multi-robot applications, mobile worker robots are often engaged in performing some tasks repetitively by following pre-computed trajectories . Asthese robots are battery-powered, they need to get recharged at regular intervals . We envision that in the future, a few mobile recharger robots will be employed to supply charge to the energy-deficient worker robots recurrently, to keep the overall efficiency of the system optimized .…

## Teach Me to Explain A Review of Datasets for Explainable NLP

Explainable NLP (ExNLP) has increasingly focused on collecting human-annotated explanations . These explanations are used downstream in threeways: as data augmentation to improve performance on a predictive task, as aloss signal to train models to produce explanations for their predictions, and as a means to evaluate the quality of model-generated explanations .…

## Temporal Energy Analysis of Symbol Sequences for Fiber Nonlinear Interference Modelling via Energy Dispersion Index

The stationary statistical properties of independent, identically distributed(i.i.d.) input symbols provide insights on the induced nonlinear interference(NLI) during fiber transmission . These statistical properties can be used inthe design of probabilistic amplitude shaping (PAS) The effective signal-to-noise ratio (SNR) in PAS has been shown to increase when the shaping blocklength decreases.…

## Railway Anomaly detection model using synthetic defect images generated by CycleGAN

Train companies are facing difficulties in gathering adequate images of defective equipment . Machine-learning models have developed a model using CycleGAN to generate artificial images instead of real images . These generated images play a vital role in enhancing the accuracy of the defect detection models, say researchers .…

## It was all for nothing sharp phase transitions for noiseless discrete channels

We establish a phase transition known as the “all-or-nothing” phenomenon fornoiseless discrete channels . This class of models includes the Bernoulli grouptesting model and the planted Gaussian perceptron model . Previously, the existence of the phenomenon was only known in alimited range of parameters .…

## PolicySpace2 modeling markets and endogenous housing policies

Policymakers decide on alternative policies facing restricted budgets anduncertain, ever-changing future . Designing housing policies is difficult giving the heterogeneous characteristics of properties themselves and the intricacy of housing markets . We propose PolicySpace2 (PS2) as an adapted and extended version of the open source PolicySpace agent-based model .…

## SocialNLP EmotionGIF 2020 Challenge Overview Predicting Reaction GIF Categories on Social Media

EmotionGIF2020 Challenge was held at the 8th International Workshop on Natural Language Processing for Social Media . The challenge required predictingaffective reactions to online texts . The novel dataset included 40Ktweets with their reaction GIFs . A total of 84 teams registered for the task .…