An Algorithm to Effect Prompt Termination of Myopic Local Search on Kauffman s NK Landscape

In the NK model given by Kauffman, myopic local search involves flipping onerandomly-chosen bit of an N-bit decision string in every time step and accepting the new configuration if that has higher fitness . This algorithm consumes the full extent of computational resources allocated – given by the number of alternative configurations inspected – even though search is expected to terminate the moment there are no neighbors having higher fitness.…

Identifying Offensive Expressions of Opinion in Context

Annotation approach was evaluated at the expression-level and achieveshigh human inter-annotator agreement . The provided offensive lexicon is available in Portuguese and English languages . It consists of explicit and implicit offensive and swearing expressions ofopinion, which were annotated in two different classes: context dependent and context-independent offensive .…

A new symmetric linearly implicit exponential integrator preserving polynomial invariants or Lyapunov functions for conservative or dissipative systems

We present a new linearly implicit exponential integrator that preserves thepolynomial first integrals or Lyapunov functions for the conservative and dissipative stiff equations . The method is tested by bothoscillated ordinary differential equations and partial differential equations,e.g., an averaged system in wind-induced oscillation, the Fermi-Pasta-Ulams, and the polynomial pendulum oscillators .…

User Preference aware Fake News Detection

The confirmation bias theory has indicated that a user is more likely to spread a piece of fake news when it confirms his/her existing beliefs/preferences . Users’ historical, socialengagements such as posts provide rich information about users’ preferencestoward news . We propose a new framework, UPFD, which captures various signals from user preferences by jointcontent and graph modeling .…

Random Spreading for Unsourced MAC with Power Diversity

We propose an improvement of the random spreading approach with polar codes for unsourced multiple access . Each user encodes its message by a polar code, and the coded bits are then spread using a random spreading sequence . The proposed approach outperforms the existing methods, especially when the number of active users is large, especially in large numbers of users .…

Transformers to Fight the COVID 19 Infodemic

The massive spread of false information on social media has become a global risk especially in a global pandemic situation like COVID-19 . False informationdetection has thus become a surging research topic in recent months . NLP4IF-2021 shared task on fighting the COVI-19 infodemic has been organised to strengthen the research in false information detection where theparticipants are asked to predict seven different binary labels regarding false information in a tweet .…

Fair Capacitated Clustering

Traditionally, clustering algorithms focus on partitioning the data intogroups of similar instances . The similarity objective is notsufficient in applications where a fair-representation of the groups in termsof protected attributes like gender or race is required for each cluster . In many applications, to make the clusters useful for the end-user, abalanced cardinality among the clusters is required .…

Labeling Multipath via Reconfigurable Intelligent Surface

Reconfigurable intelligent surface (RIS) has shown promise in providing apparent benefits in wireless communication and positioning . Each labeled path contains spatial knowledge between the RISand the receiver, thus opening the door for sensing the surrounding world byRISs . The critical challenge is how the labeled paths can be extracted and distinguish from other paths, especially with multipath effects .…

On the Achievable Sum rate of the RIS aided MIMO Broadcast Channel

Reconfigurable intelligent surfaces (RISs) represent a new technology that can shape the radio wave propagation . We exploit the well-known duality between theGaussian multiple-input multiple- input multiple-output (MIMO) BC and multiple-access channel(MAC) We propose an alternating optimization (AO) algorithm which optimizes the users’ covariance matrices and the RIS phase shifts in the dual MAC .…

RDMAbox Optimizing RDMA for Memory Intensive Workloads

RDMAbox is a set of low level RDMA opti-mizations that provide better performance than previous ap-proaches . The optimizations are packaged in easy-to-use ker-nel and userspace libraries and presented through simplenodelevel abstractions . The I/O mergequeue at the same time functions as a traffic regulator to enforce admissioncontrol and avoidoverloading the NIC .…

Learning Passage Impacts for Inverted Indexes

DeepImpact is a new documentterm-weighting scheme suitable for efficient retrieval using a standardinverted index . Compared to existing methods, it improves impact-scoremodeling and tackles the vocabulary-mismatch problem . When deployed in a re-ranking scenario, it can reach the same effectiveness of state-of-the-art approaches with up to 5.1x speedup inefficiency .…

XLM T A Multilingual Language Model Toolkit for Twitter

Language models are ubiquitous in current NLP, and their multilingualcapacity has recently attracted considerable attention . XLM-T is a framework for using and evaluating multilingual language models in Twitter . This framework featurestwo main assets: (1) a strong multilingual baseline consisting of a model pre-trained on millions of tweets in over thirty languages .…

Contextual Lexicon Based Approach for Hate Speech and Offensive Language Detection

This paper presents a new approach for offensive language and hate speechdetection on social media . Our approach incorporates an offensive lexiconcomposed by implicit and explicit offensive and swearing expressions annotated with binary classes: context-dependent offensive and context-independentoffensive . Due to the severity of the hate speech and offensive comments inBrazil and the lack of research in Portuguese, Brazilian Portuguese is thelanguage used to validate our method .…

An Adaptive Learning based Generative Adversarial Network for One To One Voice Conversion

Voice Conversion (VC) deals with conversion of vocal style of one speaker to another speaker while keeping the linguistic contentsunchanged . VC task is performed through a three-stage pipeline consisting of speech analysis, speech feature mapping, and speech reconstruction . ALGAN-VC framework consists of some approaches to improve speech quality and voice similarity between source and target speakers .…

Predicting the Number of Reported Bugs in a Software Repository

The bug growth pattern prediction is a complicated, unrelieved task, which needs considerable attention . Advance knowledge of the likely number of bugs discovered in the software system helps software developers in designatingsufficient resources at a convenient time . We observe that LSTM is effective when considering long-runpredictions whereas Random Forest Regressor enriched by exogenous variables performs better for predicting bugs in the short term .…

Automatic Post Editing for Translating Chinese Novels to Vietnamese

Automatic post-editing (APE) is an important remedy for reducing errors ofraw translated texts that are produced by machine translation (MT) systems or software-aided translation . In this paper, we present the first attempt totackle the APE task for Vietnamese . We construct the first large-scale dataset of 5M Vietnamese translated and corrected sentence pairs .…

Learning Latent Graph Dynamics for Deformable Object Manipulation

DefOrmable Object Manipulation(G-DOOM) is a long-standing challenge in robotics . It aims to learn latent Graph dynamics for DefOratable Object Manipulations . We train the resulting graph dynamics model through contrastive learning in a high-fidelity simulator . We evaluate a set of challenging cloth and rope manipulation tasks and show that G-Doomperforms a state-of-the-art method .…

Superconvergence of Galerkin variational integrators

Galerkin variational integrators approximate avariational (Lagrangian) problem by restricting the space of curves to the set of polynomials of degree at most $s$ and approximating the action integral . We show that, if the quadrature rule is sufficiently accurate, the order of the integrators thus obtained is $2s$.…

Math Operation Embeddings for Open ended Solution Analysis and Feedback

Feedback on student answers and even during intermediate steps in solving questions is an important element in math education . Such feedback can help students correct their errors and ultimately lead toimproved learning outcomes . Most existing approaches for automated studentsolution analysis and feedback require manually constructing cognitive models and anticipating student errors for each question .…

Gaining Insights on Student Course Selection in Higher Education with Community Detection

Gaining insight into course choices holds significant value for universities, especially those who aim for flexibility in their programs and wish to adapt quickly to changing demands of the job market . We found that course choices diversify as programs progress, meaning that attempting to identify a “typical” student gives less insight than understanding what characterizes course choice diversity .…

Low rank Tensor Estimation via Riemannian Gauss Newton Statistical Optimality and Second Order Convergence

In this paper, we consider the estimation of a low Tucker rank tensor from anumber of noisy linear measurements . The general problem covers many specificexamples arising from applications, including tensor regression, tensorcompletion, and tensor PCA/SVD . We propose a Riemannian Gauss-Newton (RGN)method with fast implementations for low Tucker Rank tensor estimation .…

OPTION OPTImization Algorithm Benchmarking ONtology

Different platforms for benchmarking optimization algorithms use different data models and formats, which drastically inhibits identification of relevant data sets, their interpretation, and their interoperability . We report in this paper on the development of such an ontology, which we nameOPTION (OPTImization algorithm benchmarking ONtology) Our ontology providesthe vocabulary needed for semantic annotation of the core entities involved inthe benchmarking process, such as algorithms, problems, and evaluationmeasures .…