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 .…

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 .…

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 .…

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 $2s$.…

Efficient Binary Decision Diagram Manipulation in External Memory

We follow up on the idea of Lars Arge to rephrase the Reduce and Applyalgorithms of Binary Decision Diagrams as iterative I/O-efficient algorithms . These algorithms are implemented in a new BDD library, named Adiar . For instances of about 50 GiB, our algorithms, using external memory, are only upto 3.9 times slower compared to Sylvan, exclusively using internal memory .…

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 .…

Normal Driven Spherical Shape Analogies

This paper introduces a new method to stylize 3D geometry . The key observation is that the surface normal is an effective instrument to capturedifferent geometric styles . This formulation can deform a 3D shape intodifferent styles within a single framework .…

A Comprehensive Attempt to Research Statement Generation

Research statement generation (RSG) task aims to summarize one’s researchachievements and help prepare a formal research statement . For this task, we construct an RSG dataset with 62 research statements and the corresponding 1,203 publications . We propose a practical RSG method which identifies arearcher’s research directions by topic modeling and clustering techniques .…

Causal Learning for Socially Responsible AI

There have been increasing concerns about Artificial Intelligence due to its unfathomable potential power . Researchers proposed to develop socially responsible AI (SRAI) One of these approaches is causal learning (CL) We survey state-of-the-art methods of CL for SRAI . We begin by examining the seven CL tools to enhance the social responsibility of AI .…

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 .…

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 .…

Prior free Strategic Multiagent Scheduling with focus on Social Distancing

The algorithm takes input from citizens and schedules the store’s time-slots based on their importance to visit the facility . We show that it reduces the socialcongestion significantly using users’ visit data from a store . The problem becomes NP-complete as soon as the multi-slot demands are indivisibleand provide a polynomial-time mechanism that is truthful, individuallyrational, and approximately optimal .…

Demystification of Few shot and One shot Learning

Few-shot and one-shot learning have been the subject of active and intensive research in recent years . Theory is based on intrinsic properties of high-dimensional spaces . We show that if the ambient or latent decision space of a learning machine is sufficiently high .dimensional…

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 .…

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 .…

Speeding up Computational Morphogenesis with Online Neural Synthetic Gradients

A wide range of modern science and engineering applications are formulated as optimization problems with partial differential equations (PDEs) These PDE-constrained optimization problems are typically solved using a standard discretize-then-optimize approach . In many industry applicationsthat require high-resolution solutions, the discretized constraints can easilyhave millions or even billions of variables, making it very slow for the standard iterative optimizer to solve the exact gradients .…

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 .…

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 .…

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 .…

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 .…

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 .…

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 .…

Towards Low burden Responses to Open Questions in VR

Subjective self-reports in VR user studies is a burdening and often tedioustask for the participants . To minimize the disruption with the ongoingexperience VR research has started to administer the surveying directly insidethe virtual environments . However, due to the tedious nature of text-entry inVR, most VR surveying tools focus on closed questions with predetermined answers, while open questions with free-text responses remain unexplored .…