## Importance Estimation from Multiple Perspectives for Keyphrase Extraction

Keyphrase extraction is a fundamental task in Natural Language Processing . We typically measure the importance of phrase according to its syntactic accuracy, information saliency, and concept consistencysimultaneously . Most existing keyphrase extraction approaches only focus on the part of them, which leads to biased results .…

## Two stage Voice Application Recommender System for Unhandled Utterances in Intelligent Personal Assistant

Some requests may not be handled properly by the standard natural language understanding (NLU) component . In such cases, a simple reply like “Sorry, I don’t know” hurts the user’s experience . In this paper, we propose a two-stageshortlister-reranker recommender system to match third-party voice applications(skills) to unhandled utterances .…

## Dynamic Tolling for Inducing Socially Optimal Traffic Loads

How to design tolls that induce socially optimal traffic loads? We propose atwo-timescale discrete-time stochastic dynamics that adaptively adjusts thetoll prices on a parallel link network . We show that the loads and the tolls concentrate in a neighborhood of the fixed point, which correspondsto the socially optimal load and toll price .…

## Hybrid Layers Neural Network Architectures for Modeling the Self Interference in Full Duplex Systems

Full-duplex (FD) systems have been introduced to provide high data rates forbeyond fifth-generation wireless networks . This article proposes two novel hybrid-layersneural network (NN) architectures to cancel the SI with low complexity . The key idea behindusing hybrid layers is to build an NN model, which makes use of the different layers employed in its architecture .…

## Capacity Region Bounds for the K user Dispersive Nonlinear Optical WDM Channel with Peak Power Constraints

It is known that fiber nonlinearities induce crosstalk in a wavelengthdivision multiplexed (WDM) system . We characterize, for the first time, an outer bound on the capacity region of simultaneously achievablerate pairs, assuming a general K-user perturbative channel model usinggenie-aided techniques .…

## Wideband and Entropy Aware Deep Soft Bit Quantization

Deep learning has been recently applied to physical layer processing indigital communication systems . We introduce a novel deep learning solution for soft bitquantization across wideband channels . Our method is trained end-to-end withquantization- and entropy-aware augmentations to the loss function .…

## Understanding Players Interaction Patterns with Mobile Game App UI via Visualizations

Understanding how players interact with the mobile game app on smartphonedevices is important for game experts to develop and refine their app products . Visualizing therecorded logs of users’ UI operations is a promising way for quantitativelyunderstanding the interaction patterns .…

## Affine Hermitian Grassmann Codes

The Grassmannian is an important object in Algebraic Geometry . We introduce a new class of linear codes called Affine Hermitian GrassmanCodes . These codes are the linear codes resulting from an affine part of the projective embedding of the Grassmann codes .…

## RL4RS A Real World Benchmark for Reinforcement Learning based Recommender System

Reinforcement learning based recommender systems (RL-based RS) aims at learning a good policy from a batch of collected data . However, current RL-basedRS benchmarks commonly have a large reality gap, because they involve artificial RL datasets or semi-simulated RS datasets .…

## Fairness Concepts for Indivisible Items with Externalities

We study a fair allocation problem of indivisible items under additiveexternalities in which each agent also receives values from items that are assigned to other agents . We propose a new fairness concept called general fair share (GFS) We undertake a detailed study and present algorithms for finding fair allocations .…

## Empirical Policy Optimization for n Player Markov Games

In single-agent Markov decision processes, an agent can optimize its policy based on the interaction with environment . In multi-player Markov games, the interaction is non-stationary due to the behaviors of other players . The core is to evolve one’s policy according to not just its current in-game performance, but an aggregation of its performance over history .…

## Online Motion Planning with Soft Timed Temporal Logic in Dynamic and Unknown Environment

Motion planning of an autonomous system with high-level specifications has wide applications . Research of formal languages involving timedtemporal logic is still under investigation . Many existing resultsrely on a key assumption that user-specified tasks are feasible in the given environment .…

## Deep Learning Based Power Control for Uplink Cell Free Massive MIMO Systems

A framework for deep learning-based power control methods for max-min, max-product and max-sum-rate optimization in uplinkcell-free massive multiple-input multiple- input multiple-output (CF mMIMO) systems is proposed . Instead of using supervised learning, the proposed method relies onunsupervised learning, in which optimal power allocations are not required to be known, and thus has low training complexity .…

## Learning to Learn a Cold start Sequential Recommender

The cold-start recommendation is an urgent problem in contemporary online applications . Many data-driven algorithms, suchas the widely used matrix factorization, underperform because of datasparseness . This work adopts the idea of meta-learning to solve the user’scold start recommendation problem .…

## Ranking Facts for Explaining Answers to Elementary Science Questions

Explanations are created from a human-annotated set ofnearly 5,000 candidate facts in the WorldTree corpus . Our aim is to obtainbetter matches for valid facts of an explanation for the correct answer of a question over the available fact candidates .…

## Small Data and Process in Data Visualization The Radical Translations Case Study

This paper uses the collaborative project Radical Translations as case study to examine some of the theoretical perspectives informing the adoption andcritique of data visualization in the digital humanities . It showcases how data visualization is used within a King’s DigitalLab project lifecycle to facilitate collaborative data exploration within the project interdisciplinary team .…

## Location Information Assisted Beamforming Design for Reconfigurable Intelligent Surface Aided Communication Systems

In reconfigurable intelligent surface (RIS) aided millimeter-wave (mmWave)communication systems, in order to overcome the limitation of the conventional channel state information (CSI) acquisition techniques, this paper proposes alocation information assisted beamforming design without the requirement of the channel training process .…

## Semantics of Conjectures

This paper aims to expand and detail the notion of formal semantics of Conjectures by applying a theoretic-model approach . After a short introduction to the concepts and basics, we will start from the concept ofSimple Interpretation of RDF, applying and extending the semantic rules and conditions to fully cover the concepts .…

## Ride Sharing Data Privacy An Analysis of the State of Practice

Digital services like ride sharing rely heavily on personal data . Services include a varying set of personal data and offer limited privacy-related features . Privacy concerns are a decisive factor for individuals to (not) use these services . The results show that services include a different set of data and are often limited on privacy- related features .…

## Bayesian Persuasion in Sequential Trials

We consider a Bayesian persuasion or information design problem where thesender tries to persuade the receiver to take a particular action via a sequence of signals . This we model by considering multi-phase trials where the FDA determines some of the experiments .…

## Ctrl Shift How Privacy Sentiment Changed from 2019 to 2021

People’s privacy sentiments drive changes in legislation and may influencetheir willingness to use a variety of technologies . After the onset of COVID-19, we observe significant changes in Americans’ privacy sentimentstoward government- and health-related data uses . We observe additionalchanges in the context of other national events such as the U.S.…

## A Formalisation of Abstract Argumentation in Higher Order Logic

We present an approach for representing abstract argumentation frameworks based on an encoding into classical higher-order logic . This provides a uniform framework for computer-assisted assessment of abstract argumentations . This enables the formalanalysis and verification of meta-theoretical properties as well as theflexible generation of extensions and labellings with respect to well-known semantics .…

## Model Order Estimation for A Sum of Complex Exponentials

In this paper, we present a new method for estimating the number of terms in a sum of exponentially damped sinusoids embedded in noise . We propose to combine the shift-invariance property of the Hankel matrix with a constraint over its singular values topenalize small order estimations .…

## Joint Spatial Division and Coaxial Multiplexing for Downlink Multi User OAM Wireless Backhaul

Orbital angular momentum (OAM) at radio frequency (RF) provides a novel approach of multiplexing a set of orthogonal modes on the same frequency channel to achieve high spectral efficiencies (SEs) At last, the proposed methods are extended to the downlink MU-OAM-MIMO wireless backhaul system equipped with uniform concentric circular arrays (UCCAs) for which much higher spectral efficiency (SE) and energy efficiency (EE) can be achieved .…

## Newsalyze Effective Communication of Person Targeting Biases in News Articles

Media bias and its extreme form, fake news, can decisively affect public opinion, authors say . Slanted news coverage may influence societal decisions, e.g., in democratic elections . Study suggests that our content-driven identification method detects groups of similarly slanted news articles due to substantial biases present in individual news articles.…

## Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E Commerce

In e-commerce, the watchlist enables users to track items over time and hasemerged as a primary feature, playing an important role in users’ shopping journey . Watchlist items typically have multiple attributes whose values maychange over time (e.g., price, quantity) Since many users accumulate dozens of items on their watchlist, and since shopping intents change over time,recommending the top watchlist items in a given context can be valuable .…

## Learning Realtime One Counter Automata

Ouralgorithm uses membership and equivalence queries as in Angluin’s L* algorithm . In a partialequivalence query, we ask the teacher whether the language of a givenfinite-state automaton coincides with a counter-bounded subset of the targetlanguage . We evaluate an implementation of our algorithm on a number of randombenchmarks .…

## DroneStick Flying Joystick as a Novel Type of Interface

DroneStick is a novel hands-free method for smooth interaction between a human and a robotic system via one of its agents . A flying joystick(DroneStick) is composed of a flying drone and coiled wire with a vibration motor . A potential application can enhance an automated `lastmile’ delivery when a recipient needs to guide a delivery drone/robot gently to a spot where a parcel has to be dropped .…

## Don t Judge Me by My Face An Indirect Adversarial Approach to Remove Sensitive Information From Multimodal Neural Representation in Asynchronous Job Video Interviews

Adversarial methods have been proven to effectively remove sensitive information from the latent representation of neural networks without the need to collect any sensitive variable . This is the first application of adversarial techniques for obtaining a multimodal fair representation in the context of video job interviews .…

## On line Optimal Ranging Sensor Deployment for Robotic Exploration

The approach is general for any class of mobile system, we run simulations and experiments with indoor drones . We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows . We developed a genetic algorithm that minimizes the deployment of newanchors, saving energy and resources on the mobile robot and maximizing the mission .…

## Structured vector fitting framework for mechanical systems

In this paper, we develop a structure-preserving formulation of the data-driven vector fitting algorithm for the case of modally damped mechanical systems . We propose two possible structuredextensions of the barycentric formula of system transfer functions . Integrating these new forms within the classical vector fitting algorithms leads to theformulation of two new algorithms .…

## How to Effectively Identify and Communicate Person Targeting Media Bias in Daily News Consumption

Slanted news coverage has long been studied in the socialsciences, resulting in comprehensive models to describe it and effective yetcostly methods to analyze it . We present anin-progress system for news recommendation that is the first to automate themanual procedure of content analysis to reveal person-targeting biases in news articles reporting on policy issues .…

## Measuring Cognitive Status from Speech in a Smart Home Environment

By 2050, one in six people in the world will be over age 65 (up from one in 11 in 2019) Smart devices and smart home technology have potential to transform how people age, their ability to live independently in later years .…

## A Primer on the Statistical Relation between Wireless Ultra Reliability and Location Estimation

This letter statistically characterizes the impact of location estimationuncertainty in the wireless communication reliability . The reliability – characterized by how likely the outage probabilityis to be above a target threshold – can be sensitive to location errors . We highlight the difficulty of choosing a rate that both meets targetreliability and accounts for the location uncertainty, and that the most directsolutions suffer from being too conservative .…

## Uncertainty aware Topic Modeling Visualization

Topic modeling is a state-of-the-art technique for analyzing text corpora . It uses a statistical model, most commonly Latent Dirichlet Allocation (LDA) to discover abstract topics that occur in the document collection . The LDA-based topic modeling procedure is based on a randomly selected initialconfiguration .…

## The search of Type I codes

A self-dual binary linear code is called Type I code if it has singly-evencodewords, i.e.~it has codewords with weight divisible by $2.$ The purpose of this paper is to investigate interesting properties of Type I codes . Further, we build up a computer-based code-searching program .…