## A Study of Low Resource Speech Commands Recognition based on Adversarial Reprogramming

In this study, we propose a novel adversarial reprogramming (AR) approach for low-resource spoken command recognition . The AR procedure aims to modify the acoustic signals (from the target domain) to repurpose a pretrained SCR model . We evaluate the proposed AR-SCR system on three low- resource SCR datasets, including Arabic,Lithuanian, and dysarthric Mandarin speech .…

## Text analysis and deep learning A network approach

Deep language models such as BERT have achievedunprecedented success in many applications of computational linguistics . However, much less is known about how these models can be used to analyze existing text . We propose a novel method that combines transformer models withnetwork analysis to form a self-referential representation of language use within a corpus of interest .…

## Appearance

ACM “The Handbook on Socially Interactive Agents” reviews research on and technologies involving socially interactive agents . It outlines the design space for the appearance of agents, including what appearance comprises, modalities in which agents are presented, and how agents are constructed .…

## Social Groups Based Content Caching in Wireless Networks

A promising approach to reduce the backhaul load is toproactively cache content at the network edge, taking into account the overlaid social network . Known caching schemes require complete knowledge of the socialgraph and mainly focus on one-to-one interactions forgoing the prevalent mode of content sharing among circles of ‘friends’ We propose Bingo, a proactive content caching scheme that leverages the presence of interest groups in onlinesocial networks .…

## Smart Crawling A New Approach toward Focus Crawling from Twitter

Twitter is a social network that offers a rich and interesting source of information challenging to retrieve and analyze . The available operations allow retrieving tweets on the basis of a set of keywords but with limitations such as the number of calls perminute and the size of results .…

## Emulating homoeostatic effects with metal oxide memristors T dependence

Memristor technologies have been rapidly maturing for the past decade to support emerging memory, artificial synapses, logic gates and bio-signal processing applications . Here, we report on the thermal properties of metal-oxide memristors and demonstrate how these can be used toemulate a fundamental function of biological neurons: homeostasis .…

## Contextual Sentence Classification Detecting Sustainability Initiatives in Company Reports

We introduce the novel task of detecting sustainability initiatives incompany reports . Given a full report, the aim is to automatically identifymentions of practical activities that a company has performed in order totackle specific societal issues . As a single initiative can often be described over multiples sentences, new methods for identifying continuous sentence spans needs to be developed .…

## A Mechanism Design Approach to Allocating Travel Funds

I explain how faculty members could exploit a method to allocate travel funds . I also explain how to use game theory to design a method that cannot be manipulated .…

## Discrete Approximation of Pressure Field Contact Patches

Pressure Field Contact (PFC) was recently introduced as a method for detailed modeling of contact interface regions at rates much faster thanelasticity-theory models . PFC was designed to work withcoarsely-meshed objects while preserving continuity to permit use of witherror-controlled integrators .…

## A New Data Integration Framework for Covid 19 Social Media Information

Current research on Covid-19 is typically based on a single source of information, specifically on structured historical data . Other studies are exclusively focused on unstructured onlineretrieved insights, such as data available from social media . The proposed approach is based on vine copulas, which allow us to improve predictions byexploiting the dependencies between different sources of information .…

## Nonconvex Nonconcave Min Max Optimization with a Small Maximization Domain

We study the problem of finding approximate first-order stationary points inoptimization problems . The objective function $f(x,y) issmooth, but assumed neither convex in$x$nor concave in$y$Our approachrelies upon replacing the function with its$k$th order Taylorapproximation (in$y) and finding a near-stationary point in the resultingsurrogate problem .…

## A Mining Software Repository Extended Cookbook Lessons learned from a literature review

The main purpose of Mining Software Repositories (MSR) is to discover the latest enhancements and provide an insight into how to make improvements in asoftware project . This paper updates the MSR findings of the original MSR Cookbook, by first conducting a systematic mapping study to elicitand analyze the state-of-the-art, and then proposing an extended version of the Cookbook .…

## Towards Creating a Standardized Collection of Simple and Targeted Experiments to Analyze Core Aspects of the Recommender Systems Problem

In Recommender Systems, more often than not, we design evaluations to measure an algorithm’sability to optimize goals in complex scenarios . We believe the RS community wouldgreatly benefit from creating a collection of standardized, simple, andtargeted experiments, which, much like a suite of “unit tests”, would assess algorithm’s ability to tackle core challenges that makeup complex RS tasks .…

## Multifocal Stereoscopic Projection Mapping

Stereoscopic projection mapping (PM) allows a user to see a 3D computer-generated (3D) object floating over physical surfaces ofarbitrary shapes around us . The current technology only satisfies binocular cues and is not capable of providing correct focus cues, which causes a vergence–accommodation conflict(VAC) We propose a multifocal approach to mitigate VAC instereoscopic PM .…

## Nash Convergence of Mean Based Learning Algorithms in First Price Auctions

We consider repeated first price auctions where each bidder, having adeterministic type, learns to bid using a mean-based learning algorithm . We characterize the Nash convergence property of the bidding dynamics in two senses: (1) time-average: the fraction of rounds where bidders play aNash equilibrium approaches to 1 in the limit; (2) last-iterate: the mixedstrategy profile of bidder approaches to a Nash equilibrium in limit .…

## School Virus Infection Simulator for Customizing School Schedules During COVID 19

During the Coronavirus 2019 (the covid-19) pandemic, schools continuouslystrive to provide consistent education to their students . Teachers and education policymakers are seeking ways to re-open schools, as it is necessary for community and economic development . The School-Virus-Infection-Simulator (SVIS) simulates the spread of infection at a school .…

## Computing an Optimal Pitching Strategy in a Baseball At Bat

The field of quantitative analytics has transformed the world of sports over the last decade . We often view teamsports, such as soccer, hockey, and baseball, as pairwise win-lose encounters . We propose a novel model of this encounter as a zero-sum stochastic game, in which the goal of the batter is toget on base, an outcome the pitcher aims to prevent .…

## TFix Self configuring Hybrid Timeout Bug Fixing for Cloud Systems

Timeout bugs can cause serious availability and performance issues which are difficult to fix due to the lack of diagnostic information . In this paper, we present TFix+ a self-configuring timeout bug fixingframework for automatically correcting two major kinds of timeout bugs with dynamic timeout valuepredictions .…

## A Framework for Aspectual Requirements Validation An Experimental Study

Aspect-Oriented Requirements Engineering (AORE) extends the existing software engineering approaches to cope with the issue of tangling andscattering resulted from crosscutting concerns . The proposed framework comprises a high-level and low-levelvalidation to implement on software requirements specification (SRS) Validation of requirements artefacts is an essential task in software development .…

## Accelerating Multi Objective Neural Architecture Search by Random Weight Evaluation

Neural Architecture Search (NAS) methodology is becoming increasingly important for both academia and industries . Most existing NAS methods are computationally expensive for real-world deployments . We introduce a new estimation metric, named Random-Weight Evaluation (RWE) to quantify the quality of CNNs in a cost-efficient manner .…

## Discrete Approximation of Pressure Field Contact Patches

Pressure Field Contact (PFC) was recently introduced as a method for detailed modeling of contact interface regions at rates much faster thanelasticity-theory models . PFC was designed to work withcoarsely-meshed objects while preserving continuity to permit use of witherror-controlled integrators .…

## Constraint Aware Deep Reinforcement Learning for End to End Resource Orchestration in Mobile Networks

Network slicing is a promising technology that allows mobile network operators to efficiently serve various emerging use cases in 5G . It is challenging to optimize the utilization of network infrastructures while ensuring the performance of network slices according to service levelagreements (SLAs) To solve this problem, we propose SafeSlicing that introduces a new constraint-aware deep reinforcement learning (CaDRL) algorithm to learn the optimal resource orchestration policy within two steps, i.e.,offline…

## Directionally Decomposing Structured Light for Projector Calibration

Intrinsic projector calibration is essential in projection mapping (PM) applications, especially in dynamic PM . We aim to estimate the intrinsic parameters of a projector while avoiding the limitation of shallow DOF . The device consists of a flat-bed scanner and pinhole-array masks .…

## Graph Meta Network for Multi Behavior Recommendation

Modern recommender systems often embed users and items into low-dimensionallatent representations, based on their observed interactions . Exploring multi-typed behavior patterns is of great importance torecommendation systems, yet is very challenging because of two aspects: i. The complex dependencies across different types of user-item interactions; ii)Diversity of such multi-behavior patterns may vary by users due to their personalized preference .…

## Contrastive Learning for Source Code with Structural and Functional Properties

BOOST is a novel self-supervised model to focus pre-training based on the characteristics of source code . We train our model in a way that brings the functionally equivalent code closer and distinct code further through a contrastive learning objective .…