Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons™

Open Access. Powered by Scholars. Published by Universities.®

Singapore Management University

Discipline
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 1951 - 1980 of 7454

Full-Text Articles in Physical Sciences and Mathematics

Adversarial Meta Sampling For Multilingual Low-Resource Speech Recognition, Yubei Xiao, Ke Gong, Pan Zhou, Guolin Zheng, Xiaodan Liang, Liang Lin Feb 2021

Adversarial Meta Sampling For Multilingual Low-Resource Speech Recognition, Yubei Xiao, Ke Gong, Pan Zhou, Guolin Zheng, Xiaodan Liang, Liang Lin

Research Collection School Of Computing and Information Systems

Human doctors with well-structured medical knowledge can diagnose a disease merely via a few conversations with patients about symptoms. In contrast, existing knowledgegrounded dialogue systems often require a large number of dialogue instances to learn as they fail to capture the correlations between different diseases and neglect the diagnostic experience shared among them. To address this issue, we propose a more natural and practical paradigm, i.e., low-resource medical dialogue generation, which can transfer the diagnostic experience from source diseases to target ones with a handful of data for adaptation. It is capitalized on a commonsense knowledge graph to characterize the …

Go to article

Terrace-Based Food Counting And Segmentation, Huu-Thanh Nguyen, Chong-Wah Ngo Feb 2021

Terrace-Based Food Counting And Segmentation, Huu-Thanh Nguyen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper represents object instance as a terrace, where the height of terrace corresponds to object attention while the evolution of layers from peak to sea level represents the complexity in drawing the finer boundary of an object. A multitask neural network is presented to learn the terrace representation. The attention of terrace is leveraged for instance counting, and the layers provide prior for easy-to-hard pathway of progressive instance segmentation. We study the model for counting and segmentation for a variety of food instances, ranging from Chinese, Japanese to Western food. This paper presents how the terrace model deals with …

Go to article

Norm-Based Generalisation Bounds For Deep Multi-Class Convolutional Neural Networks, Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft Feb 2021

Norm-Based Generalisation Bounds For Deep Multi-Class Convolutional Neural Networks, Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft

Research Collection School Of Computing and Information Systems

We show generalisation error bounds for deep learning with two main improvements over the state of the art. (1) Our bounds have no explicit dependence on the number of classes except for logarithmic factors. This holds even when formulating the bounds in terms of the Frobenius-norm of the weight matrices, where previous bounds exhibit at least a squareroot dependence on the number of classes. (2) We adapt the classic Rademacher analysis of DNNs to incorporate weight sharing—a task of fundamental theoretical importance which was previously attempted only under very restrictive assumptions. In our results, each convolutional filter contributes only once …

Go to article

Divide And Capture: An Improved Cryptanalysis Of The Encryption Standard Algorithm Rsa, Willy Susilo, Joseph Tonien, Guomin Yang Feb 2021

Divide And Capture: An Improved Cryptanalysis Of The Encryption Standard Algorithm Rsa, Willy Susilo, Joseph Tonien, Guomin Yang

Research Collection School Of Computing and Information Systems

RSA is a well known standard algorithm used by modern computers to encrypt and decrypt messages. In some applications, to save the decryption time, it is desirable to have a short secret key d compared to the modulus N. The first significant attack that breaks RSA with short secret key given by Wiener in 1990 is based on the continued fraction technique and it works with d < 1/4 root 18 N-.(25). A decade later, in 2000, Boneh and Durfee presented an improved attack based on lattice technique which works with d < N-.(292). Until this day, Boneh-Durfee attack remain as the best attack on RSA with short secret key. In this paper, we revisit the continued fraction technique and propose a new attack on RSA. Our main result shows that when d < root t (2 root 2 + 8/3) N-.(75)/root e, where e is the public exponent and t is a chosen parameter, our attack can break the RSA with the running time of O(tlog (N)). Our attack is especially well suited for the case where e is much smaller than N. When e approximate to N, the Boneh-Durfee attack outperforms ours. As a result, we could simultaneously run both attacks, our new attack and the classical Boneh-Durfee attack as a backup.

Go to article

Neural Architecture Search As Sparse Supernet, Y. Wu, A. Liu, Zhiwu Huang, S. Zhang, Gool L. Van Feb 2021

Neural Architecture Search As Sparse Supernet, Y. Wu, A. Liu, Zhiwu Huang, S. Zhang, Gool L. Van

Research Collection School Of Computing and Information Systems

This paper aims at enlarging the problem of Neural Architecture Search (NAS) from Single-Path and Multi-Path Search to automated Mixed-Path Search. In particular, we model the NAS problem as a sparse supernet using a new continuous architecture representation with a mixture of sparsity constraints. The sparse supernet enables us to automatically achieve sparsely-mixed paths upon a compact set of nodes. To optimize the proposed sparse supernet, we exploit a hierarchical accelerated proximal gradient algorithm within a bi-level optimization framework. Extensive experiments on Convolutional Neural Network and Recurrent Neural Network search demonstrate that the proposed method is capable of searching for …

Go to article

Treecaps: Tree-Based Capsule Networks For Source Code Processing, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang Feb 2021

Treecaps: Tree-Based Capsule Networks For Source Code Processing, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Recently program learning techniques have been proposed to process source code based on syntactical structures (e.g., Abstract Syntax Trees) and/or semantic information (e.g., Dependency Graphs). While graphs may be better at capturing various viewpoints of code semantics than trees, constructing graph inputs from code need static code semantic analysis that may not be accurate and introduces noise during learning. On the other hand, syntax trees are precisely defined according to the language grammar and easier to construct and process than graphs. We propose a new tree-based learning technique, named TreeCaps, by fusing capsule networks with tree-based convolutional neural networks, to …

Go to article

Mimoa: A Membrane-Inspired Multi-Objective Algorithm For Green Vehicle Routing Problem With Stochastic Demands, Yunyun Niu, Yongpeng Zhang, Zhiguang Cao, Kaizhou Gao, Jianhua Xiao, Wen Song, Fangwei Zhang Feb 2021

Mimoa: A Membrane-Inspired Multi-Objective Algorithm For Green Vehicle Routing Problem With Stochastic Demands, Yunyun Niu, Yongpeng Zhang, Zhiguang Cao, Kaizhou Gao, Jianhua Xiao, Wen Song, Fangwei Zhang

Research Collection School Of Computing and Information Systems

Nowadays, an increasing number of vehicle routing problem with stochastic demands (VRPSD) models have been studied to meet realistic needs in the field of logistics. In this paper, a bi-objective vehicle routing problem with stochastic demands (BO-VRPSD) was investigated, which aims to minimize total cost and customer dissatisfaction. Different from traditional vehicle routing problem (VRP) models, both the uncertainty in customer demands and the nature of multiple objectives make the problem more challenging. To cope with BO-VRPSD, a membrane-inspired multi-objective algorithm (MIMOA) was proposed, which is characterized by a parallel distributed framework with two operation subsystems and one control subsystem, …

Go to article

Fine-Grained Generalization Analysis Of Vector-Valued Learning, Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft Feb 2021

Fine-Grained Generalization Analysis Of Vector-Valued Learning, Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft

Research Collection School Of Computing and Information Systems

Many fundamental machine learning tasks can be formulated as a problem of learning with vector-valued functions, where we learn multiple scalar-valued functions together. Although there is some generalization analysis on different specific algorithms under the empirical risk minimization principle, a unifying analysis of vector-valued learning under a regularization framework is still lacking. In this paper, we initiate the generalization analysis of regularized vector-valued learning algorithms by presenting bounds with a mild dependency on the output dimension and a fast rate on the sample size. Our discussions relax the existing assumptions on the restrictive constraint of hypothesis spaces, smoothness of loss …

Go to article

Portfolio Diversification Using Shape-Based Clustering, Tristan Lim, Chin Sin Ong Feb 2021

Portfolio Diversification Using Shape-Based Clustering, Tristan Lim, Chin Sin Ong

Research Collection School Of Computing and Information Systems

Portfolio diversification involves lowering the correlation between portfolio assets to achieve improved risk–return exposure. It is reasonable to infer from the classic Anscombe quartet that relying on descriptive statistics, and specifically, correlation, to achieve portfolio diversification may not derive the most optimal multiperiod portfolio risk-adjusted return because stocks in a portfolio can exhibit different price trends over time, even with the same computed pairwise correlation. This research applied a shape-based time-series clustering technique of agglomerative hierarchical clustering using dynamic time-series warping as a distance measure to aggregate stocks into like-trending clusters across time as a portfolio diversification tool. Results support …

Go to article

Relative And Absolute Location Embedding For Few-Shot Node Classification On Graph, Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi Feb 2021

Relative And Absolute Location Embedding For Few-Shot Node Classification On Graph, Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Node classification is an important problem on graphs. While recent advances in graph neural networks achieve promising performance, they require abundant labeled nodes for training. However, in many practical scenarios there often exist novel classes in which only one or a few labeled nodes are available as supervision, known as few-shot node classification. Although meta-learning has been widely used in vision and language domains to address few-shot learning, its adoption on graphs has been limited. In particular, graph nodes in a few-shot task are not independent and relate to each other. To deal with this, we propose a novel model …

Go to article

Project Coolbit: Can Your Watch Predict Heat Stress And Thermal Comfort Sensation?, Negin Nazarian, Sijie Liu, Manon Kohler, Jason Lee, Clayton Miller, Winston T. L. Chow, S. B. B. Alhadad, Alberto Martilli, Matias Quintana, Lindsey Sunden, Lindsey Norford Feb 2021

Project Coolbit: Can Your Watch Predict Heat Stress And Thermal Comfort Sensation?, Negin Nazarian, Sijie Liu, Manon Kohler, Jason Lee, Clayton Miller, Winston T. L. Chow, S. B. B. Alhadad, Alberto Martilli, Matias Quintana, Lindsey Sunden, Lindsey Norford

Research Collection School of Social Sciences

Global climate is changing as a result of anthropogenic warming, leading to higher daily excursions of temperature in cities. Such elevated temperatures have great implications on human thermal comfort and heat stress, which should be closely monitored. Current methods for heat exposure assessments (surveys, microclimate measurements, and laboratory experiments), however, present several limitations: measurements are scattered in time and space and data gathered on outdoor thermal stress and comfort often does not include physiological and behavioral parameters. To address these shortcomings, Project Coolbit aims to introduce a human-centric approach to thermal comfort assessments. In this study, we propose and evaluate …

Go to article

Public Transit Infrastructure And Heat Perceptions In Hot And Dry Climates, Yuliya Dzyuban, David M. Hondula, Paul J. Coseo, Charles L. Redman Jan 2021

Public Transit Infrastructure And Heat Perceptions In Hot And Dry Climates, Yuliya Dzyuban, David M. Hondula, Paul J. Coseo, Charles L. Redman

Research Collection College of Integrative Studies

Many cities aim to progress toward their sustainability and public health goals by increasing use of their public transit systems. However, without adequate protective infrastructure that provides thermally comfortable conditions for public transit riders, it can be challenging to reach these goals in hot climates. We took micrometeorological measurements and surveyed riders about their perceptions of heat and heat-coping behaviors at bus stops with a variety of design attributes in Phoenix, AZ, USA, during the summer of 2018. We identified the design attributes and coping behaviors that made riders feel cooler. We observed that current infrastructure standards and material choices …

Go to article

Fireeye: Cybersecurity In Action, Singapore Management University Jan 2021

Fireeye: Cybersecurity In Action, Singapore Management University

Perspectives@SMU

FireEye built its success on its ‘Human + AI’ philosophy. But can a cybersecurity firm get ahead of the attackers and predict an attack…on itself?

Go to article

Sociological Perspectives On Climate Change And Society: A Review, Md Saidul Islam, Edson Kieu Jan 2021

Sociological Perspectives On Climate Change And Society: A Review, Md Saidul Islam, Edson Kieu

Research Collection Lee Kong Chian School Of Business

Society is at an important intersection in dealing with the challenges of climate change, and this paper is presented at a critical juncture in light of growing recognition that the natural sciences are insufficient to deal with these challenges. Critical aspects of sociological perspectives related to climate change research are brought together in this review in the hope of fostering greater interdisciplinary collaboration between the natural and social sciences. We fervently argue for the need to inculcate interdisciplinary approaches that can provide innovative perspectives and solutions to the challenges we face from the impacts of climate change. As such, some …

Go to article

Adversarial Specification Mining, Hong Jin Kang, David Lo Jan 2021

Adversarial Specification Mining, Hong Jin Kang, David Lo

Research Collection School Of Computing and Information Systems

There have been numerous studies on mining temporal specifications from execution traces. These approaches learn finite-state automata (FSA) from execution traces when running tests. To learn accurate specifications of a software system, many tests are required. Existing approaches generalize from a limited number of traces or use simple test generation strategies. Unfortunately, these strategies may not exercise uncommon usage patterns of a software system. To address this problem, we propose a new approach, adversarial specification mining, and develop a prototype, DICE (Diversity through Counter-Examples). DICE has two components: DICE-Tester and DICE-Miner. After mining Linear Temporal Logic specifications from an input …

Go to article

Novel Techniques In Recovering, Embedding, And Enforcing Policies For Control-Flow Integrity, Yan Lin Jan 2021

Novel Techniques In Recovering, Embedding, And Enforcing Policies For Control-Flow Integrity, Yan Lin

Dissertations and Theses Collection (Open Access)

Control-Flow Integrity (CFI) is an attractive security property with which most injected and code-reuse attacks can be defeated, including advanced attacking techniques like Return-Oriented Programming (ROP). CFI extracts a control-flow graph (CFG) for a given program and instruments the program to respect the CFG. Specifically, checks are inserted before indirect branch instructions. Before these instructions are executed during runtime, the checks consult the CFG to ensure that the indirect branch is allowed to reach the intended target. Hence, any sort of controlflow hijacking would be prevented. There are three fundamental components in CFI enforcement. The first component is accurately recovering …

Go to article

Smart Scribbles For Image Matting, Yang Xin, Yu Qiao, Shaozhe Chen, Shengfeng He, Baocai Yin, Qiang Zhang, Xiaopeng Wei, Rynson W. H. Lau Jan 2021

Smart Scribbles For Image Matting, Yang Xin, Yu Qiao, Shaozhe Chen, Shengfeng He, Baocai Yin, Qiang Zhang, Xiaopeng Wei, Rynson W. H. Lau

Research Collection School Of Computing and Information Systems

Image matting is an ill-posed problem that usually requires additional user input, such as trimaps or scribbles. Drawing a fine trimap requires a large amount of user effort, while using scribbles can hardly obtain satisfactory alpha mattes for non-professional users. Some recent deep learning-based matting networks rely on large-scale composite datasets for training to improve performance, resulting in the occasional appearance of obvious artifacts when processing natural images. In this article, we explore the intrinsic relationship between user input and alpha mattes and strike a balance between user effort and the quality of alpha mattes. In particular, we propose an …

Go to article

Context-Aware Retrieval-Based Deep Commit Message Generation, Haoye Wang, Xin Xia, David Lo, Qiang He, Xinyu Wang, John Grundy Jan 2021

Context-Aware Retrieval-Based Deep Commit Message Generation, Haoye Wang, Xin Xia, David Lo, Qiang He, Xinyu Wang, John Grundy

Research Collection School Of Computing and Information Systems

Commit messages recorded in version control systems contain valuable information for software development, maintenance, and comprehension. Unfortunately, developers often commit code with empty or poor quality commit messages. To address this issue, several studies have proposed approaches to generate commit messages from commit diffs. Recent studies make use of neural machine translation algorithms to try and translate git diffs into commit messages and have achieved some promising results. However, these learning-based methods tend to generate high-frequency words but ignore low-frequency ones. In addition, they suffer from exposure bias issues, which leads to a gap between training phase and testing phase. …

Go to article

Sustainability Of Rewards-Based Crowdfunding: A Quasi-Experimental Analysis Of Funding Targets And Backer Satisfaction, Michael Wessel, Rob Gleasure, Robert John Kauffman Jan 2021

Sustainability Of Rewards-Based Crowdfunding: A Quasi-Experimental Analysis Of Funding Targets And Backer Satisfaction, Michael Wessel, Rob Gleasure, Robert John Kauffman

Research Collection School Of Computing and Information Systems

Rewards-based crowdfunding presents an information asymmetry for participants due to the funding mechanism used. Campaign-backers trust creators to complete projects and deliver rewards as outlined prior to the fundraising process, but creators may discover better opportunities as they progress with a project. Despite this, the all-or-nothing (AON) mechanism on crowdfunding platforms incentivizes creators to set meager funding-targets that are easier to achieve but may offer limited slack when creators wish to simultaneously pursue emerging opportunities later in the project. We explore the related issues of how funding targets seem to be selected by the creators, and how dissatisfaction with the …

Go to article

Peer-To-Peer Trade And The Economy Of Distributed Pv In China, Peiyun Song, Yiou Zhou, Jiahai Yuan Jan 2021

Peer-To-Peer Trade And The Economy Of Distributed Pv In China, Peiyun Song, Yiou Zhou, Jiahai Yuan

Research Collection School Of Computing and Information Systems

With the deepening of power market reform, distributed power generation is gaining momentum. This paper tests the distributed photovoltaic (DPV) economy under different business models by taking three provinces to stand for typical resource zones. The Internal return rate (IRR) is used to measure the economy, while the improved levelized cost of electricity (LCOE) is used to model the generation cost. Three business modes, namely pure producer (all generation sold to the grid), prosumer (self-use and the rest sold to the grid), and peer-to-peer trade (P2P, all generation traded via the grid) are studied. Results show that peer-to-peer trade is …

Go to article

Fakespotter: A Simple Yet Robust Baseline For Spotting Ai-Synthesized Fake Faces, Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, Yang Liu Jan 2021

Fakespotter: A Simple Yet Robust Baseline For Spotting Ai-Synthesized Fake Faces, Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, Yang Liu

Research Collection School Of Computing and Information Systems

In recent years, generative adversarial networks (GANs) and its variants have achieved unprecedented success in image synthesis. They are widely adopted in synthesizing facial images which brings potential security concerns to humans as the fakes spread and fuel the misinformation. However, robust detectors of these AI-synthesized fake faces are still in their infancy and are not ready to fully tackle this emerging challenge. In this work, we propose a novel approach, named FakeSpotter, based on monitoring neuron behaviors to spot AIsynthesized fake faces. The studies on neuron coverage and interactions have successfully shown that they can be served as testing …

Go to article

Performance-Based Iadl Evaluation Of Older Adults With Cognitive Impairment Within A Smart Home: A Feasibility Study, Iris Rawtaer, Khalid Abdul Jabbar, Xiao Liu, Thit Thit Htat Ying, Anh Thuy Giang, Philip Lin Kiat Yap, Rachel Chin Yee Cheong, Hwee-Pink Tan, Pius Lee Wei Qi, Shiou Liang Wee, Tze Pin Ng Jan 2021

Performance-Based Iadl Evaluation Of Older Adults With Cognitive Impairment Within A Smart Home: A Feasibility Study, Iris Rawtaer, Khalid Abdul Jabbar, Xiao Liu, Thit Thit Htat Ying, Anh Thuy Giang, Philip Lin Kiat Yap, Rachel Chin Yee Cheong, Hwee-Pink Tan, Pius Lee Wei Qi, Shiou Liang Wee, Tze Pin Ng

Research Collection School Of Computing and Information Systems

Introduction Mild cognitive impairment (MCI) is characterized by subtle deficits that functional assessment via informant-report measures may not detect. Sensors can potentially detect deficits in everyday functioning in MCI. This study aims to establish feasibility and acceptability of using sensors in a smart home for performance-based assessments of two instrumental activities of daily living (IADLs). Methods Thirty-five older adults (>65 years) performed two IADL tasks in a smart home laboratory equipped with sensors and a web camera. Participants' cognitive states were determined using published criteria including measures of global cognition and comprehensive neuropsychological test batteries. Selected subtasks of the …

Go to article

Public Transit Infrastructure And Heat Perceptions In Hot And Dry Climates, Yuliya Dzyuban, David M. Hondula, Paul J. Coseo, Charles L. Redman Jan 2021

Public Transit Infrastructure And Heat Perceptions In Hot And Dry Climates, Yuliya Dzyuban, David M. Hondula, Paul J. Coseo, Charles L. Redman

Research Collection College of Integrative Studies

Many cities aim to progress toward their sustainability and public health goals by increasing use of their public transit systems. However, without adequate protective infrastructure that provides thermally comfortable conditions for public transit riders, it can be challenging to reach these goals in hot climates. We took micrometeorological measurements and surveyed riders about their perceptions of heat and heat-coping behaviors at bus stops with a variety of design attributes in Phoenix, AZ, USA, during the summer of 2018. We identified the design attributes and coping behaviors that made riders feel cooler. We observed that current infrastructure standards and material choices …

Go to article

An Efficient Privacy Preserving Message Authentication Scheme For Internet-Of-Things, Jiannan Wei, Tran Viet Xuan Phuong, Guomin Yang Jan 2021

An Efficient Privacy Preserving Message Authentication Scheme For Internet-Of-Things, Jiannan Wei, Tran Viet Xuan Phuong, Guomin Yang

Research Collection School Of Computing and Information Systems

As an essential element of the next generation Internet, Internet of Things (IoT) has been undergoing an extensive development in recent years. In addition to the enhancement of peoples daily lives, IoT devices also generate/gather a massive amount of data that could be utilized by machine learning and big data analytics for different applications. Due to the machine-to-machine communication nature of IoT, data security and privacy are crucial issues that must be addressed to prevent different cyber attacks (e.g., impersonation and data pollution/poisoning attacks). Nevertheless, due to the constrained computation power and the diversity of IoT devices, it is a …

Go to article

The (Digital) Medium Of Mobility Is The Message: Examining The Influence Of E-Scooter Mobile App Perceptions On E-Scooter Use Intent, Rabindra Ratan, Kelsey Earle, Sonny Rosenthal, Vivian Hsueh Hua Chen, Andrew Gambiro, Gerard Goggin, Hallam Stevens, Benjamin Li, Kwan Min Lee Jan 2021

The (Digital) Medium Of Mobility Is The Message: Examining The Influence Of E-Scooter Mobile App Perceptions On E-Scooter Use Intent, Rabindra Ratan, Kelsey Earle, Sonny Rosenthal, Vivian Hsueh Hua Chen, Andrew Gambiro, Gerard Goggin, Hallam Stevens, Benjamin Li, Kwan Min Lee

Research Collection College of Integrative Studies

The present research examines how perceptions of e-scooter mobile apps (i.e., a communication technology) influence intent to use e-scooters (i.e., a transportation technology) while considering other perceptions specific to e-scooters (ease of use, usefulness, safety, environmental impact, and enjoyment), context of use (geographic landscape), and demographic factors (age and sex). Results suggest mobile app perceived ease of use is associated with e-scooter use intent and this effect is mediated by e-scooter perceived usefulness, even when controlling for e-scooter perceived ease of use as well as other influential elements of e-scooter use. In addition to illustrating the importance of user experiences …

Go to article

Scalable Online Vetting Of Android Apps For Measuring Declared Sdk Versions And Their Consistency With Api Calls, Daoyuan Wu, Debin Gao, David Lo Jan 2021

Scalable Online Vetting Of Android Apps For Measuring Declared Sdk Versions And Their Consistency With Api Calls, Daoyuan Wu, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Android has been the most popular smartphone system with multiple platform versions active in the market. To manage the application’s compatibility with one or more platform versions, Android allows apps to declare the supported platform SDK versions in their manifest files. In this paper, we conduct a systematic study of this modern software mechanism. Our objective is to measure the current practice of declared SDK versions (which we term as DSDK versions afterwards) in real apps, and the (in)consistency between DSDK versions and their host apps’ API calls. To successfully analyze a modern dataset of 22,687 popular apps (with an …

Go to article

Understanding The Inter-Domain Presence Of Research Topics In The Computing Discipline, Subhajit Datta, Rumana Lakdawala, Santonu Sarkar Jan 2021

Understanding The Inter-Domain Presence Of Research Topics In The Computing Discipline, Subhajit Datta, Rumana Lakdawala, Santonu Sarkar

Research Collection School Of Computing and Information Systems

The very nature of scientific inquiry encourages the flow of ideas across research domains in a discipline. Research topics with higher inter-domain presence tend to attract higher attention at individual and organizational levels. This is more pronounced in a discipline like computing, with its deeply intertwined ideas and strong connections with technology. In this paper, we study corpora of research publications across four domains of the computing discipline – covering more than 150,000 papers, involving more than 200,000 authors over 55 years and 175 publication venues – to examine the influences on inter-domain presence of research topics. We find statistically …

Go to article

Deep Unsupervised Anomaly Detection, Tangqing Li, Zheng Wang, Siying Liu, Wen-Yan Lin Jan 2021

Deep Unsupervised Anomaly Detection, Tangqing Li, Zheng Wang, Siying Liu, Wen-Yan Lin

Research Collection School Of Computing and Information Systems

This paper proposes a novel method to detect anomalies in large datasets under a fully unsupervised setting. The key idea behind our algorithm is to learn the representation underlying normal data. To this end, we leverage the latest clustering technique suitable for handling high dimensional data. This hypothesis provides a reliable starting point for normal data selection. We train an autoencoder from the normal data subset, and iterate between hypothesizing normal candidate subset based on clustering and representation learning. The reconstruction error from the learned autoencoder serves as a scoring function to assess the normality of the data. Experimental results …

Go to article

Who Am I?: Towards Social Self-Awareness For Intelligent Agents, Budhitama Subagdja, Han Yi Tay, Ah-Hwee Tan Jan 2021

Who Am I?: Towards Social Self-Awareness For Intelligent Agents, Budhitama Subagdja, Han Yi Tay, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Most of today’s AI technologies are geared towards mastering specific tasks performance through learning from a huge volume of data. However, less attention has still been given to make the AI understand its own purposes or be responsible socially. In this paper, a new model of agent is presented with the capacity to represent itself as a distinct individual with identity, a mind of its own, unique experiences, and social lives. In this way, the agent can interact with its surroundings and other agents seamlessly and meaningfully. A practical framework for developing an agent architecture with this model of self …

Go to article

The Value Of Humanization In Customer Service, Yang Gao, Huaxia Rui, Shujing Sun Jan 2021

The Value Of Humanization In Customer Service, Yang Gao, Huaxia Rui, Shujing Sun

Research Collection School Of Computing and Information Systems

As algorithm-based agents become increasingly capable of handling customer service queries, customers are often uncertain whether they are served by humans or algorithms, and managers are left to question the value of human agents once the technology matures. The current paper studies this question by quantifying the impact of customers' enhanced perception of being served by human agents on customer service interactions. Our identification strategy hinges on the abrupt implementation by Southwest Airlines of a signature policy, which requires the inclusion of an agent's first name in responses on Twitter, thereby making the agent more humanized in the eyes of …

Go to article

First Prev Next Last