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History Matters: The Impact Of Online Customer Reviews Across Product Generations, Linyi Li, Shyam Gopinath, Stephen J. Carson May 2022

History Matters: The Impact Of Online Customer Reviews Across Product Generations, Linyi Li, Shyam Gopinath, Stephen J. Carson

Research Collection Lee Kong Chian School Of Business

We examine how online customer reviews for one generation of a product affect sales of another generation in the same product series. The main intriguing result is that previous generation valence has a positive impact on current generation sales; however, current generation valence has a negative impact on previous generation sales. The positive impact of previous generation valence becomes even stronger (1) as the uncertainty (standard deviation) in reviews for the current generation increases and (2) when the current generation valence is high. In contrast, it becomes weaker (1) as the uncertainty in reviews for the previous generation increases and …


A Black-Scholes User's Guide To The Bachelier Model, Jaehyuk Choi, Minsuk Kwak, Chyng Wen Tee, Yumeng Wang May 2022

A Black-Scholes User's Guide To The Bachelier Model, Jaehyuk Choi, Minsuk Kwak, Chyng Wen Tee, Yumeng Wang

Research Collection Lee Kong Chian School Of Business

To cope with the negative oil futures price caused by the COVID-19 recession, global commodity futures exchanges switched the option model from Black-Scholes to Bachelier in April 2020. This study reviews the literature on Bachelier's pioneering option pricing model and summarizes the practical results on volatility conversion, risk management, stochastic volatility, and barrier options pricing to facilitate the model transition. In particular, using the displaced Black-Scholes model as a model family with the Black-Scholes and Bachelier models as special cases, we not only connect the two models but also present a continuous spectrum of model choices.


Coping Strategies Mediate The Relation Between Executive Functions And Life Satisfaction In Middle And Late Adulthood: A Structural Equational Analysis, Hui Si Oh, Hwajin Yang May 2022

Coping Strategies Mediate The Relation Between Executive Functions And Life Satisfaction In Middle And Late Adulthood: A Structural Equational Analysis, Hui Si Oh, Hwajin Yang

Research Collection School of Social Sciences

Recent studies have suggested that executive functions (EF) predict life satisfaction for older adults. However, the mechanism is not known. By analyzing a sample (N = 3,287, ages 32- 84 years) from the Midlife Development in the United States 2, we examined the mediational role of coping strategies in the relation between EF and life satisfaction. Both active coping and behavioral disengagement mediated the relation between EF and life satisfaction, and age significantly moderated the mediational pathways. Specifically, the positive effect of EF on active coping was more pronounced in middle-aged and older adults than in young adults. However, the …


The Effects Of Counterfactual Thinking On Everyday Meaning, Wynn Tan May 2022

The Effects Of Counterfactual Thinking On Everyday Meaning, Wynn Tan

Dissertations and Theses Collection (Open Access)

Meaning-making literature largely focuses on predictors of global meaning rather than situational meaning. This is insufficient as both levels of meaning are necessary for a sustained sense of meaning. Past studies found evidence that downward counterfactuals can enhance the meaningfulness of events. However, those findings may be due to existing studies’ focus on major events and did not study how meaning could change over time. For everyday events, upward counterfactuals were proposed to be more apt in enhancing meaning. Using a multiphase diary study, this paper examined whether upward counterfactual thinking predicted event meaningfulness, and more specifically if it was …


Sorry, Locals Only: An Experimental Investigation Of The Affective, Behavioural, And Cognitive Consequences Of National Identity Denial, Nadyanna Binte Mohamed Majeed May 2022

Sorry, Locals Only: An Experimental Investigation Of The Affective, Behavioural, And Cognitive Consequences Of National Identity Denial, Nadyanna Binte Mohamed Majeed

Dissertations and Theses Collection (Open Access)

Existing literature shows that experiences of identity denial and questioning (IDQ) present two major consequences for racial minority groups: increased negative affect and behaviours to reassert one’s identity. The current thesis addresses two limitations in this literature—concerns about generalisability to non-US contexts, and potential consequences for cognitive functioning—by examining IDQ effects on individuals from distinct racial groups in Singapore. Through a correlational survey, Study 1 provided evidence for the incidence of IDQ in Singapore across the three racial groups, although IDQ reports were generally higher among racial minority groups (i.e., Malay and Indian) than the racial majority group (i.e., Chinese). …


I'M Special But A.I. Doesn't Get It, Huei Huei Laurel Teo May 2022

I'M Special But A.I. Doesn't Get It, Huei Huei Laurel Teo

Dissertations and Theses Collection (Open Access)

A growing body of management research on artificial intelligence (AI) has consistently shown that people innately distrust decisions made by AI and find such decision processes simply less fair compared to decisions made by humans. My dissertation adopts a different perspective to propose that aside from fairness concerns, AI decision methods trigger perceptions in people that their individual uniqueness has not be adequately considered and this has negative consequences for their psychological or subjective well-being.

By combining theories of uniqueness, individuality, power, and well-being, I develop five studies to provide empirical evidence that aversion to AI-mediated decisions also operates through …


Variation And Efficiency Of High-Frequency Betas, Congshan Zhang, Jia Li, Viktor Todorov, George Tauchen May 2022

Variation And Efficiency Of High-Frequency Betas, Congshan Zhang, Jia Li, Viktor Todorov, George Tauchen

Research Collection School Of Economics

This paper studies the efficient estimation of betas from high-frequency return data on a fixed time interval. Under an assumption of equal diffusive and jump betas, we derive the semiparametric efficiency bound for estimating the common beta and develop an adaptive estimator that attains the efficiency bound. We further propose a Hausman type test for deciding whether the common beta assumption is true from the high-frequency data. In our empirical analysis we provide examples of stocks and time periods for which a common market beta assumption appears true and ones for which this is not the case. We further quantify …


Labor Market Institutions And The Incidence Of Payroll Taxation, Jinyoung Kim, Seonghoon Kim, Kanghyock Koh May 2022

Labor Market Institutions And The Incidence Of Payroll Taxation, Jinyoung Kim, Seonghoon Kim, Kanghyock Koh

Research Collection School Of Economics

Despite the unambiguous predictions of the canonical model of a competitive labor market, empirical studies of the labor market effects of payroll taxation provide conflicting evidence. We estimate the labor market impacts of payroll taxation in Singapore, the country with the most competitive and flexible labor market among the countries investigated in the literature. By exploiting the sharp reduction in payroll tax rate when workers turn 60, we find that the reduced payroll tax rate in Singapore has a large effect on wages without changes in employment. Our meta-analysis shows consistent evidence that varying degrees of labor market competitiveness across …


Exploring And Adapting Chinese Gpt To Pinyin Input Method, Minghuan Tan, Yong Dai, Duyu Tang, Zhangyin Feng, Guoping Huang, Jing Jiang, Jiwei Li, Shuming Shi May 2022

Exploring And Adapting Chinese Gpt To Pinyin Input Method, Minghuan Tan, Yong Dai, Duyu Tang, Zhangyin Feng, Guoping Huang, Jing Jiang, Jiwei Li, Shuming Shi

Research Collection School Of Computing and Information Systems

While GPT has become the de-facto method for text generation tasks, its application to pinyin input method remains unexplored. In this work, we make the first exploration to leverage Chinese GPT for pinyin input method. We find that a frozen GPT achieves state-of-the-art performance on perfect pinyin. However, the performance drops dramatically when the input includes abbreviated pinyin. A reason is that an abbreviated pinyin can be mapped to many perfect pinyin, which links to even larger number of Chinese characters. We mitigate this issue with two strategies, including enriching the context with pinyin and optimizing the training process to …


Ptm4tag: Sharpening Tag Recommendation Of Stack Overflow Posts With Pre-Trained Models, Junda He, Bowen Xu, Zhou Yang, Donggyun Han, Chengran Yang, David Lo May 2022

Ptm4tag: Sharpening Tag Recommendation Of Stack Overflow Posts With Pre-Trained Models, Junda He, Bowen Xu, Zhou Yang, Donggyun Han, Chengran Yang, David Lo

Research Collection School Of Computing and Information Systems

Stack Overflow is often viewed as one of the most influential Software Question & Answer (SQA) websites, containing millions of programming-related questions and answers. Tags play a critical role in efficiently structuring the contents in Stack Overflow and are vital to support a range of site operations, e.g., querying relevant contents. Poorly selected tags often introduce extra noise and redundancy, which raises problems like tag synonym and tag explosion. Thus, an automated tag recommendation technique that can accurately recommend high-quality tags is desired to alleviate the problems mentioned above.


Legal Frameworks For Autonomous Vehicles, Siyuan Chen May 2022

Legal Frameworks For Autonomous Vehicles, Siyuan Chen

Research Collection Yong Pung How School Of Law

SMU’s Assoc Prof Chen Siyuan shares his thoughts on the legal challenges for autonomous vehicles when it comes to road safety.


Gender, Bottom-Line Mentality, And Workplace Mistreatment: The Roles Of Gender Norm Violation And Team Gender Composition, Kenneth Tai, Kiyoung Lee, Eugene Kim, Tiffany D. Johnson, Wei Wang, Michelle K. Duffy, Seongsu Kim May 2022

Gender, Bottom-Line Mentality, And Workplace Mistreatment: The Roles Of Gender Norm Violation And Team Gender Composition, Kenneth Tai, Kiyoung Lee, Eugene Kim, Tiffany D. Johnson, Wei Wang, Michelle K. Duffy, Seongsu Kim

Research Collection Lee Kong Chian School Of Business

Although gender has been identified as an important antecedent in workplace mistreatment research, empirical research has shown mixed results. Drawing on role congruity theory, we propose an interactive effect of gender and bottom-line mentality on being the target of mistreatment. Across two field studies, our results showed that whereas women experienced more mistreatment when they had higher levels of bottom-line mentality, men experienced more mistreatment when they had lower levels of bottom-line mentality. In another field study, using round-robin survey data, we found that team gender composition influenced the degree to which the adoption of a bottom-line mentality by female …


Guide On The Treatment Of Insolvent Micro And Small Enterprises In Asia, Aurelio Gurrea-Martinez May 2022

Guide On The Treatment Of Insolvent Micro And Small Enterprises In Asia, Aurelio Gurrea-Martinez

Research Collection Yong Pung How School Of Law

Micro and small enterprises (MSEs) represent the vast majority of businesses in all jurisdictions in Asia. Despite the economic relevance of MSEs and the importance of the insolvency process, most Asian jurisdictions do not have insolvency frameworks that are suitable for MSEs. The COVID-19 pandemic has further exacerbated the woes of these businesses. This Guide is thus prepared with a view of seeking to provide a set of principles or policy recommendations for the implementation of an efficient and effective insolvency framework for MSEs in Asia. These principles or policy recommendations include five key principles suggested for adoption by jurisdictions …


Software Engineering User Study Recruitment On Prolific: An Experience Report, Brittany Reid, Markus Wagner, Marcelo D’Amorim, Christoph Treude May 2022

Software Engineering User Study Recruitment On Prolific: An Experience Report, Brittany Reid, Markus Wagner, Marcelo D’Amorim, Christoph Treude

Research Collection School Of Computing and Information Systems

Online participant recruitment platforms such as Prolific have been gaining popularity in research, as they enable researchers to easily access large pools of participants. However, participant quality can be an issue; participants may give incorrect information to gain access to more studies, adding unwanted noise to results. This paper details our experience recruiting participants from Prolific for a user study requiring programming skills in Node.js, with the aim of helping other researchers conduct similar studies. We explore a method of recruiting programmer participants using prescreening validation, attention checks and a series of programming knowledge questions. We received 680 responses, and …


Is Surprisal In Issue Trackers Actionable?, James Caddy, Markus Wagner, Christoph Treude, Earl T. Barr, Miltiadis Allamanis May 2022

Is Surprisal In Issue Trackers Actionable?, James Caddy, Markus Wagner, Christoph Treude, Earl T. Barr, Miltiadis Allamanis

Research Collection School Of Computing and Information Systems

Background. From information theory, surprisal is a measurement of how unexpected an event is. Statistical language models provide a probabilistic approximation of natural languages, and because surprisal is constructed with the probability of an event occuring, it is therefore possible to determine the surprisal associated with English sentences. The issues and pull requests of software repository issue trackers give insight into the development process and likely contain the surprising events of this process. Objective. Prior works have identified that unusual events in software repositories are of interest to developers, and use simple code metrics-based methods for detecting them. In this …


Watch Your Flavors: Augmenting People's Flavor Perceptions And Associated Emotions Based On Videos Watched While Eating, Meetha Nesam James, Nimesha Ranasinghe, Anthony Tang, Lora Oehlberg May 2022

Watch Your Flavors: Augmenting People's Flavor Perceptions And Associated Emotions Based On Videos Watched While Eating, Meetha Nesam James, Nimesha Ranasinghe, Anthony Tang, Lora Oehlberg

Research Collection School Of Computing and Information Systems

People engage in different activities while eating alone, such as watching television or scrolling through social media on their phones. However, the impacts of these visual contents on human cognitive processes, particularly related to flavor perception and its attributes, are still not thoroughly explored. This paper presents a user study to evaluate the influence of six different types of video content (including nature, cooking, and a new food video genre known as mukbang) on people’s flavor perceptions in terms of taste sensations, liking, and emotions while eating plain white rice. Our findings revealed that the participants’ flavor perceptions are augmented …


Graphcode2vec: Generic Code Embedding Via Lexical And Program Dependence Analyses, Wei Ma, Mengjie Zhao, Ezekiel Soremekun, Qiang Hu, Jie M. Zhang, Mike Papadakis, Maxime Cordy, Xiaofei Xie, Yves Le Traon May 2022

Graphcode2vec: Generic Code Embedding Via Lexical And Program Dependence Analyses, Wei Ma, Mengjie Zhao, Ezekiel Soremekun, Qiang Hu, Jie M. Zhang, Mike Papadakis, Maxime Cordy, Xiaofei Xie, Yves Le Traon

Research Collection School Of Computing and Information Systems

Code embedding is a keystone in the application of machine learning on several Software Engineering (SE) tasks. To effectively support a plethora of SE tasks, the embedding needs to capture program syntax and semantics in a way that is generic. To this end, we propose the first self-supervised pre-training approach (called Graphcode2vec) which produces task-agnostic embedding of lexical and program dependence features. Graphcode2vec achieves this via a synergistic combination of code analysis and Graph Neural Networks. Graphcode2vec is generic, it allows pre-training, and it is applicable to several SE downstream tasks. We evaluate the effectiveness of Graphcode2vec on four (4) …


Devops Education: An Interview Study Of Challenges And Recommendations, Marcelo Fernandes, Samuel Ferino, Anny K. Fernandes, Uirá Kulesza, Eduardo Aranha, Christoph Treude May 2022

Devops Education: An Interview Study Of Challenges And Recommendations, Marcelo Fernandes, Samuel Ferino, Anny K. Fernandes, Uirá Kulesza, Eduardo Aranha, Christoph Treude

Research Collection School Of Computing and Information Systems

Over the last years, the software industry has adopted several DevOps technologies related to practices such as continuous integration and continuous delivery. The high demand for DevOps practitioners requires non-trivial adjustments in traditional software engineering courses and educational methodologies. This work presents an interview study with 14 DevOps educators from different universities and countries, aiming to identify the main challenges and recommendations for DevOps teaching. Our study identified 83 challenges, 185 recommendations, and several association links and conflicts between them. Our findings can help educators plan, execute and evaluate DevOps courses. They also highlight several opportunities for researchers to propose …


Linkbreaker: Breaking The Backdoor-Trigger Link In Dnns Via Neurons Consistency Check, Zhenzhu Chen, Shang Wang, Anmin Fu, Yansong Gao, Shui Yu, Robert H. Deng May 2022

Linkbreaker: Breaking The Backdoor-Trigger Link In Dnns Via Neurons Consistency Check, Zhenzhu Chen, Shang Wang, Anmin Fu, Yansong Gao, Shui Yu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Backdoor attacks cause model misbehaving by first implanting backdoors in deep neural networks (DNNs) during training and then activating the backdoor via samples with triggers during inference. The compromised models could pose serious security risks to artificial intelligence systems, such as misidentifying 'stop' traffic sign into '80km/h'. In this paper, we investigate the connection characteristic between the backdoor and the trigger in DNNs and observe the fact that the backdoor is implanted via establishing a link between a cluster of neurons, representing the backdoor, and the triggers. Based on this observation, we design LinkBreaker, a new generic scheme for defending …


Sanitizable Access Control System For Secure Cloud Storage Against Malicious Data Publishers, Willy Susilo, Peng Jiang, Jianchang Lai, Fuchun Guo, Guomin Yang, Robert H. Deng May 2022

Sanitizable Access Control System For Secure Cloud Storage Against Malicious Data Publishers, Willy Susilo, Peng Jiang, Jianchang Lai, Fuchun Guo, Guomin Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cloud computing is considered as one of the most prominent paradigms in the information technology industry, since it can significantly reduce the costs of hardware and software resources in computing infrastructure. This convenience has enabled corporations to efficiently use the cloud storage as a mechanism to share data among their employees. At the first sight, by merely storing the shared data as plaintext in the cloud storage and protect them using an appropriate access control would be a nice solution. This is assuming that the cloud is fully trusted for not leaking any information, which is impractical as the cloud …


Do Pre-Trained Models Benefit Knowledge Graph Completion? A Reliable Evaluation And A Reasonable Approach, Xin Lv, Yankai Lin, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Peng Li, Jie Zhou May 2022

Do Pre-Trained Models Benefit Knowledge Graph Completion? A Reliable Evaluation And A Reasonable Approach, Xin Lv, Yankai Lin, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Peng Li, Jie Zhou

Research Collection School Of Computing and Information Systems

In recent years, pre-trained language models (PLMs) have been shown to capture factual knowledge from massive texts, which encourages the proposal of PLM-based knowledge graph completion (KGC) models. However, these models are still quite behind the SOTA KGC models in terms of performance. In this work, we find two main reasons for the weak performance: (1) Inaccurate evaluation setting. The evaluation setting under the closed-world assumption (CWA) may underestimate the PLM-based KGC models since they introduce more external knowledge; (2) Inappropriate utilization of PLMs. Most PLM-based KGC models simply splice the labels of entities and relations as inputs, leading to …


Storm The Capitol: Linking Offline Political Speech And Online Twitter Extra-Representational Participation On Qanon And The January 6 Insurrection, Claire Seungeun Lee, Juan Merizalde, John D. Colautti, Jisun An, Haewoon Kwak May 2022

Storm The Capitol: Linking Offline Political Speech And Online Twitter Extra-Representational Participation On Qanon And The January 6 Insurrection, Claire Seungeun Lee, Juan Merizalde, John D. Colautti, Jisun An, Haewoon Kwak

Research Collection School Of Computing and Information Systems

The transfer of power stemming from the 2020 presidential election occurred during an unprecedented period in United States history. Uncertainty from the COVID-19 pandemic, ongoing societal tensions, and a fragile economy increased societal polarization, exacerbated by the outgoing president's offline rhetoric. As a result, online groups such as QAnon engaged in extra political participation beyond the traditional platforms. This research explores the link between offline political speech and online extra-representational participation by examining Twitter within the context of the January 6 insurrection. Using a mixed-methods approach of quantitative and qualitative thematic analyses, the study combines offline speech information with Twitter …


Simple Or Complex? Together For A More Accurate Just-In-Time Defect Predictor, Xin Zhou, Donggyun Han, David Lo May 2022

Simple Or Complex? Together For A More Accurate Just-In-Time Defect Predictor, Xin Zhou, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Just-In-Time (JIT) defect prediction aims to automatically predict whether a commit is defective or not, and has been widely studied in recent years. In general, most studies can be classified into two categories: 1) simple models using traditional machine learning classifiers with hand-crafted features, and 2) complex models using deep learning techniques to automatically extract features. Hand-crafted features used by simple models are based on expert knowledge but may not fully represent the semantic meaning of the commits. On the other hand, deep learning-based features used by complex models represent the semantic meaning of commits but may not reflect useful …


On The Transferability Of Pre-Trained Language Models For Low-Resource Programming Languages, Fuxiang Chen, Fatemeh H. Fard, David Lo, Timofey Bryksin May 2022

On The Transferability Of Pre-Trained Language Models For Low-Resource Programming Languages, Fuxiang Chen, Fatemeh H. Fard, David Lo, Timofey Bryksin

Research Collection School Of Computing and Information Systems

A recent study by Ahmed and Devanbu reported that using a corpus of code written in multilingual datasets to fine-tune multilingual Pre-trained Language Models (PLMs) achieves higher performance as opposed to using a corpus of code written in just one programming language. However, no analysis was made with respect to fine-tuning monolingual PLMs. Furthermore, some programming languages are inherently different and code written in one language usually cannot be interchanged with the others, i.e., Ruby and Java code possess very different structure. To better understand how monolingual and multilingual PLMs affect different programming languages, we investigate 1) the performance of …


Shellfusion: Answer Generation For Shell Programming Tasks Via Knowledge Fusion, Neng Zhang, Chao Liu, Xin Xia, Christoph Treude, Ying Zou, David Lo, Zibin Zheng May 2022

Shellfusion: Answer Generation For Shell Programming Tasks Via Knowledge Fusion, Neng Zhang, Chao Liu, Xin Xia, Christoph Treude, Ying Zou, David Lo, Zibin Zheng

Research Collection School Of Computing and Information Systems

Shell commands are widely used for accomplishing tasks, such as network management and file manipulation, in Unix and Linux platforms. There are a large number of shell commands available. For example, 50,000+ commands are documented in the Ubuntu Manual Pages (MPs). Quite often, programmers feel frustrated when searching and orchestrating appropriate shell commands to accomplish specific tasks. To address the challenge, the shell programming community calls for easy-to-use tutorials for shell commands. However, existing tutorials (e.g., TLDR) only cover a limited number of frequently used commands for shell beginners and provide limited support for users to search for commands by …


Arsearch: Searching For Api Related Resources From Stack Overflow And Github, Kien Luong, Ferdian Thung, David Lo May 2022

Arsearch: Searching For Api Related Resources From Stack Overflow And Github, Kien Luong, Ferdian Thung, David Lo

Research Collection School Of Computing and Information Systems

Stack Overflow and GitHub are two popular platforms containing API-related resources for developers to learn how to use APIs. The platforms are good sources for information about API such as code examples, usages, sentiment, bug reports, etc. However, it is difficult to collect the correct resources regarding a particular API due to the ambiguity of an API method name. An API method name mentioned in the text would only refer to one API, but the method name could match with different APIs. To help people in finding the correct resources for a particular API, we introduce ARSearch. ARSearch finds Stack …


A Global Experiment On Motivating Social Distancing During The Covid-19 Pandemic, Nicole Legate, Thuy-Vy Nguyen, Andree Hartanto May 2022

A Global Experiment On Motivating Social Distancing During The Covid-19 Pandemic, Nicole Legate, Thuy-Vy Nguyen, Andree Hartanto

Research Collection School of Social Sciences

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. …


Downscaling Of Physical Risks For Climate Scenario Design, Enrico Biffis, Shuai Wang Apr 2022

Downscaling Of Physical Risks For Climate Scenario Design, Enrico Biffis, Shuai Wang

Sim Kee Boon Institute for Financial Economics

Southeast Asia is arguably one of the areas most vulnerable to natural disasters due to its dense population, coastal urbanization, and rainfall variability driven by the local monsoon systems. In this report, we focus on the impact of global warming in the region along four climate dimensions: temperature, precipitation, wind speed and coastal surge. The latter represents the surge of water from the ocean in excess of astronomical tides. Our objective is to downscale the outputs of global climate models to temporal and spatial resolutions of interest to market participants wishing to quantify climate risk vulnerability via climate stress testing …


Joint Capacity Allocation And Job Assignment Under Uncertainty, Peng Wang, Yun Fong Lim, Gar Goei Loke Apr 2022

Joint Capacity Allocation And Job Assignment Under Uncertainty, Peng Wang, Yun Fong Lim, Gar Goei Loke

Research Collection Lee Kong Chian School Of Business

In this paper, we consider the multi-period joint capacity allocation and job assignment problem. The goal of the planner is to simultaneously decide on allocating resources across the J different supply nodes, and assigning of jobs of I different demand origins to these J nodes, so as to maximize the reward for matching or minimize the cost of failure to match. We furthermore consider three features: (i) supply is replenishable after random time, (ii) demand is random; and (iii) demand can wait and need not be fully fulfilled immediately. Such problems emerge in many service management settings such as ride-sharing …


Shieldfl: Mitigating Model Poisoning Attacks In Privacy-Preserving Federated Learning, Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Yingjiu Li, Robert H. Deng Apr 2022

Shieldfl: Mitigating Model Poisoning Attacks In Privacy-Preserving Federated Learning, Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Privacy-Preserving Federated Learning (PPFL) is an emerging secure distributed learning paradigm that aggregates user-trained local gradients into a federated model through a cryptographic protocol. Unfortunately, PPFL is vulnerable to model poisoning attacks launched by a Byzantine adversary, who crafts malicious local gradients to harm the accuracy of the federated model. To resist model poisoning attacks, existing defense strategies focus on identifying suspicious local gradients over plaintexts. However, the Byzantine adversary submits encrypted poisonous gradients to circumvent existing defense strategies in PPFL, resulting in encrypted model poisoning. To address the issue, in this paper we design a privacy-preserving defense strategy using …