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Articles 1801 - 1830 of 8681
Full-Text Articles in Entire DC Network
Tourgether360: Collaborative Exploration Of 360° Videos Using Pseudo-Spatial Navigation, Kartikaeya Kumar, Lev Poretski, Jianan Li, Anthony Tang
Tourgether360: Collaborative Exploration Of 360° Videos Using Pseudo-Spatial Navigation, Kartikaeya Kumar, Lev Poretski, Jianan Li, Anthony Tang
Research Collection School Of Computing and Information Systems
Collaborative exploration of 360 videos with contemporary interfaces is challenging because collaborators do not have awareness of one another's viewing activities. Tourgether360 enhances social exploration of 360° tour videos using a pseudo-spatial navigation technique that provides both an overhead "context" view of the environment as a minimap, as well as a shared pseudo-3D environment for exploring the video. Collaborators are embodied as avatars along a track depending on their position in the video timeline and can point and synchronize their playback. We evaluated the Tourgether360 concept through two studies: first, a comparative study with a simplified version of Tourgether360 with …
Politically Speaking: Ethnic Language And Audience Opinion In Southeast Asia, Jacob I. Ricks
Politically Speaking: Ethnic Language And Audience Opinion In Southeast Asia, Jacob I. Ricks
Research Collection School of Social Sciences
Language is one of the quintessential markers of ethnicity. It allows co-ethnics to easily identify one another and underscores in-group and out-group boundaries. Recognizing this, politicians frequently employ ethnic tongues to enhance their political appeal. To what extent does this shape the opinions of their audiences? Utilizing a survey experiment, I test the impact of an ethnic tongue against that of the common political language among the Javanese in Indonesia, the Tagalog in the Philippines, and the Isan people in Thailand. The experiment demonstrates that the ethnic language has a significant impact in both Thailand and Indonesia, but there appears …
Epic-Kitchens Visor Benchmark: Video Segmentations And Object Relations, Ahmad Ak Dar Khalil, Dandan Shan, Bin Zhu, Jian Ma, Amlan Kar, Richard Higgins, David Fouhey, Sanja Fidler, Dima Damen
Epic-Kitchens Visor Benchmark: Video Segmentations And Object Relations, Ahmad Ak Dar Khalil, Dandan Shan, Bin Zhu, Jian Ma, Amlan Kar, Richard Higgins, David Fouhey, Sanja Fidler, Dima Damen
Research Collection School Of Computing and Information Systems
We introduce VISOR, a new dataset of pixel annotations and a benchmark suite for segmenting hands and active objects in egocentric video. VISOR annotates videos from EPIC-KITCHENS, which comes with a new set of challenges not encountered in current video segmentation datasets. Specifically, we need to ensure both short- and long-term consistency of pixel-level annotations as objects undergo transformative interactions, e.g. an onion is peeled, diced and cooked - where we aim to obtain accurate pixel-level annotations of the peel, onion pieces, chopping board, knife, pan, as well as the acting hands. VISOR introduces an annotation pipeline, AI-powered in parts, …
Vfirm: Verifiable Fine-Grained Encrypted Image Retrieval In Multi-Owner Multi-User Settings, Qiuyun Tong, Yinbin Miao, Lei Chen, Jian Weng, Kim-Kwang Raymond Choo, Ximeng Liu, Robert H. Deng
Vfirm: Verifiable Fine-Grained Encrypted Image Retrieval In Multi-Owner Multi-User Settings, Qiuyun Tong, Yinbin Miao, Lei Chen, Jian Weng, Kim-Kwang Raymond Choo, Ximeng Liu, Robert H. Deng
Research Collection School Of Computing and Information Systems
To ensure the security of images outsourced to the malicious cloud without affecting searchability on such outsourced (typically encrypted) images, one could use privacy-preserving Content-Based Image Retrieval (CBIR) primitive. However, conventional privacy-preserving CBIR schemes based on Searchable Symmetric Encryption (SSE) are not capable of supporting efficient fine-grained access control and result verification simultaneously. Therefore, in this article, we propose a Verifiable Fine-grained encrypted Image Retrieval scheme in the Multi-owner multi-user settings (VFIRM). VFIRM first utilizes a novel polynomial-based access strategy to provide efficient fine-grained access control. Then, it employs the dual secure kk-nearest neighbor technique to distribute distinct keys to …
Reliable Policy Updating Under Efficient Policy Hidden Fine-Grained Access Control Framework For Cloud Data Sharing, Zuobin Ying, Wenjie Jiang, Ximeng Liu, Shengmin Xu, Robert H. Deng
Reliable Policy Updating Under Efficient Policy Hidden Fine-Grained Access Control Framework For Cloud Data Sharing, Zuobin Ying, Wenjie Jiang, Ximeng Liu, Shengmin Xu, Robert H. Deng
Research Collection School Of Computing and Information Systems
Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is one of the potent encryption paradigms in protecting data confidentiality in the cloud data sharing scenario. However, the access policy of the traditional CP-ABE is in plaintext form that reveals significant sensitive information of data owners and data visitors. To mitigate this problem, two approaches have been proposed in the literature. One is partially hidden, where the attributes in the access policy are divided into two parts: the plaintext attribute names and the hidden attribute values. The other approach fully hides the attributes in the access policy which, unfortunately, hinders efficient and correct decryption as …
Microcontextual Considerations In Ouster Clause Analysis: A Comparative Study Of Parallel Trends In The United Kingdom And Singapore, Kenny Chng
Research Collection Yong Pung How School Of Law
The classic legal approach to legislative ouster clauses in the common law was articulated by the House of Lords in Anisminic Ltd. v. Foreign Compensation Commission. However, recent developments in both the United Kingdom and Singapore indicate a judicial desire to shift away from that approach towards a more flexible analysis of an ouster clause’s effect, centered on the rule of law. This article highlights the significance of those parallel developments, especially given the starkly differing constitutional contexts shaping the approach to ouster clauses in the two jurisdictions. Capitalizing on these trends, it proposes a comparative assessment of the materiality …
Is There A Strategic Organization In The Behavioral Theory Of The Firm? Looking Back And Looking Forward, Henrich R. Greve, Cyndi Man Zhang
Is There A Strategic Organization In The Behavioral Theory Of The Firm? Looking Back And Looking Forward, Henrich R. Greve, Cyndi Man Zhang
Research Collection Lee Kong Chian School Of Business
In the 20 years of Strategic Organization, how well has knowledge drawn from the behavioral theory of the firm contributed to the field of strategy? We see progress both in the pages of SO! and elsewhere in the field of strategy, but this progress has been held back by divisions between strategy and organization theory in what theories should predict, what mechanisms are preferable predictors, and what outcomes are of interest. Despite these divisions, the last few years have seen particularly rapid progress, turning the behavioral theory of the firm into one of multiple organization theory sources of strategy knowledge. …
Api-Related Developer Information Needs In Stack Overflow, Mingwei Liu, Xin Peng, Andrian Marcus, Shuangshuang Xing, Christoph Treude, Chengyuan Zhao
Api-Related Developer Information Needs In Stack Overflow, Mingwei Liu, Xin Peng, Andrian Marcus, Shuangshuang Xing, Christoph Treude, Chengyuan Zhao
Research Collection School Of Computing and Information Systems
Stack Overflow (SO) provides informal documentation for APIs in response to questions that express API related developer needs. Navigating the information available on SO and getting information related to a particular API and need is challenging due to the vast amount of questions and answers and the tag-driven structure of SO. In this paper we focus on identifying and classifying fine-grained developer needs expressed in sentences of API-related SO questions, as well as the specific information types used to express such needs, and the different roles APIs play in these questions and their answers. We derive a taxonomy, complementing existing …
Towards Automated Safety Vetting Of Smart Contracts In Decentralized Applications, Yue Duan, Xin Zhao, Yu Pan, Shucheng Li, Minghao Li, Fengyuan Xu, Mu Zhang
Towards Automated Safety Vetting Of Smart Contracts In Decentralized Applications, Yue Duan, Xin Zhao, Yu Pan, Shucheng Li, Minghao Li, Fengyuan Xu, Mu Zhang
Research Collection School Of Computing and Information Systems
We propose VetSC, a novel UI-driven, program analysis guided model checking technique that can automatically extract contract semantics in DApps so as to enable targeted safety vetting. To facilitate model checking, we extract business model graphs from contract code that capture its intrinsic business and safety logic. To automatically determine what safety specifications to check, we retrieve textual semantics from DApp user interfaces. To exclude untrusted UI text, we also validate the UI-logic consistency and detect any discrepancies. We have implemented VetSC and applied it to 34 real-world DApps. Experiments have demonstrated that VetSC can accurately interpret smart contract code, …
Towards Automated Safety Vetting Of Smart Contracts In Decentralized Applications, Yue Duan, Xin Zhao, Yu Pan, Shucheng Li, Minghao Li, Fengyuan Xu, Mu Zhang
Towards Automated Safety Vetting Of Smart Contracts In Decentralized Applications, Yue Duan, Xin Zhao, Yu Pan, Shucheng Li, Minghao Li, Fengyuan Xu, Mu Zhang
Research Collection School Of Computing and Information Systems
We propose VetSC, a novel UI-driven, program analysis guided model checking technique that can automatically extract contract semantics in DApps so as to enable targeted safety vetting. To facilitate model checking, we extract business model graphs from contract code that capture its intrinsic business and safety logic. To automatically determine what safety specifications to check, we retrieve textual semantics from DApp user interfaces. To exclude untrusted UI text, we also validate the UI-logic consistency and detect any discrepancies. We have implemented VetSC and applied it to 34 real-world DApps. Experiments have demonstrated that VetSC can accurately interpret smart contract code, …
The Privacy Of Hak-Shing William Tam: Imagining Asian Families In California’S Proposition 8, Justin Kh Tse
The Privacy Of Hak-Shing William Tam: Imagining Asian Families In California’S Proposition 8, Justin Kh Tse
Research Collection School of Social Sciences
In terms of Asian Americans whose reputations have been popularly derided, the concerned parent activist Hak-Shing William Tam perhaps ranks among the top. Tam was a citizen proponent of California’s Proposition 8 in 2008 to amend the state constitution to ban same-sex marriage and became a hostile witness for the plaintiffs in the subsequent 2010 lawsuit to overturn the amendment, Perry v. Schwarzenegger. In this paper, I explore Tam’s claim to privacy in his understanding of these events, both in terms of his sexualized imagination of liberal civil society and his suffering from what he understood as violations of his …
Deliberate Errors Promote Meaningful Learning, Sarah Shi Hui Wong, Stephen Wee Hun Lim
Deliberate Errors Promote Meaningful Learning, Sarah Shi Hui Wong, Stephen Wee Hun Lim
Research Collection School of Social Sciences
Our civilization recognizes that errors can be valuable learning opportunities, but for decades, they have widely been avoided or, at best, allowed to occur as serendipitous accidents. The present research tested whether greater learning success could paradoxically be achieved through making errors by intentional design, relative to traditional errorless learning methods. We show that deliberately committing and correcting errors even when one knows the correct answers enhances learning—a counterintuitive phenomenon that we termed the derring effect. Across two experiments (N = 160), learners engaged in open-book study of scientific expository texts and were then tested on their retention and higher-order …
Personal Comfort Models Based On A 6‐Month Experiment Using Environmental Parameters And Data From Wearables, Federico Tartarini, Stefano Schiavon, Matias Quintana, Clayton Miller
Personal Comfort Models Based On A 6‐Month Experiment Using Environmental Parameters And Data From Wearables, Federico Tartarini, Stefano Schiavon, Matias Quintana, Clayton Miller
Research Collection College of Integrative Studies
Personal thermal comfort models are a paradigm shift in predicting how building occupants perceive their thermal environment. Previous work has critical limitations related to the length of the data collected and the diversity of spaces. This paper outlines a longitudinal field study comprising 20 participants who answered Right-Here-Right-Now surveys using a smartwatch for 180 days. We collected more than 1080 field-based surveys per participant. Surveys were matched with environmental and physiological measured variables collected indoors in their homes and offices. We then trained and tested seven machine learning models per participant to predict their thermal preferences. Participants indicated 58% of …
Recipegen++: An Automated Trigger Action Programs Generator, Imam Nur Bani Yusuf, Diyanah Abdul Jamal, Lingxiao Jiang, David Lo
Recipegen++: An Automated Trigger Action Programs Generator, Imam Nur Bani Yusuf, Diyanah Abdul Jamal, Lingxiao Jiang, David Lo
Research Collection School Of Computing and Information Systems
Trigger Action Programs (TAPs) are event-driven rules that allow users to automate smart-devices and internet services. Users can write TAPs by specifying triggers and actions from a set of predefined channels and functions. Despite its simplicity, composing TAPs can still be challenging for users due to the enormous search space of available triggers and actions. The growing popularity of TAPs is followed by the increasing number of supported devices and services, resulting in a huge number of possible combinations between triggers and actions. Motivated by such a fact, we improve our prior work and propose RecipeGen++, a deep-learning-based approach that …
Predictive Self-Organizing Neural Networks For In-Home Detection Of Mild Cognitive Impairment, Seng Khoon Teh, Iris Rawtaer, Ah-Hwee Tan
Predictive Self-Organizing Neural Networks For In-Home Detection Of Mild Cognitive Impairment, Seng Khoon Teh, Iris Rawtaer, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
In-home sensing of daily living patterns from older adults coupled with machine learning is a promisingapproach to detect Mild Cognitive Impairment (MCI), a potentially reversible condition with early detectionand appropriate intervention. However, the number of subjects involved in such real-world studies istypically limited, posing the so-called small data problem to most predictive models which rely on a sizablenumber of labeled data. In this work, a predictive self-organizing neural network known as fuzzy AdaptiveResonance Associate Map (fuzzy ARAM) is proposed to detect MCI using in-home sensor data collected from aunique Singapore cross-sectional study. Specifically, mean and standard deviation of nine in-home …
Autopruner: Transformer-Based Call Graph Pruning, Cong Thanh Le, Hong Jin Kang, Truong Giang Nguyen, Stefanus Agus Haryono, David Lo, Xuan-Bach D. Le, Huynh Quyet Thang
Autopruner: Transformer-Based Call Graph Pruning, Cong Thanh Le, Hong Jin Kang, Truong Giang Nguyen, Stefanus Agus Haryono, David Lo, Xuan-Bach D. Le, Huynh Quyet Thang
Research Collection School Of Computing and Information Systems
Constructing a static call graph requires trade-offs between soundness and precision. Program analysis techniques for constructing call graphs are unfortunately usually imprecise. To address this problem, researchers have recently proposed call graph pruning empowered by machine learning to post-process call graphs constructed by static analysis. A machine learning model is built to capture information from the call graph by extracting structural features for use in a random forest classifier. It then removes edges that are predicted to be false positives. Despite the improvements shown by machine learning models, they are still limited as they do not consider the source code …
How To Formulate Specific How-To Questions In Software Development?, Mingwei Liu, Xin Peng, Andrian Marcus, Christoph Treude, Jiazhan Xie, Huanjun Xu, Yanjun Yang
How To Formulate Specific How-To Questions In Software Development?, Mingwei Liu, Xin Peng, Andrian Marcus, Christoph Treude, Jiazhan Xie, Huanjun Xu, Yanjun Yang
Research Collection School Of Computing and Information Systems
Developers often ask how-to questions using search engines, technical Q&A communities, and interactive Q&A systems to seek help for specific programming tasks. However, they often do not formulate the questions in a specific way, making it hard for the systems to return the best answers. We propose an approach (TaskKG4Q) that interactively helps developers formulate a programming related how-to question. TaskKG4Q is using a programming task knowledge graph (task KG in short) mined from Stack Overflow questions, which provides a hierarchical conceptual structure for tasks in terms of [actions], [objects], and [constraints]. An empirical evaluation of the intrinsic quality of …
In War And Peace: The Impact Of World Politics On Software Ecosystems, Raula Kula, Christoph Treude
In War And Peace: The Impact Of World Politics On Software Ecosystems, Raula Kula, Christoph Treude
Research Collection School Of Computing and Information Systems
Reliance on third-party libraries is now commonplace in contemporary software engineering. Being open source in nature, these libraries should advocate for a world where the freedoms and opportunities of open source software can be enjoyed by all. Yet, there is a growing concern related to maintainers using their influence to make political stances (i.e., referred to as protestware). In this paper, we reflect on the impact of world politics on software ecosystems, especially in the context of the ongoing War in Ukraine. We show three cases where world politics has had an impact on a software ecosystem, and how these …
Avoiding Bias In The Search For Implicit Bias, Wilson Cyrus-Lai, Warren Tierney, Christilene Du Plessis, My Nguyen, Michael Schaerer, Elena Giulia Clemente, Eric Luis Uhlmann
Avoiding Bias In The Search For Implicit Bias, Wilson Cyrus-Lai, Warren Tierney, Christilene Du Plessis, My Nguyen, Michael Schaerer, Elena Giulia Clemente, Eric Luis Uhlmann
Research Collection Lee Kong Chian School Of Business
To revitalize the study of unconscious bias, Gawronski, Ledgerwood, and Eastwick (this issue) propose a paradigm shift away from implicit measures of intergroup attitudes and beliefs. Specifically, researchers should capture discriminatory biases and demonstrate that participants are unaware of the influence of social category cues on their judgments and actions. Individual differences in scores on implicit measures will be useful to predict and better understand implicitly prejudiced behaviors, but the latter should be the collective focus of researchers interested in unconscious biases against social groups.
Revisiting Meta-Analytic Estimates Of Validity In Personnel Selection: Addressing Systematic Overcorrection For Restriction Of Range, Paul R. Sackett, Charlene Zhang, Christopher M. Berry, Filip Lievens
Revisiting Meta-Analytic Estimates Of Validity In Personnel Selection: Addressing Systematic Overcorrection For Restriction Of Range, Paul R. Sackett, Charlene Zhang, Christopher M. Berry, Filip Lievens
Research Collection Lee Kong Chian School Of Business
This paper systematically revisits prior meta-analytic conclusions about the criterion-related validity of personnel selection procedures, and particularly the effect of range restriction corrections on those validity estimates. Corrections for range restriction in meta-analyses of predictor–criterion relationships in personnel selection contexts typically involve the use of an artifact distribution. After outlining and critiquing five approaches that have commonly been used to create and apply range restriction artifact distributions, we conclude that each has significant issues that often result in substantial overcorrection and that therefore the validity of many selection procedures for predicting job performance has been substantially overestimated. Revisiting prior meta-analytic …
Commonality In Credit Spread Changes: Dealer Inventory And Intermediary Distress, Zhiguo He, Paymon Khorrami, Zhaogang Song
Commonality In Credit Spread Changes: Dealer Inventory And Intermediary Distress, Zhiguo He, Paymon Khorrami, Zhaogang Song
Research Collection Lee Kong Chian School Of Business
Two intermediary-based factors—a corporate bond dealer inventory measure and a broad intermediary distress measure—explain more than 40% of the puzzling common variation in credit spread changes beyond canonical structural factors. A simple intermediary-based model with partial market segmentation accounts for intermediary factors’ explanatory power and delivers three further implications with empirical support. First, whereas bond sorts on risk-related variables produce monotonic loading patterns on intermediary factors, non-risk-related sorts produce no pattern. Second, dealer inventory comoves with corporate-credit assets only, whereas intermediary distress comoves with both corporate-credit and non-corporate-credit assets. Third, dealers’ inventory responds to (instrumented) bond sales by institutional investors.
A Consumer Perspective On Managing The Consequences Of Chain Liability, Julia Hartmann, Sebastian Forkmann, Sabine Benoit, Stephan C. Henneberg
A Consumer Perspective On Managing The Consequences Of Chain Liability, Julia Hartmann, Sebastian Forkmann, Sabine Benoit, Stephan C. Henneberg
Research Collection Lee Kong Chian School Of Business
Consumers tend to hold a focal firm responsible for its suppliers' unsustainable practices (chain liability), suggesting that firms need effective responses that can mitigate negative consumer reactions. In applying psychological contract theory to investigate recovery efforts related to such chain liability, the current study addresses three broad focal firm responses: Do nothing, choose a nonsubstantive response that verbally clarifies its own and the supplier's roles in the incident, or substantively rectify the supplier's wrongdoing with sustainability-focused responses, such as termination, monitoring or development. With a vignette-based experiment, we examine consumer perceptions and behaviors in three stages: before the unsustainable supplier …
Transrepair: Context-Aware Program Repair For Compilation Errors, Xueyang Li, Shangqing Liu, Ruitao Feng, Guozhu Meng, Xiaofei Xie, Kai Chen, Yang Liu
Transrepair: Context-Aware Program Repair For Compilation Errors, Xueyang Li, Shangqing Liu, Ruitao Feng, Guozhu Meng, Xiaofei Xie, Kai Chen, Yang Liu
Research Collection School Of Computing and Information Systems
Automatically fixing compilation errors can greatly raise the productivity of software development, by guiding the novice or AI programmers to write and debug code. Recently, learning-based program repair has gained extensive attention and became the state of-the-art in practice. But it still leaves plenty of space for improvement. In this paper, we propose an end-to-end solution TransRepair to locate the error lines and create the correct substitute for a C program simultaneously. Superior to the counterpart, our approach takes into account the context of erroneous code and diagnostic compilation feedback. Then we devise a Transformer-based neural network to learn the …
Hierarchical Hourglass Convolutional Network For Efficient Video Classification, Yi Tan, Yanbin Hao, Hao Zhang, Shuo Wang
Hierarchical Hourglass Convolutional Network For Efficient Video Classification, Yi Tan, Yanbin Hao, Hao Zhang, Shuo Wang
PhD Student’s Publications Collection
Videos naturally contain dynamic variation over the temporal axis, which will result in the same visual clues (e.g., semantics, objects) changing their scale, position, and perspective patterns between adjacent frames. A primary trend in video CNN is adopting spatial-2D convolution for spatial semantics and temporal-1D convolution for temporal dynamics. Though the direction achieves a favorable balance between efficiency and efficacy, it suffers from misalignment of visual clues with large displacements. Particularly, rigid temporal convolution would fail to capture correct motions when a specific target moves out of the reception field of temporal convolution between adjacent frames.To tackle large visual displacements …
Impact Of Geographical Diversification And Limited Attention On Private Equity Fund Returns, Victor Hock Keong Ong
Impact Of Geographical Diversification And Limited Attention On Private Equity Fund Returns, Victor Hock Keong Ong
Dissertations and Theses Collection (Open Access)
This study analyzes the effect of geographical diversification on global private equity (PE) fund returns. I find that there is a negative correlation between geographical diversification and PE fund returns. To establish the causality between geographical diversification and PE fund returns, I employ an instrument variable analysis where the instrument used is the stock market capitalization value of the host country where the PE fund is based. My results apply to Net IRR, multiple and DPI as dependent variables used to proxy for PE fund returns in the main regression model. A one standard deviation increase in geographical diversification results …
Vpsl: Verifiable Privacy-Preserving Data Search For Cloud-Assisted Internet Of Things, Qiuyun Tong, Yinbin Miao, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng
Vpsl: Verifiable Privacy-Preserving Data Search For Cloud-Assisted Internet Of Things, Qiuyun Tong, Yinbin Miao, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cloud-assisted Internet of Things (IoT) is increasingly prevalent used in various fields, such as the healthcare system. While in such a scenario, sensitive data (e.g., personal electronic medical records) can be easily revealed, which incurs potential security challenges. Thus, Symmetric Searchable Encryption (SSE) has been extensively studied due to its capability of supporting efficient search on encrypted data. However, most SSE schemes require the data owner to share the complete key with query users and take malicious cloud servers out of consideration. Seeking to address these limitations, in this paper we propose a Verifiable Privacy-preserving data Search scheme with Limited …
Two Singapore Public Healthcare Ai Applications For National Screening Programs And Other Examples, Andy Wee An Ta, Han Leong Goh, Christine Ang, Lian Yeow Koh, Ken Poon, Steven M. Miller
Two Singapore Public Healthcare Ai Applications For National Screening Programs And Other Examples, Andy Wee An Ta, Han Leong Goh, Christine Ang, Lian Yeow Koh, Ken Poon, Steven M. Miller
Research Collection School Of Computing and Information Systems
This article explains how two AI systems have been incorporated into the everyday operations of two Singapore public healthcare nation-wide screening programs. The first example is embedded within the setting of a national level population health screening program for diabetes related eye diseases, targeting the rapidly increasing number of adults in the country with diabetes. In the second example, the AI assisted screening is done shortly after a person is admitted to one of the public hospitals to identify which inpatients—especially which elderly patients with complex conditions—have a high risk of being readmitted as an inpatient multiple times in the …
Qvip: An Ilp-Based Formal Verification Approach For Quantized Neural Networks, Yedi Zhang, Zhe Zhao, Guangke Chen, Fu Song, Min Zhang, Taolue Chen, Jun Sun
Qvip: An Ilp-Based Formal Verification Approach For Quantized Neural Networks, Yedi Zhang, Zhe Zhao, Guangke Chen, Fu Song, Min Zhang, Taolue Chen, Jun Sun
Research Collection School Of Computing and Information Systems
Deep learning has become a promising programming paradigm in software development, owing to its surprising performance in solving many challenging tasks. Deep neural networks (DNNs) are increasingly being deployed in practice, but are limited on resource-constrained devices owing to their demand for computational power. Quantization has emerged as a promising technique to reduce the size of DNNs with comparable accuracy as their floating-point numbered counterparts. The resulting quantized neural networks (QNNs) can be implemented energy-efficiently. Similar to their floating-point numbered counterparts, quality assurance techniques for QNNs, such as testing and formal verification, are essential but are currently less explored. In …
Ergo: Event Relational Graph Transformer For Document-Level Event Causality Identification, Meiqi Chen, Yixin Cao, Kunquan Deng, Mukai Li, Kun Wang, Jing Shao, Yan Zhang
Ergo: Event Relational Graph Transformer For Document-Level Event Causality Identification, Meiqi Chen, Yixin Cao, Kunquan Deng, Mukai Li, Kun Wang, Jing Shao, Yan Zhang
Research Collection School Of Computing and Information Systems
Document-level Event Causality Identification (DECI) aims to identify event-event causal relations in a document. Existing works usually build an event graph for global reasoning across multiple sentences. However, the edges between events have to be carefully designed through heuristic rules or external tools. In this paper, we propose a novel Event Relational Graph TransfOrmer (ERGO) framework1 for DECI, to ease the graph construction and improve it over the noisy edge issue. Different from conventional event graphs, we define a pair of events as a node and build a complete event relational graph without any prior knowledge or tools. This naturally …
Interactive Contrastive Learning For Self-Supervised Entity Alignment, Kaisheng Zeng, Zhenhao Dong, Lei Hou, Yixin Cao, Minghao Hu, Jifan Yu, Xin Lv, Lei Cao, Xin Wang, Haozhuang Liu, Yi Huang, Jing Wan, Juanzi Li
Interactive Contrastive Learning For Self-Supervised Entity Alignment, Kaisheng Zeng, Zhenhao Dong, Lei Hou, Yixin Cao, Minghao Hu, Jifan Yu, Xin Lv, Lei Cao, Xin Wang, Haozhuang Liu, Yi Huang, Jing Wan, Juanzi Li
Research Collection School Of Computing and Information Systems
Self-supervised entity alignment (EA) aims to link equivalent entities across different knowledge graphs (KGs) without the use of pre-aligned entity pairs. The current state-of-the-art (SOTA) selfsupervised EA approach draws inspiration from contrastive learning, originally designed in computer vision based on instance discrimination and contrastive loss, and suffers from two shortcomings. Firstly, it puts unidirectional emphasis on pushing sampled negative entities far away rather than pulling positively aligned pairs close, as is done in the well-established supervised EA. Secondly, it advocates the minimum information requirement for self-supervised EA, while we argue that self-described KG’s side information (e.g., entity name, relation name, …