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Articles 31 - 44 of 44
Full-Text Articles in Engineering
Incentivizing Collaboration In A Competition, Arunesh Sinha, Michael P. Wellman
Incentivizing Collaboration In A Competition, Arunesh Sinha, Michael P. Wellman
Research Collection School Of Computing and Information Systems
Research and design competitions aim to promote innovation or creative production, which are often best achieved through collaboration. The nature of a competition, however, typically necessitates sorting by individual performance. This presents tradeoffs for the competition designer, between incentivizing global performance and distinguishing individual capability. We model this situation in terms of an abstract collaboration game, where individual effort also benefits neighboring agents. We propose a scoring mechanism called LSWM that rewards agents based on localized social welfare. We show that LSWM promotes global performance, in that social optima are equilibria of the mechanism. Moreover, we establish conditions under which …
Designated-Server Identity-Based Authenticated Encryption With Keyword Search For Encrypted Emails, Hongbo Li, Qiong Huang, Jian Shen, Guomin Yang, Willy Susilo
Designated-Server Identity-Based Authenticated Encryption With Keyword Search For Encrypted Emails, Hongbo Li, Qiong Huang, Jian Shen, Guomin Yang, Willy Susilo
Research Collection School Of Computing and Information Systems
In encrypted email system, how to search over encrypted cloud emails without decryption is an important and practical problem. Public key encryption with keyword search (PEKS) is an efficient solution to it. However, PEKS suffers from the complex key management problem in the public key infrastructure. Its variant in the identity-based setting addresses the drawback, however, almost all the schemes does not resist against offline keyword guessing attacks (KGA) by inside adversaries. In this work we introduce the notion of designated-server identity-based authenticated encryption with keyword search (dIBAEKS), in which the email sender authenticates the message while encrypting so that …
Community Discovery In Heterogeneous Social Networks, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch
Community Discovery In Heterogeneous Social Networks, Lei Meng, Ah-Hwee Tan, Donald C. Wunsch
Research Collection School Of Computing and Information Systems
Discovering social communities of web users through clustering analysis of heterogeneous link associations has drawn much attention. However, existing approaches typically require the number of clusters a priori, do not address the weighting problem for fusing heterogeneous types of links, and have a heavy computational cost. This chapter studies the commonly used social links of users and explores the feasibility of the proposed heterogeneous data co-clustering algorithm GHF-ART, as introduced in Sect. 3.6, for discovering user communities in social networks. Contrary to the existing algorithms proposed for this task, GHF-ART performs real-time matching of patterns and one-pass learning, which guarantees …
Cure: Flexible Categorical Data Representation By Hierarchical Coupling Learning, Songlei Jian, Guansong Pang, Longbing Cao, Kai Lu, Hang Gao
Cure: Flexible Categorical Data Representation By Hierarchical Coupling Learning, Songlei Jian, Guansong Pang, Longbing Cao, Kai Lu, Hang Gao
Research Collection School Of Computing and Information Systems
The representation of categorical data with hierarchical value coupling relationships (i.e., various value-to-value cluster interactions) is very critical yet challenging for capturing complex data characteristics in learning tasks. This paper proposes a novel and flexible coupled unsupervised categorical data representation (CURE) framework, which not only captures the hierarchical couplings but is also flexible enough to be instantiated for contrastive learning tasks. CURE first learns the value clusters of different granularities based on multiple value coupling functions and then learns the value representation from the couplings between the obtained value clusters. With two complementary value coupling functions, CURE is instantiated into …
Emerging App Issue Identification From User Feedback: Experience On Wechat, Cuiyun Gao, Wujie Zheng, Yuetang Deng, David Lo, Jichuan Zeng, Michael R. Lyu, Irwin King
Emerging App Issue Identification From User Feedback: Experience On Wechat, Cuiyun Gao, Wujie Zheng, Yuetang Deng, David Lo, Jichuan Zeng, Michael R. Lyu, Irwin King
Research Collection School Of Computing and Information Systems
It is vital for popular mobile apps with large numbers of users to release updates with rich features while keeping stable user experience. Timely and accurately locating emerging app issues can greatly help developers to maintain and update apps. User feedback (i.e., user reviews) is a crucial channel between app developers and users, delivering a stream of information about bugs and features that concern users. Methods to identify emerging issues based on user feedback have been proposed in the literature, however, their applicability in industry has not been explored. We apply the recent method IDEA to WeChat, a popular messenger …
Interaction-Aware Arrangement For Event-Based Social Networks, Feifei Kou, Zimu Zhou, Hao Cheg, Junping Du, Yexuan Shi, Pan Xu
Interaction-Aware Arrangement For Event-Based Social Networks, Feifei Kou, Zimu Zhou, Hao Cheg, Junping Du, Yexuan Shi, Pan Xu
Research Collection School Of Computing and Information Systems
No abstract provided.
Wiwear: Wearable Sensing Via Directional Wifi Energy Harvesting, Huy Vu Tran, Archan Misra, Jie Xiong, Rajesh Krishna Balan
Wiwear: Wearable Sensing Via Directional Wifi Energy Harvesting, Huy Vu Tran, Archan Misra, Jie Xiong, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Energy harvesting, from a diverse set of modes such as light or motion, has been viewed as the key to developing batteryless sensing devices. In this paper, we develop the nascent idea of harvesting RF energy from WiFi transmissions, applying it to power a prototype wearable device that captures and transmits accelerometer sensor data. Our solution, WiWear, has two key innovations: 1) beamforming WiFi transmissions to significantly boost the energy that a receiver can harvest ~23 meters away, and 2) smart zero-energy, triggering of inertial sensing, that allows intelligent duty-cycled operation of devices whose transient power consumption far exceeds what …
Ict: In-Field Calibration Transfer For Air Quality Sensor Deployments, Yun Cheng, Xiaoxi He, Zimu Zhou, Lothar Thiele
Ict: In-Field Calibration Transfer For Air Quality Sensor Deployments, Yun Cheng, Xiaoxi He, Zimu Zhou, Lothar Thiele
Research Collection School Of Computing and Information Systems
Recent years have witnessed a growing interest in urban air pollution monitoring, where hundreds of low-cost air quality sensors are deployed city-wide. To guarantee data accuracy and consistency, these sensors need periodic calibration after deployment. Since access to ground truth references is often limited in large-scale deployments, it is difficult to conduct city-wide post-deployment sensor calibration. In this work we propose In-field Calibration Transfer (ICT), a calibration scheme that transfers the calibration parameters of source sensors (with access to references) to target sensors (without access to references). On observing that (i) the distributions of ground truth in both source and …
Fc2: Cloud-Based Cluster Provisioning For Distributed Machine Learning, Nguyen Binh Duong Ta
Fc2: Cloud-Based Cluster Provisioning For Distributed Machine Learning, Nguyen Binh Duong Ta
Research Collection School Of Computing and Information Systems
Training large, complex machine learning models such as deep neural networks with big data requires powerful computing clusters, which are costly to acquire, use and maintain. As a result, many machine learning researchers turn to cloud computing services for on-demand and elastic resource provisioning capabilities. Two issues have arisen from this trend: (1) if not configured properly, training models on cloud-based clusters could incur significant cost and time, and (2) many researchers in machine learning tend to focus more on model and algorithm development, so they may not have the time or skills to deal with system setup, resource selection …
Topical Co-Attention Networks For Hashtag Recommendation On Microblogs, Yang Li, Ting Liu, Jingwen Hu, Jing Jiang
Topical Co-Attention Networks For Hashtag Recommendation On Microblogs, Yang Li, Ting Liu, Jingwen Hu, Jing Jiang
Research Collection School Of Computing and Information Systems
Hashtags provide a simple and natural way of organizing content in microblog services. Along with the fast growing of microblog services, the task of recommending hashtags for microblogs has been given increasing attention in recent years. However, much of the research depends on hand-crafted features. Motivated by the successful use of neural models for many natural language processing tasks, in this paper, we adopt an attention based neural network to learn the representation of a microblog post. Unlike previous works, which only focus on content attention of microblogs, we propose a novel Topical CoAttention Network (TCAN) that jointly models content …
A Coordination Framework For Multi-Agent Persuasion And Adviser Systems, Budhitama Subagdja, Ah-Hwee Tan, Yilin Kang
A Coordination Framework For Multi-Agent Persuasion And Adviser Systems, Budhitama Subagdja, Ah-Hwee Tan, Yilin Kang
Research Collection School Of Computing and Information Systems
Assistive agents have been used to give advices to the users regarding activities in daily lives. Although adviser bots are getting smarter and gaining more popularity these days they are usually developed and deployed independent from each other. When several agents operate together in the same context, their advices may no longer be effective since they may instead overwhelm or confuse the user if not properly arranged. Only little attentions have been paid to coordinating different agents to give different advices to a user within the same environment. However, aligning the advices on-the-fly with the appropriate presentation timing at the …
Deception In Finitely Repeated Security Games, Thanh H. Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman
Deception In Finitely Repeated Security Games, Thanh H. Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman
Research Collection School Of Computing and Information Systems
Allocating resources to defend targets from attack is often complicated by uncertainty about the attacker’s capabilities, objectives, or other underlying characteristics. In a repeated interaction setting, the defender can collect attack data over time to reduce this uncertainty and learn an effective defense. However, a clever attacker can manipulate the attack data to mislead the defender, influencing the learning process toward its own benefit. We investigate strategic deception on the part of an attacker with private type information, who interacts repeatedly with a defender. We present a detailed computation and analysis of both players’ optimal strategies given the attacker may …
Vireo @ Video Browser Showdown 2019, Phuong Anh Nguyen, Chong-Wah Ngo, Danny Francis, Benoit Huet
Vireo @ Video Browser Showdown 2019, Phuong Anh Nguyen, Chong-Wah Ngo, Danny Francis, Benoit Huet
Research Collection School Of Computing and Information Systems
In this paper, the VIREO team video retrieval tool is described in details. As learned from Video Browser Showdown (VBS) 2018, the visualization of video frames is a critical need to improve the browsing effectiveness. Based on this observation, a hierarchical structure that represents the video frame clusters has been built automatically using k-means and self-organizing-map and used for visualization. Also, the relevance feedback module which relies on real-time supportvector-machine classification becomes unfeasible with the large dataset provided in VBS 2019 and has been replaced by a browsing module with pre-calculated nearest neighbors. The preliminary user study results on IACC.3 …
Person Re-Identification Over Encrypted Outsourced Surveillance Videos, Hang Cheng, Huaxiong Wang, Ximeng Liu, Yan Fang, Meiqing Wang, Xiaojun Zhang
Person Re-Identification Over Encrypted Outsourced Surveillance Videos, Hang Cheng, Huaxiong Wang, Ximeng Liu, Yan Fang, Meiqing Wang, Xiaojun Zhang
Research Collection School Of Computing and Information Systems
Person re-identification (Re-ID) has attracted extensive attention due to its potential to identify a person of interest from different surveillance videos. With the increasing amount of the surveillance videos, high computation and storage costs have posed a great challenge for the resource-constrained users. In recent years, the cloud storage services have made a large volume of video data outsourcing become possible. However, person Re-ID over outsourced surveillance videos could lead to a security threat, i.e., the privacy leakage of the innocent person in these videos. Therefore, we propose an efFicient privAcy-preseRving peRson Re-ID Scheme (FARRIS) over outsourced surveillance videos, which …