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Wang-Chien Lee
Researcher at Pennsylvania State University
Publications - 367
Citations - 15328
Wang-Chien Lee is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Wireless sensor network & Mobile computing. The author has an hindex of 60, co-authored 366 publications receiving 14123 citations. Previous affiliations of Wang-Chien Lee include Ohio State University & Verizon Communications.
Papers
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Journal ArticleDOI
Improving Data Analytics with Fast and Adaptive Regularization
TL;DR: This paper proposes a general adaptive regularization method based on Gaussian Mixture to learn the best regularization function according to the observed parameters, and develops an effective update algorithm which integrates Expectation Maximization with Stochastic Gradient Descent.
Proceedings ArticleDOI
Signature path dictionary for nested object query processing
Dik Lun Lee,Wang-Chien Lee +1 more
TL;DR: A new method is introduced, the signature path dictionary, which combines signature techniques with the path dictionary organization designed for fast object traversals and derives cost formulae for its storage overhead as well as the retrieval and update costs.
Journal ArticleDOI
On Extracting Socially Tenuous Groups for Online Social Networks with k-Triangles
Chih-Ya Shen,Hong-Han Shuai,De-Nian Yang,Guang-Siang Lee,Liang-Hao Huang,Wang-Chien Lee,Ming-Syan Chen +6 more
TL;DR: In this paper, the authors introduced the notion of k-triangles to measure the tenuity of a group and formulated a new research problem, Minimum k-Triangle Disconnected Group with No-Pair Constraint, to find a socially tenuous group from the online social network.
Journal ArticleDOI
Workload analysis for scientific literature digital libraries
TL;DR: This study presents an extensive analysis into the workload of scientific literature digital libraries, unveiling their temporal and user interest patterns and investigates how to utilize the findings to improve system performance.
Proceedings ArticleDOI
Distributed in-memory processing of All K Nearest Neighbor queries
Georgios Chatzimilioudis,Constantinos Costa,Demetrios Zeinalipour-Yazti,Wang-Chien Lee,Evaggelia Pitoura +4 more
TL;DR: This paper evaluates, both analytically and experimentally, how the pruning efficiency of the Spitfire algorithm plays a pivotal role in reducing communication and response time up to an order of magnitude, compared to three other state-of-the-art distributed AkNN algorithms executed in distributed main-memory.