Faculty of Mathematics, University of Waterloo

WebNotice Postings: 20-Apr-2015 through 26-Apr-2015

Postings for all Departments

Monday, 20 April 2015, 12:30PM -- DC 2314
Information Retrieval Group Seminar -- Computer Science
Speaker: Nava Ehsan, Visiting PhD candidate, University of Tehran
Title: "Extrinsic cross language plagiarism detection."
Abstract: Plagiarism refers to unauthorized use of text, code and ideas. In automatic cross-language plagiarism detection, the task is to retrieve plagiarized text written in language L that has originated from another document in a language other than L. With the rapid growth of documents in different languages, the increased accessibility of electronic documents, and the availability of translation tools, cross-language plagiarism detection has become a serious problem and requires more attention. The task entails two main steps: candidate retrieval and detailed analysis. Candidate retrieval entails the identification of source documents that contain suspicious fragments. Detailed analysis requires closer comparison of the subject document with each suspected source and retrieval of plagiarized fragments.

Monday, 20 April 2015, 2:30PM -- QNC 0101
Seminar -- Institute for Quantum Computing
Speaker: Jerry Chow, IBM T.J. Watson Research Center, USA
Title: "Taking Superconducting Qubits to the Next Generation"
Abstract: Fault tolerant quantum computing is possible by employing quantum error correction techniques. In this talk I will describe an implementation of a true quantum code using 4 lithographically defined superconducting qubits in a square lattice capable of measuring both types of possible quantum errors occurring on a single qubit. The experiment requires highly coherent qubits, high quality quantum operations implementing the detecting circuit, and a high quality independent qubit measurement set-up. Looking beyond this implementation, there remains both theoretical and experimental control hurdles which must be overcome to build verifiably reliable quantum networks of qubits. I will present some experiments which point towards these important questions and give proposals for future integration capability, measurement integration, and scalable control architectures. The focus will be on a variety of questions which will increasingly become important as the field moves towards a larger network of qubits.

Tuesday, 21 April 2015, 4:00PM -- DC 1304
Waterloo Research Institute in Insurance, Securities and Quantitative Finance Seminar -- Statistics & Actuarial Science
Speaker: Amir Memartoluie, PhD Candidate, David R. Cheriton School of Computer Science, University of Waterloo
Title: "On the Rearrangement and Related Algorithms for Computing Worst Value-at-Risk: Computational Improvements and the Adaptive Rearrangement Algorithm"
Abstract: ABSTRACT: Recently, the Rearrangement Algorithm (in the general case) and “explicit” algorithms (in the homogeneous case) were introduced to approximately compute worst Value-at-Risk for a portfolio with given marginal loss distributions. However, practitioners are often left alone with crucial choices of tuning parameters and other decisions when implementing such algorithms. In the present work, numerical challenges inherent in various algorithms for computing worst Value-at-Risk are identified and words of warning concerning their implementation are raised. Furthermore, both numerical and conceptual improvements to these algorithms are provided (e.g., more meaningful tuning parameters). All presented algorithms and their improvements have been implemented in the R package qrmtools. (co-authors: Marius Hofert, David Saunders and Tony Wirjanto)

BIO: I am a Ph.D. candidate at Cheriton School of Computer Science, University of Waterloo, working under the supervision of Prof. Tony Wirjanto and Prof. David Saunders. I received my Master in Quantitative Finance from the Centre for Advanced Studies in Finance at the University of Waterloo in 2009. As of September 2011, I represent the Faculty of Mathematics for the Graduate Studies Endowment Fund at the University of Waterloo. I studied statistics and applied mathematics prior to my studies in finance and received my M.Sc. in statistics from Concordia University in 2007. I received my B.Sc. in applied mathematics (First Class Honors), from the Department of Mathematics at K.N.T. University of Technology, Tehran.

Wednesday, 22 April 2015, 11:00AM -- DC 2585
ISS4E Seminar -- Computer Science
Speaker: Xue (Steve) Liu, William Dawson Scholar and Assoc. Prof., School of Comp. Sci., McGill University
Title: "Intelligent Load Balancing for Smart Energy Powered Internet Data Centres"
Abstract: The operations of today's Internet data centres (IDCs) require gigantic amount of energy. Companies like Facebook, Google, Microsoft, Yahoo pay tens of millions of dollars annually for electricity. In the meantime, smart grid and renewable energy technologies have gained significant momentum. In this talk, I will summarize research findings from two of our recent projects focusing on smart energy powered Internet data centres. The first project discusses Geographical Load Balancing designs to minimize the electricity cost for IDC operations. The second project discusses how to power up IDCs with renewable wind energy.


Brief Bio:

Xue (Steve) Liu is a William Dawson Scholar and an Associate Professor in the School of Computer Science at McGill University in Montreal, Canada. He received his Ph.D. in Computer Science (with multiple honours) from the University of Illinois at Urbana-Champaign. He has also worked as the Samuel R. Thompson Chaired Associate Professor in the University of Nebraska-Lincoln and at HP Labs in Palo Alto, California. His research interests are in computer and communication networks, real-time and embedded systems, cyber-physical systems, green computing and smart energy technologies. He has published over 200 research papers in major peer-reviewed international journals and conference proceedings in these areas and received several best paper awards. Dr. Liu's research has been reported by news media including the New York Times, Computer World, Business Insider, The Register, Huffington Post, CBC, NewScientist, MIT Technology Review's Blog, etc.

He is a recipient of the Outstanding Young Canadian Computer Science Researcher Prizes from the Canadian Association of Computer Science, and a recipient of the Tomlinson Scientist Award from McGill University. He serves on the editorial boards of IEEE Transactions of Parallel and Distributed Systems (TPDS), IEEE Transactions on Vehicular Technology (TVT), and IEEE Communications Surveys and Tutorials (COMST).

Wednesday, 22 April 2015, 1:30PM -- DC 1304 true
Algorithms and Complexity Group Seminar -- Computer Science
Speaker: Professor A. Lopez-Ortiz, David R. Cheriton School of Comp. Sci., Univ. Waterloo
Title: "Finding Out Who Hangs With Whom in Social Networks .....or Equivalently...... Kernelization Algorithms for Packing Problems Allowing Overlaps'"
Abstract: We consider the problem of discovering overlapping communities in social networks. This can be modeled as generalizations of the Set and Graph Packing problems with overlap. More formally we seek a sub-collection S consisting of at least k sets subject to certain disjointness restrictions. In the r-Set Packing with t-Membership, each element belongs to at most t sets of S while in r-Set Packing with t-Overlap each pair of sets in S overlaps in at most t elements.

Similarly, both of our graph packing problems seek a sub-collection of at least k subgraphs in a graph G each isomorphic to one of several graphs H of at most r vertices. In H-Packing with t-Membership, each vertex of G belongs to at most t subgraphs in the sub-collection while in H-Packing with t-Overlap each pair of subgraphs overlaps in at most t vertices.

Here, we show NP-Completeness results for all of our packing problems. Furthermore, we give a dichotomy result for H-Packing with t-Membership. Given this intractability, we reduce r-Set Packing with t-Membership and t-Overlap to problem kernels with O((r+1)^r k^{r}) and O(r^r k^{r-t-1}) elements, respectively. Similarly, we reduce H-Packing with t-Membership and t-Overlap to instances with O((r+1)^r k^{r}) and O(r^r k^{r-t-1}) vertices, respectively. In all cases, k is the input parameter while t and r are constants.

This is joint work with Jazmin Romero (Waterloo) and Henning Fernau (Trier, Germany).

Thursday, 23 April 2015, 1:00PM -- DC 1331
Cryptography, Security, and Privacy (CrySP) Group PhD Seminar -- Computer Science
Speaker: Hassan Khan, PhD candidate, David R. Cheriton School of Comp. Sci., Univ. Waterloo
Title: "Itus: An Implicit Authentication Framework for Android"
Abstract: Security and usability issues with pass-locks on mobile devices have prompted researchers to develop implicit authentication (IA) schemes, which continuously and transparently authenticate users using behavioural biometrics. Contemporary IA schemes proposed by the research community are challenging to deploy, and there is a need for a framework that supports: different behavioural classifiers, given that different apps have different requirements; app developers using IA without becoming domain experts; and real-time classification on resource-constrained mobile devices. We present Itus, an IA framework for Android that allows the research community to improve IA schemes incrementally, while allowing app developers to adopt these improvements at their own pace. We describe the Itus framework and how it provides: (i) ease of use: Itus allows app developers to use IA by changing as few as two lines of their existing code - on the other hand, Itus provides an oracle capable of making advanced recommendations should developers wish to fine-tune the classifiers; (ii) flexibility: developers can deploy Itus in an application-specific manner, adapting to their unique needs; (iii) extensibility: researchers can contribute new behavioural features and classifiers without worrying about deployment particulars; (iv) low performance overhead: Itus operates with minimal performance overhead, allowing app developers to deploy it without compromising end-user experience. These goals are accomplished with an API allowing individual stakeholders to incrementally improve Itus without re-engineering new systems. We implement Itus in two demo apps and measure its performance impact. To our knowledge, Itus is the first open-source extensible IA framework for Android that can be deployed off-the-shelf.

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