# Differences

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schedule [2019/01/09 10:54] avis |
schedule [2019/01/19 19:21] (current) avis |
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Abstract: In this talk I will present recent developments on quantum algorithms for problems from linear algebra and graph-theoretic problems. I will first introduce the concept of quantum algorithms, and in particular the powerful technique known as “quantum search”, and describe several fundamental applications. Most examples will deal with problems from linear algebra (computing the product of two matrices, inverting a matrix,…), and their natural applications to graph-theoretic problems. | Abstract: In this talk I will present recent developments on quantum algorithms for problems from linear algebra and graph-theoretic problems. I will first introduce the concept of quantum algorithms, and in particular the powerful technique known as “quantum search”, and describe several fundamental applications. Most examples will deal with problems from linear algebra (computing the product of two matrices, inverting a matrix,…), and their natural applications to graph-theoretic problems. | ||

+ | == October 18 == | ||

+ | <color brown> 14:45 -16:15, Joho 2, Research Bldg. No.7 (総合７), Main Campus </color>\\ | ||

+ | **[[http://cgm.cs.mcgill.ca/~avis/Kyoto/|David Avis]]**, //Kyoto University and McGill University// \\ | ||

+ | Title: **All Meals for a Dollar and Other Vertex Enumeration Problems**\\ | ||

+ | Abstract: Linear programming is a powerful modelling tool that has wide application and is very efficient in practice. However it provides only the optimum solution to a linear program. How can one obtain a set of near optimum solutions, say those within 1% of the optimum? This is an example of a vertex enumeration problem. I will introduce this problem, give some examples such as computing all meals for a dollar, and discuss its solution using the reverse search technique discovered by the speaker and Komei Fukuda. | ||

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+ | Bio: David Avis is Professor Emeritus in the School of Computer Science at McGill University and a researcher in the Department of Intelligence Science and Technology at Kyoto University. He received his PhD in 1977 from Stanford University in Operations Research. His research interests include discrete optimization, polyhedral computation and parallel computation. | ||

== October 25 == | == October 25 == | ||

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Abstract: I will describe mts, a generic framework for parallelizing certain types of tree search programs using a single common wrapper. The first part of the talk is a tutorial on how to parallelize enumeration codes based on reverse search using a very simple mts interface. mts also supports sharing information between processes which is important for applications such as satisfiability testing and branch-and-bound. No parallelization is implemented in the legacy single processor code minimizing the changes needed and simplifying debugging. mts is written in C, uses MPI for parallelization and can be used on a network of computers. I will give computational results for the parallelization of two simple existing reverse search codes, generating topological sorts and generating spanning trees of a graph, and two codes for satisfiability testing. (Joint work with Skip Jordan) | Abstract: I will describe mts, a generic framework for parallelizing certain types of tree search programs using a single common wrapper. The first part of the talk is a tutorial on how to parallelize enumeration codes based on reverse search using a very simple mts interface. mts also supports sharing information between processes which is important for applications such as satisfiability testing and branch-and-bound. No parallelization is implemented in the legacy single processor code minimizing the changes needed and simplifying debugging. mts is written in C, uses MPI for parallelization and can be used on a network of computers. I will give computational results for the parallelization of two simple existing reverse search codes, generating topological sorts and generating spanning trees of a graph, and two codes for satisfiability testing. (Joint work with Skip Jordan) | ||

- | Bio: David Avis is Professor Emeritus in the School of Computer Science at McGill University and a researcher in the Department of Intelligence Science and Technology at Kyoto University. He received his PhD in 1977 from Stanford University in Operations Research. His research interests include discrete optimization, polyhedral computation and parallel computation. | + | |

== January 24 == | == January 24 == | ||

<color brown> 14:45 -16:15, Joho 2, Research Bldg. No.7 (総合７), Main Campus </color>\\ | <color brown> 14:45 -16:15, Joho 2, Research Bldg. No.7 (総合７), Main Campus </color>\\ | ||

- | **[[http://adnan-sljoka.ca/|Adnan Sljoka]]**, ////Kwansei Gakuin University// \\ | + | **[[http://adnan-sljoka.ca/|Adnan Sljoka]]**, //Kwansei Gakuin University// \\ |

Title: **Rigidity Theory and its Applications to Protein Function Analysis**\\ | Title: **Rigidity Theory and its Applications to Protein Function Analysis**\\ | ||

+ | |||

+ | Abstract: Rigidity theory has a rich mathematical foundation in geometry and graph theory and it investigates the rigidity and flexibility of structures which are defined by geometric constraints on a set of rigid objects. Rigidity theory has many practical applications in engineering, material science and biochemistry. Since the time of Laman’s theorem (1970), which gives a rigorous combinatorial (counting) characterization for (generic) rigidity of 2-dimensional bar and joint frameworks, there have been a number of important advancements in this rich and fascinating subject. In this talk we will introduce some basic concepts and algorithms in rigidity theory and its applications to predicting flexibility and dynamics of protein structures to better understand their function. We will discuss our experimentally validated methods on probing the mechanism of elusive allosteric regulation (i.e. second secret of life) of protein function (Science, 2017, Nature Communication, 2018) and other proteins as a powerful computational algorithms and methods for probing the difficult allosteric control of protein function. We will also highlight our recent results on uses of rigidity theory algorithms in analysis of antibodies [Frontiers in Immunology, 2018] which provides novel insights into how immune system proteins recognize antigens. We will also discuss decomposition of special minimally rigid graphs and their applications in robotics. | ||

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+ | Bio: | ||

+ | Adnan Sljoka is a Canadian, Applied Mathematician and Computational Biologist. His research is highly interdisciplinary. He is working on rigidity theory and algorithm design for analysis of protein function, drug discovery and robotics. He completed his PhD at York University in Toronto, Canada in 2012 in Applied Mathematics. Currently he is a Visiting Professor in University of Toronto in Biochemistry and Assistant Professor in Kwansei Gakuin, Informatics. For more info see http://adnan-sljoka.ca/ | ||