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Computational Statistics Research Talk - Saied Amiri

Title: Revisiting the clustering methods with the application for the BIG DATA Abstract: According to the Moore’s and Kryder’s laws, the computational power and information storage increase exponentially, so researchers and workers need more sophisticated and advanced methods for managing and interrogating Big Data.

PhD Math Defence: Complex Matrix Scalings, Extremal Permanents, and the Geometric Measure of Entanglement

CANDIDATE:   GEORGE HUTCHINSON ABSTRACT: An n x n matrix with complex entries is said to be doubly quasi-stochastic (DQS) if all row and column sums are equal to one. Given a positive definite matrix A and a diagonal matrix D, we say that D*AD is a (complex matrix) scaling of A if D*AD is doubly quasi-stochastic. Motivated by a result of Pereira and Boneng concerning the application of complex matrix scalings to the geometric measure of entanglement of certain symmetric states, we embark upon an investigation of these scalings and their properties.

Computational Statistics Research Talk - Farhad Shokoohi

Title:  New Insight into the Role of Intangible Heterogeneity of Gene Effects on Survival Time of Patients with Ovarian Cancer:  A statistical method for variable selection in finite mixture of survival models Abstract:

Computational Statistics Research Talk - Dan Tulpan

Title: Wheat gene annotations via comparative genomics: challenges and solutions Abstract: While the gargantuan multi-nation effort of sequencing wheat gets close to completion, the annotation process for the vast number of wheat genes and proteins is in its infancy. Previous experimental studies carried out on model plant organisms such as Arabidopsis and rice provide a plethora of gene annotations that can be used as potential starting points for wheat gene annotations, proven that solid cross-species gene-to-gene and protein-to-protein correspondences are provided.

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