# Graduate Seminar

A seminar organized by/for the graduate students.

## April 2017

### Grad Student Seminar: Hyungsuk Tak, SAMSI

Hyungsuk Tak SAMSI Bayesian Estimates of Astronomical Time Delays between Gravitationally Lensed Stochastic Light Curves The gravitational field of a galaxy can act as a lens and deflect the light emitted by a more distant object such as a quasar. Strong gravitational lensing causes multiple images of the same quasar to appear in the sky. Since the light in each gravitationally lensed image traverses a different path length from the quasar to the Earth, fluctuations in the source brightness are…

Find out more »## August 2017

### Grad Seminar: Wanyi Chen, Eric Friedlander

Wanyi Chen Dynamic Decision Making In A Queueing System With Secondary Service Motivated by operational practices in emergency departments, we consider a queueing model where each job is one of two types. Type 1 jobs need only a primary service given by a single server. Type 2 jobs need an additional secondary service. Secondary service is conducted by infinitely many servers. Primary servers cannot serve a new job until secondary service of a job is over. Jobs incur waiting costs…

Find out more »## September 2017

### Grad Student Seminar: Jianyu Liu and Zhengling Qi

Jianyu Liu Joint Skeleton Estimation of Multiple Directed Acyclic Graphs for Heterogeneous Population The directed acyclic graph (DAG) is a powerful tool to model the interactions of high-dimensional variables. While estimating edge directions in a DAG often requires interventional data, one can estimate the skeleton of a DAG (i.e., an undirected graph formed by removing the direction of each edge in a DAG) using observational data. In real data analyses, the samples of the high-dimensional variables may be collected from…

Find out more »### Grad Student Seminar: Tianxiao Sun & Jonathan Williams

Tianxiao Sun Globally convergent Newton-type methods for convex optimization based on smoothness structures We study the smooth structure of convex functions by generalizing a powerful concept so-called self-concordance introduced by Nesterov and Nemirovskii to a broader class of convex functions. The proposed theory provides a mathematical tool to analyze both local and global convergence of Newton-type methods as long as the underlying functionals fall into our generalized self-concordant function class. First, we introduce the class of generalized self-concordant functions, which…

Find out more »## October 2017

### Grad Student Seminar: Siliang Gong & Leo Liu

Siliang Gong (Joint work with Kai Zhang and Yufeng Liu) Penalized linear regression with high-dimensional pairwise screening In variable selection, most existing screening methods focus on marginal e ects and ignore dependence between covariates. To improve the performance of selection, we incorporate pairwise e ects in covariates for screening and penalization. We achieve this by studying the asymptotic distribution of the maximal absolute pairwise sample correlation among independent covariates. The novelty of the theory is in that the convergence is…

Find out more »## November 2017

### Grad Student Seminar: Gabor Pataki, Bryan Davis

Gabor Pataki UNC-Chapel Hill Bad semidefinite programs with short proofs, and elementary linear algebra Semidefinite programs (SDPs) – optimization problems with linear constraints, linear objective, and semidefinite matrix variables – are some of the most useful, versatile, and pervasive optimization problems to emerge in the last 30 years. They find applications in combinatorial optimization, machine learning, and statistics, to name just a few areas. Unfortunately, SDPs often behave pathologically: the optimal values of the primal and dual problems may differ…

Find out more »### Grad Student Seminar: Yifan Cui and Melody Zhu

Yifan Cui Some asymptotic results of survival tree and forest models We develop atheoretical framework and asymptotic results for survival tree and forest models under right censoring. We first investigate the method from the aspect of splitting rules, where the survival curves of the two potential child nodes are calculated and compared. We show that existing approaches lead to a potentially biased estimation of the within-node survival and cause non-optimal selection of the splitting rules. This bias is due to…

Find out more »## February 2018

### Grad Student Seminar: Danianne Mizzy and Lorin Bruckner

How Can the Library Help You? Lorin Bruckner will present on data visualization and numeric data services and tools available to you through UNC Libraries. Danianne Mizzy will present about citation & reputation management tools.

Find out more »### Grad Student Seminar: Meilei Jiang

Angle-based Joint and Individual Variation Explained Integrative analysis of disparate data blocks measured on a common set of experimental subjects is a major challenge in modern data analysis. This data structure naturally motivates the simultaneous exploration of the joint and individual variation within each data block resulting in new insights. For instance, there is a strong desire to integrate the multiple genomic data sets in The Cancer Genome Atlas to characterize the common and also the unique aspects of…

Find out more »## April 2018

### Grad Student Seminar: Eric Friedlander

Eric Friedlander UNC-Chapel Hill Joint Image and Genomic Analysis for Breast Cancer Current clinical practice for the diagnosis of cancer is through biopsies with pathology reviews. More recently genomic data has been used for a refined diagnosis and in particular for tumor classification to enable patient-specific treatment and improved long-term disease prognosis. In an ongoing collaboration with researchers in the Computer Science Department and Lineberger Collaborative Cancer Center we are working to improve prognosis by combining both…

Find out more »