Risk Classification in High Dimensional Survival Models Date: Monday, November 21, 2016 Place: 052 Tyler Hall Time: 11:00 a.m. Sparse regression models are an actively burgeoning area of statistical learning research. A subset of these models seek to separate out significant and non-trivial main effects from noise effects within the regression framework (yielding so-called “sparse”(…)
News and Announcements
NETWORK-BASED STATISTICAL METHODS FOR THE ANALYSIS OF STOCK RETURNS Date: Monday, November 21, 2016 Place: 049 Tyler Hall Time: 9:00 a.m. To maximize returns and diversify portfolios, the stock price market participants have always been interested in learning associations of stock price returns for different companies. Five primary goals of this thesis are: (1) to(…)
The Computing Research Association would like to encourage graduate students from The University of Rhode Island to participate in a skill-building and mentoring workshop specifically for women in computing. All travel expenses are reimbursed for this workshop. The upcoming CRA-Women Graduate Student Cohort (Grad Cohort) will be held April 7-8, 2017 in Washington, D.C. The(…)
Crowdsourcing Deep Thoughts: Meeting the Challenges of In-depth Language Understanding Systems for Smarter Social Media
Speaker: Jamie Macbeth Speaker Affiliation: School of Engineering, Fairfield University Date: Friday, November 18, 2016 Time: 2:00 PM to 3:00 PM Location: CBLS 152 Intelligent systems driven by natural language input are well-positioned to meet the challenges of intervening against abuses of social media (such as cyberbullying) and providing resources for victims. However, the language(…)
CSC392 Section 02 Dr. Lutz Hamel Programming for Data Science Spring 2017, T&Th 12:30-1:45PM Data science exists at the intersection of computer science, statistics, and machine learning. That means writing programs to access and manipulate data so that it becomes available for analysis using statistical and machine learning techniques is at the core of data(…)
CSC 592 Prof. Noah Daniels Algorithms for Big Data Spring 2017, T&Th 2:30-3:15 In this project-oriented course, we will explore algorithms for large data sets, including data sources that are growing faster than Moore’s Law. Topics will include sketching and streaming algorithms, randomized polynomial-time approximation schemes and their error bounds, compressive acceleration, and other(…)
Speaker: Alexandr Kodess, URI Time: Friday, October 21, 1-2pm, Lippitt 204 See http://www.math.uri.edu/~thoma/dmg/dmg.html for further information and updates.
Applied Mathematics and Scientific Computing Seminar Dr. Noah Daniels Dept. of Computer Science & Statistics, URI Abstract: Recent technological improvements have increased the scale and content of data produced across a variety of fields, from astronomy and biology to global trade and social networks. In many cases, the scale, richness, and noise of the data(…)
Dr. Ying Zhang, Department of Cell and Molecular Biology • Time: Tuesdays & Thursdays @ 11am-12:15pm; • Location: Tyler Hall 053 • Credits: 3 Have you heard of the Human Genome Project? How can a drug target be identified? What is responsible for maintaining the health of our own body and the natural environment? Recent(…)
Data science exists at the intersection of computer science, statistics, and machine
learning. That means writing programs to access and manipulate data so that it becomes
available for analysis using statistical and machine learning techniques is at the core of
data science. This course is offered in Spring 2017 Tuesdaya and Thursday from 12:30PM to 1:45PM.
For further details please contact Dr. Lutz Hamel: firstname.lastname@example.org