Daniel Evangelakos will guide us through High-Performance and Scalable Radix Sorting, by Duane Merrill and Andrew Grimshaw. Here, high performance is achieved by performing the sort on a GPU. You need not have read this paper to attend; all are welcome! Sorting is arguably the most common task… Continue reading »
If you would like to register for our fall 2015 independent research course, either to pursue a single-semester project or to begin research potentially leading to a thesis in the spring, please download and complete our fall research form. You must discuss possible projects with any faculty member you… Continue reading »
Google’s mission is to organize the world’s information and make it universally accessible and useful. It’s an enormous goal to accomplish and we need great people to help us achieve it! We invite you to come learn about Google and meet some of our Googlers at this exciting event! Who:… Continue reading »
Wednesday, November 5 in TCL 206 1:00 pm — Networking in the Light 1:15 pm — StudentLife App: A term in the life of a Dartmouth Class 1:35 pm — Q&A on Dartmouth as a place for graduate studies in CS This event will count as colloquium credit… Continue reading »
Saving the World with Computer Science? Williams College will be awarding Ethan Zuckerman a Bicentennial Medal during convocation this weekend. On September 19, while Ethan is on campus, he will be giving a talk in the Computer Science department. There will be a lunch reception in the Computer Science lounge… Continue reading »
The Computer Science Department’s Class of 1960 Scholars Lecture Series Thursday, September 18 at 8:00 pm in Wege Auditorium (TCL 123) Neural Representations of Language Meaning How does the human brain use neural activity to create and represent meanings of words, sentences and stories? One way to… Continue reading »
Students will be presenting their research on Monday, May 19 at 9:00 am in TCL 202. 9:00 am Daniel Seita – Building Sum-Product Networks Probabilistic inference is the process of determining the probability of an event given some evidence. While techniques based on probabilistic graphical models have… Continue reading »