CS545:
Stanford InfoSeminar
Winter 2014
Infoseminar is a weekly event held at Stanford that brings together people who are interested
databases, big data and other interesting computer science topics.
Logistics
- Time and place: Fridays 4:15-5:15pm in the Hewlett building room 201, ten talks from January 10th through March 14th.
- Mailing list: To be added to the seminar mailing list, send your name, affiliation, and preferred mailing address to Marianne Siroker.
- Enrolled students: Students enrolled in the seminar as CS545 must attend 8 of the 10 scheduled lectures to pass the course, no make-ups permitted.
- Directions and parking: The good news is that most parking on campus is unregulated after 4:00pm.
- Attendance is open. Everyone is welcome to come to the lectures without any registration.
Organization
The Stanford InfoSeminar is held during the winter quarter only. It is organized by
Jure Leskovec and sponsored by the
Stanford Computer Forum.
Schedule
| Date |
Speaker |
Title (link to abstract) |
Bio |
Slides |
| Jan 10 2014 |
Xavier Amatriain, Netflix |
Behind the Curtain: Data & Algorithms that power the Netflix User Experience |
bio |
slides |
| Jan 17 2014 |
Lise Getoor, UCSC |
Scalable Collective Inference in Heterogenous Networks using PSL |
bio |
slides |
| Jan 24 2014 |
Andy Pavlo, CMU |
Cache Rules Everything Around Me |
bio |
|
| Jan 31 2014 |
Doug Cutting, Cloudera |
Data Software: Design for Change |
bio |
|
| Feb 7 2014 |
Julian McAuley, Stanford |
Machine Learning for Social Systems: Modeling Opinions, Activities, and Interactions |
bio |
|
| Feb 14 2014 |
Andreas Krause, ETH |
Learning with the Crowd: Detection, Clustering and Teaching |
bio |
|
| Feb 21 2014 |
Anil K Goel, SAP
Shel Finkelstein, SAP
|
SAP HANA: Delivering A Data Platform for Enterprise Applications on Modern Hardware |
bio
bio
|
slides |
| Feb 28 2014 |
Raghu Ramakrishnan, MSR |
Scale-Out Beyond Map-Reduce |
bio |
|
| Mar 7 2014 |
Ravi Kumar, Google Research |
Estimating Network Parameters |
|
|
| Mar 14 2014 |
Carlos Guestrin, UW |
Scalability, Data Distribution and Usability of Machine Learning with GraphLab |
bio |
|
