Invalid quantity. Please enter a quantity of 1 or more.
The quantity you chose exceeds the quantity available.
Please enter your name.
Please enter an email address.
Please enter a valid email address.
Please enter your message or comments.
Please enter the code as shown on the image.
Please select the date you would like to attend.
Please enter an email address.
Please enter a valid email address in the To: field.
Please enter a subject for your message.
Please enter a message.
You can only send this invitations to 10 email addresses at a time.
$$$$ is not a properly formatted color. Please use the format #RRGGBB for all colors.
Please limit your message to $$$$ characters. There are currently ££££.
$$$$ is not a valid email address.
Please enter a promotional code.
N/A
Sold Out
Pending
You have exceeded the time limit and your reservation has been released.
The purpose of this time limit is to ensure that registration is available to as many people as possible. We apologize for the inconvenience.
This is option is not available anymore. Please choose a different option.
Please read and accept the waiver.
All fields marked with * are required.
Please double check your email address. The email address format does not appear valid.
$$$$ requires a number between ££££ and §§§§
US Zipcodes need to be 5 digits.
Please double check your website URL.
All fields marked with * are required.
Your credit card expiration date is in the past.
Your credit card CSC needs to be 4 digits.
Please confirm your order:
$$$$
You have selected to Pay by Check.
Click OK to confirm your order.
Please confirm your order:
$$$$
You have selected to Pay at the Door.
Click OK to confirm your order.
Please confirm your order:
$$$$
You have selected to Pay upon Receiving an Invoice.
Click OK to confirm your order.
Your credit card CSC needs to be 3 digits.
Your billing zip code needs to be 5 digits.
There was a problem saving your address.
There was a problem saving your credit card info.
There was a problem saving your personal information.
Please select the date you would like to attend.
McAfee Secure sites help keep you safe from identity theft, credit card fraud, spyware, spam, viruses and online scams.
Copying Prohibited by Law - McAfee Secure is a Trademark of McAfee, Inc.
Unknown card type.
No card number provided.
Credit card number is in invalid format.
Wrong card type or credit card number is invalid.
Credit card number has an inappropriate number of digits.
Please enter numbers here.
Please enter an integer value.
Numbers must be less or equal to $$$$
All the required fields have not been filled out. Click OK to proceed without all the required information, or click Cancel to finish entering the missing data.
Sorry, invalid event registration form.
Sorry, invalid event or database error.
Sorry, quantity must be a positive integer.
Sorry, you did not select a valid ticket.
Sorry, invalid event organizer email address.
Your order was canceled.
Thank You. Your order has been successfully completed. Your name and email address have been added to the list of event attendees.
Sorry, that option is sold out.
Sorry, that option is no longer available.
Sorry, there are only tickets of that type still available.
Sorry, you entered an invalid quantity. Please enter a quantity of 1 or more next to the type or types of tickets you would like to purchase.
Sorry, you did not select any tickets to purchase. Please enter a quantity of 1 or more next to the type or types of tickets you would like to purchase.
Sorry, there are no tickets left for this event.
The tickets, ticket quantity or date and time you've requested are no longer available, due to previous sales. Please choose a different date, time or number of tickets and place your order again.
Sorry, one or more of the tickets you requested are no longer available for purchase.
Sorry, you need to select the date you want to attend.
Sorry, the promotional code you entered is not valid yet.
Sorry, the promotional code you entered has expired.
Sorry, the promotional code you entered is not valid.
Your session has expired. Try ordering again.
Sorry, your requested ticket quantity exceeds the number provided by your promotional code.
Sorry, the tickets you are trying to order are not currently available.
Sorry, the payment type chosen is invalid for this event.
Sorry, there is only 1 ticket left for this event.
Sorry, there are only tickets left for this event.
We're sorry, this invitation is invalid.
We're sorry, this invitation has already been used.
We're sorry, you already have an order being processed for this event. Please wait a few minutes and try again.
We're sorry, there is a problem with your invitation. Please try again.
Invalid quantity of tickets selected.
Invalid donation amount.
Sorry, the promotional code you entered has been claimed.
Sorry, the payment type chosen is invalid for this event.
Sorry, your billing address was not saved properly, please try again.
Sorry, we experienced an internal error, please try again.
The captcha you entered is invalid. Please try again.
Invalid credit card selected. You have been logged out.
Sorry, your team selection was not valid.
Sorry, the payment type chosen is invalid for this event.
Sorry, your billing address was not saved properly, please try again.
Sorry, we experienced an internal error, please try again.
State
Zip Code
Province
Postal Code
County
State/Territory
State/Province
Event Details
MLconf presents:
Join us on Monday, July 9th in San Francisco for a full-day workshop on Large Scale Machine Learning. Featuring CMU's Graphlab and including presentations from Twitter, Pandora, Netflix, Intel Labs, IBM Watson, MapR, and many more. Follow @MLconf for updates, discounts and free tickets!
The Big Learning Workshop is a meeting place for both academia and industry to discuss upcoming challenges of large scale machine learning and solution methods. The workshop will include demos and tutorials showcasing the next generation of the GraphLab framework, as well as lectures and demos from the top technology companies about their applied large scale machine learning solutions.
Event Details
Schedule:
- 8am - 9am: Registration & Contintental Breakfast
- 9am - Presentations begin (See agenda below)
- 5pm - 7pm Networking with hosted bar / appetizers
Parking:
Click here for a complete list of nearby parking.
Resturants near the event
Agenda:
| Time | Session | Talk title (and length) | Speaker |
|---|
| 08:00 – 09:00 |
Reception |
Reception and continental breakfast |
|
| 09:00 – 10:30 |
Morning session |
GraphLab Version 2 Overview (60 mins) |
Carlos Guestrin |
| |
|
Large scale ML challenges (30 mins) |
Theodore Willke, Intel Labs |
| 10:30 – 10:50 |
Break |
|
|
| 10:50 – 12:20 |
Late morning session |
Bloom: Disorderly Programming for Distributed Systems (30 mins) |
Joseph Hellerstein, UC Berkeley |
| |
|
Schism: Graph Partitioning for Scalable Query Processing on Large OLTP Databases (30 mins) |
Sam Madden – MIT |
| |
|
Visualization and Interactive Data Analysis (30 mins) |
Jeffrey Heer, Stanford |
| 12:20 – 13:50 |
Lunch Break |
|
|
| 13:40 – 14:55 |
Afternoon session |
The Parameter Servrer (30 Mins) |
Alexander Smola, Yahoo! Labs |
| |
|
Vowpal Wabbit for Extremely Fast Machine Learning (15 mins) |
Lihong Li, Yahoo! Research |
| |
|
Cassovary Graph Processing System (15 mins) |
Pankaj Gupta, Twitter |
| |
|
Tera-scale deep learning (15 mins) |
Quoc Le, Stanford |
| 14:55 – 15:15 |
Break |
|
|
| 15:15 – 17:10 |
Late afternoon session |
Identifying densely overlapping clusters in large networks |
Jure Leskovec, Stanford |
| |
|
Large-scale Single-pass k-Means Clustering at Scale (30 mins) |
Ted Dunning, MapR Technologies |
| |
|
Recommendations @Netflix: Big Data, Smart Models & Scalable Systems (15 mins) |
Xavier Amatriain - Netflix |
| |
|
Large scale ML at Pandora (15 mins) |
Tao Ye, Pandora Internet Radio |
| |
|
NIMBLE - A toolkit for the implementation of parallel data mining and machine learning algorithms on Map-Reduce (15 mins) |
Amol Gothing, IBM Watson |
| |
|
Machine learning in One Kings Lane (5 mins) |
Mohit Singh, One Kings Lane |
| 17:10 – 19:00 |
Poster/demo session |
See detailed list below |
|
Posters/Demos
- Green Marl graph processing framework – Sungpack Hong, Oracle Labs
- Machine learning benchmark framework – Nicholas Kolegraff, Accenture
- TBD -Alexander Gray, Georgia Tech
- Alpine and MADLib Demo – Steven Hilion, Alpine Data Labs
- Disk-based Massive Graph Computation – Aapo Kyrola, CMU
- Titan: A Highly Scalable, Distributed Graph Database - Matthias Broecheler, Aurelius
- Distributed Active Graph Platform, Andrey Logvinov, Meralabs LLC
- Health Insights in Real-Time. Adam Sadilek, Andrew Abumoussa, Sean Brennan, Henry Kautz University of Rochester
- YarcData graph analytics contest, Monte LaBute, YarcData
Signup for email updates, sponsor and speaker information, discount codes and free tickets!
Platinum Sponsor
Gold Sponsors
Bronze Sponsors
Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries. All other logos are trademarks of the companies who own them, respectivley.
For more Machine Learning events see mlconf.com and follow @mlconf on twitter.
Attendee List
Sort by: Date
When & Where
50 Third Street
San Francisco,
94103
Monday, July 9, 2012 from 8:00 AM to 7:00 PM (PDT)
Add to my calendar
In order to purchase these tickets in installments, you'll need an Eventbrite account. Log in or sign up for a free account to continue.
