Schedule

CiML2015

NIPS 2015 CiML workshop [new: we have posted the slides below]

Saturday, December 12, 2015

Palais des Congrès de Montréal

Convention and Exhibition Center

Room 512 e [Floor map] Talk abstracts

Morning session (9:00 am-12:00 pm)

9:00 - Welcome and introduction. Evelyne Viegas [slides]

9:10 - Invited talk, Challenges in Medical Image Analysis: Comparison, Competition, Collaboration, Bram van Ginneken [slides]

9:50 - Break

10:20 - Invited talk, Techniques and Technologies for Efficient and Realistic Benchmarks: Examples from the MediaEval Multimedia Benchmark and CLEF NewsREEL, Martha Larson [slides]

11:00 - Discussion: Open Innovation, Balazs Kegl and Ben Hamner moderators [Balazs' post][Balazs' slides]

12:00 - Break

Break-out session on AutoML challenge.

12:30 - Presentation of the AutoML challenge. Isabelle Guyon -- Announcement of the new GPU track. [slides]

13:00 - Automated Machine Learning: Successes & Challenges. Frank Hutter. Team aaad_freiburg. First place AutoML1 phase, second place AutoML2 phase. [paper][supplementary material][slides]

13:30 - Sensible allocation of computation for ensemble construction. James Lloyd. Team jrl44/backstreet.bayes. First place AutoML2 phase, second place AutoML1 phase. [slides]

14:00 - Scalable ensemble learning with stochastic feature boosting. Eugene Tuv. Team ideal.intel.analytics. First place Final0 phase, second place Final1 phase. [slides]

14:30 - Break

Afternoon session (15:00-18:30)

15:00 - Invited talk, Lessons Learned from the PASCAL VOC Challenges, and Improving the Data Analytics Process, Chris Williams [slides]

15:40 - Discussion: Coopetitions, Evelyne Viegas and Isabelle Guyon moderator

16:40 - Break

17:00 - Contributed talk, Academic Torrents: Scalable Data Distribution, Henry Z. Lo and Joseph Paul Cohen [paper][slides]

17:30 - Open discussion, Michele Sebag modelator

18:20 - Wrap up

18:30 - Adjourn

CiML dinner
Eugene Tuv

Eugene Tuv

James Lloyd

James Lloyd

Chris Willians

Balazs Kegl

Joseph P. Cohen and Henry Z. Lo

Ben Hamner

Frank Hutter
Bram van Ginneken
Erick Watson

Frank Hutter

Bram van Ginneken

Erick Watson

Joseph, Henry & Sebastien Treger

Jaffray Woodriff & Bram

Balazs, John Platt & Chris

We are connected to the Bayesian Optimization workshop and the Black Box Learning and Inference workshop, because they both treat in some way the "Automatic Machine Learning" problem, which we will discuss during the lunch session.

We are grateful to our Committee for helping put this program together.