Schedule

Dec 8

Thursday

Dec 9

Friday

10:00

Bernhard Schölkopf
Inference of Cause and Effect

10:40

Alexandr Tsybakov
Optimal Exponential Bounds for the Accuracy of Classification

11:20

Bob Williamson
Theory of Loss Functions

12:00

Lunch (Max Planck Haus)

13:30

Alex Smola
The Mean Trick

14:10

Vladimir Vapnik
Talk

15:30

Free time (e.g., Christmas Market)

19:00

Dinner (downtown)
Larry Jäckel: Machine Learning Applications at Bell Labs: Before and After the Arrival of Vladimir Vapnik

Dec 10

Saturday

10:00

Naftali Tishby
Kernel Information Bottleneck

10:40

Olivier Chapelle
Click Modeling for Display Advertising

11:20

Masashi Sugiyama
Density Ratio Estimatino: A New Versatile Tool for Machine Learning

12:00

Lunch (Max Planck Haus)

13:30

Koji Tsuda
Fast Graph Search with Succinct Trees

14:10

Gunnar Raetsch
Transfer Learning in Computational Biology

14:50

Olivier Bousquet
Shattering and Compression

15:30

Break

16:00

Andre Elisseeff
Two Statistical Challenges in Medical Applications

16:30

Joaquin Quiñonero Candela
Click Prediction in Computational Advertising

17:00

Mingmin Chi
Chinese Stock Mining via Topic Models

17:30

Matthew Blaschko
Ranking and Structured Output Prediction

18:00

Poster Session

19:00

Dinner (Max Planck Haus)