Program

Draft Version

Workshops

Deep Reinforcement Learning and Robotics (Thursday, January 3)
Raia Hadsell, Google DeepMind, Nicolas Heess, Google DeepMind, Pulkit Agrawal, UC Berkeley, Tuomas Haarnoja, UC Berkeley
Room: Owl & Eagle Suite
Fairness and Transparency in Machine Learning (Thursday, January 3)
Moustapha Cisse, Google AI, Vukosi Marivate, University of Pretoria/CSIR
Room: Kingfisher Suite
Optimization (Thursday, January 3)
Simon Lacoste-Julien, U of Montreal
Room: Grey & Knysna Suite
Healthcare in Machine Learning (Saturday, January 5)
Danielle Belgrave, Microsoft Research
Room: Owl & Eagle Suite
Security and Robustness (Saturday, January 5)
Pushmeet Kohli, DeepMind, Krishnamurthy Dvijotham, DeepMind, Adrian Weller, Turing Institute
Room: Kingfisher Suite
Machine Learning Theory (Saturday, January 5)
Samory Kpotufe, Princeton University, Ilya Tolstikhin, Google
Room: Grey & Knysna Suite

Full Schedule

Day 0 January 2 (Wednesday)

Registration and Arrival

19:30 Conference Opening & Welcoming Cocktail

Activities for family members (10:30-17:00h)

09:30- 11:00 Morning Session 1

Coffee Break

11:30- 13:00 Morning Session 2

Lunch Break

17:00- 19:00 Afternoon Session

19:00- 20:00 Debate (Plenary Session)

20:00 Dinner (attendees to self-organise)

Day 2 January 4 (Friday)

Single track symposium

09:30- 10:10 Keynote 1: Data Science Africa - Lessons from a grassroots initiative Ciira wa Maina, Dedan Kimathi University of Technology

10:15- 10:55 Keynote 2: Statistical and machine learning challenges from genetics to CRISPR gene editing Jennifer Listgarten, University of California, Berkeley

11:00- 13:00 Coffee Break and Posters

Lunch and Excursion

19:00- 19:40 Keynote 3: Stein’s Method, Inference, and Learning (SMILE) Lester Mackey, Microsoft Research

20:00 Conference Banquet

Day 3 January 5 (Saturday)

Workshops Day