Reliable ML in the Wild – NIPS 2016 Workshop

NIPS 2016 워크샵에서 관심을 많이 받았던 것 중에 하나인 ‘Reliable Machine Learning in the Wild‘의 동영상이 워크샵 스케줄 페이지에 링크되었습니다. 비디오가 공개된 것만 추려보았습니다. 비디오는 wmv 파일로 스트링이 아니고 다운로드입니다. 전체 동영상을 한꺼번에 받으시려면 여기에서 전체 목록을 쉽게 확인할 수 있습니다. 동영상외에 전체 자료는 워크샵 스케줄 페이지를 확인하세요.

8:40Opening Remarks (video)

Session 1: New Challenges in Machine Learning

9:00 – Invited talk: Rules for Reliable Machine Learning. Martin Zinkevich (video)

9:30 – Contributed talk: What’s your ML Test Score? A rubric for ML production systems. Eric Breck, Shanqing Cai, Eric Nielsen, Michael Salib, D. Sculley (slides) (video)

9:45 – Poster spotlights (video)

Session 2: Robustness to Model Mis-specification

10:30 – Invited talk: Robust Learning and Inference. Yishay Mansour (video)

11:00 – Invited talk: Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition. Jennifer Hill (video)

11:30 – Contributed talk: Robust Covariate Shift Classification Using Multiple Feature Views. Anqi Liu, Hong Wang Brian D. Ziebart (video)

11:45 – Poster spotlights (video)

Session 3: Machine Learning and Security

1:30 – Contributed talk: Learning from Untrusted DataMoses Charikar, Jacob Steinhardt, Gregory Valiant (slides) (video)

1:45 – Invited talk: Adversarial Examples and Adversarial Training. Ian Goodfellow (video)

2:15 – Contributed talk: Summoning Demons: The Pursuit of Exploitable Bugs in Machine Learning. Rock Stevens, Octavian Suciu, Andrew Ruef, Sanghyun Hong, Michael Hicks, Tudor Dumitras (slides) (video)

2:30 – Poster spotlights (video)

Session 4: Reliable Robotics in Complex Environments

3:30 – Invited talk: Learning Reliable Objectives. Anca Dragan (video)

Session 5: Reliable Machine Learning in Practice

4:30 – Contributed talk: Online Prediction with Selfish Experts. Okke Schrijvers (video)

4:45 – Contributed talk: TensorFlow Debugger: Debugging Dataflow Graphs for Machine Learning. Shanqing Cai, Eric Breck, Eric Nielsen, Michael Salib, D. Sculley (slides) (video)

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