NIPS 2017

4 Program Highlights »

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Symposium

Thu Dec 7th 02:00 -- 09:30 PM @ Hall A

Deep Reinforcement Learning

Pieter Abbeel · Yan Duan · David Silver · Satinder Singh · Junhyuk Oh · Rein Houthooft

Mastering Games » Soft Actor-Critic » Active Neural Localization » NLP Search » Reproducibility » Backprop thru Void » Parameter Space Noise » Time-Contrastive » Neural Map » Variance Reduction » Sample-efficient Policy Optimization » One-Shot Visual Imitation » Deep Exploration » StarCraft II » Neural Network Dynamics » Overcoming Exploration in RL »

Symposium

Thu Dec 7th 02:00 -- 09:30 PM @ Hall C

Interpretable Machine Learning

Andrew G Wilson · Jason Yosinski · Patrice Simard · Rich Caruana · William Herlands

Opening Remarks » Masked Autoregressive » Deep Sets » David Bayesian Sparsity » Causality for Interpretability » Interpretable Discovery » Spotlight talks » Explainablity challenge » Cost of Calibration » Panel 1 » Interpretability for AI safety » Manipulating and Measuring Model Interpretability. » Debugging the ML Pipeline. » Panel 2 »

Symposium

Thu Dec 7th 02:00 -- 09:30 PM @ Beverly Theater

Kinds of intelligence: types, tests and meeting the needs of society

José Hernández-Orallo · Zoubin Ghahramani · Tomaso A Poggio · Adrian Weller · Matthew Crosby

Opening Remarks » Why the mind evolved » Distinctive intelligence of children » Learning from first principles » Panel 1 » Types of Intelligence » Artifical General Intelligence » Video games and collaborative AI » Panel 2 »

Symposium

Thu Dec 7th 02:00 -- 09:30 PM @ Grand Ballroom

Metalearning

Risto Miikkulainen · Quoc V Le · Kenneth Stanley · Chrisantha Fernando

Opening » Evolving Multitask » Evolving to Learning » PathNet » Bayesian Opt » AutoML » Contrasting Model » Population-based Training » Learning to Learn » Learning Strategies » Intrinsically Motivated RL » Self-Play » Neural Architecture Search » Multiple scales » Panel »

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