13:00
Lieu: Microsoft Research Cambridge
Hoda Heidari – What can Fair ML learn from Economic Theories of Disruptive Justice? (opens in new tab)
Finale Doshi-Velez – Interpretability in Machine Learning: What it means, How we’re getting there. (opens in new tab)
Francis Bach – Optimal Algorithms for smooth and strongly convex distributed optimization in networks (opens in new tab)
Andreas Geiger – Probabilistic and Deep Models for 3D Reconstruction (opens in new tab)
Francesco Orabona – Coin Betting for Backprop without Learning rates and More
Regina Barzilay – How Can NLP Help Cure Cancer? (opens in new tab)
Aapo Hyvarinen – Nonlinear ICA using temporal structure: a principled framework for unsupervised deep learning
Max Welling – Generalizing Convolutions for Deep Learning
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