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Workshop
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Fri 10:05
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Q&A for Inference Risks for Machine Learning
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Workshop
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Fri 7:10
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Poster Spotlight "Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure"
Zhijie Deng
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Workshop
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Fri 7:00
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2nd Workshop on Practical ML for Developing Countries: Learning Under Limited/low Resource Scenarios
Esube Bekele · Waheeda Saib · Timnit Gebru · Meareg Hailemariam · Vukosi Marivate · Judy Gichoya
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Workshop
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Fri 14:02
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Invited Talk: A deep learning theory for neural networks grounded in physics
Benjamin Scellier
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Poster
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Mon 17:00
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Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
Junwen Bai · Weiran Wang · Yingbo Zhou · Caiming Xiong
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Workshop
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Fri 6:30
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Intro: Reasoning with Deep Learning Architectures Based on System 2 Inductive Biases
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Poster
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Tue 1:00
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Scaling the Convex Barrier with Active Sets
Alessandro De Palma · Harkirat Singh Behl · Rudy R Bunel · Philip Torr · M. Pawan Kumar
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Workshop
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On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning
Marc Vischer · Henning Sprekeler · Robert Lange
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Workshop
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Fri 11:40
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Deep Kernels with Probabilistic Embeddings for Small-Data Learning
Ankur Mallick
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Poster
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Thu 17:00
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Adapting to Reward Progressivity via Spectral Reinforcement Learning
Michael Dann · John Thangarajah
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Poster
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Thu 9:00
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Deconstructing the Regularization of BatchNorm
Yann Dauphin · Ekin Cubuk
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Workshop
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Fri 11:00
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Keynote 6: Liangwei Ge. Title: Deep learning challenges and how Intel is addressing them
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