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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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Thu 9:00
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Deconstructing the Regularization of BatchNorm
Yann Dauphin · Ekin Cubuk
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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 17:00
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Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Colin Wei · Kendrick Shen · Yining Chen · Tengyu Ma
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Oral
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Thu 19:00
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Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Colin Wei · Kendrick Shen · Yining Chen · Tengyu Ma
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Spotlight
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Mon 21:56
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Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning
Dong Bok Lee · Dongchan Min · Seanie Lee · Sung Ju Hwang
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Poster
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Tue 1:00
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BOIL: Towards Representation Change for Few-shot Learning
Jaehoon Oh · Hyungjun Yoo · ChangHwan Kim · Se-Young Yun
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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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Poster
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Thu 17:00
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Neural Thompson Sampling
Weitong ZHANG · Dongruo Zhou · Lihong Li · Quanquan Gu
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Workshop
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Fri 5:15
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Geometric Deep Learning
Fernando Gama
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Workshop
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Fri 11:52
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DeepSMOTE: Deep Learning for Imbalanced Data
Bartosz Krawczyk
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