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Poster
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Mon 9:00 |
PAC Confidence Predictions for Deep Neural Network Classifiers Sangdon Park · Shuo Li · Insup Lee · Osbert Bastani |
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Poster
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Thu 9:00 |
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning Kanil Patel · William H Beluch · Bin Yang · Michael Pfeiffer · Dan Zhang |
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Poster
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Thu 17:00 |
Representing Partial Programs with Blended Abstract Semantics Maxwell Nye · Yewen Pu · Matthew Bowers · Jacob Andreas · Joshua B Tenenbaum · Armando Solar-Lezama |
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Oral
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Thu 0:30 |
Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime Atsushi Nitanda · Taiji Suzuki |
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Workshop
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Fri 6:00 |
Keynote 3: Ehsan Saboori. Title: Deep learning model compression using neural network design space exploration |
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Poster
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Wed 17:00 |
Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs Zhen Han · Peng Chen · Yunpu Ma · Volker Tresp |
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Oral
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Mon 11:00 |
Federated Learning Based on Dynamic Regularization Durmus Alp Emre Acar · Yue Zhao · Ramon Matas · Matthew Mattina · Paul Whatmough · Venkatesh Saligrama |
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Oral
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Tue 11:00 |
Iterated learning for emergent systematicity in VQA Ankit Vani · Max Schwarzer · Yuchen Lu · Eeshan Dhekane · Aaron Courville |
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Poster
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Wed 1:00 |
Fooling a Complete Neural Network Verifier Dániel Zombori · Balázs Bánhelyi · Tibor Csendes · István Megyeri · Márk Jelasity |
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Poster
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Thu 9:00 |
Enforcing robust control guarantees within neural network policies Priya Donti · Melrose Roderick · Mahyar Fazlyab · Zico Kolter |
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Poster
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Thu 9:00 |
Deconstructing the Regularization of BatchNorm Yann Dauphin · Ekin Cubuk |
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Poster
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Mon 1:00 |
Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits Jiawang Bai · Baoyuan Wu · Yong Zhang · Yiming Li · Zhifeng Li · Shu-Tao Xia |