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Poster
Thu 9:00 Meta-Learning of Structured Task Distributions in Humans and Machines
Sreejan Kumar · Ishita Dasgupta · Jonathan Cohen · Nathaniel Daw · Thomas L Griffiths
Poster
Mon 1:00 Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets
Hayeon Lee · Eunyoung Hyung · Sung Ju Hwang
Poster
Mon 1:00 Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
Xinyue Chen · Che Wang · Zijian Zhou · Keith Ross
Poster
Wed 17:00 Protecting DNNs from Theft using an Ensemble of Diverse Models
Sanjay Kariyappa · Atul Prakash · Moinuddin K Qureshi
Workshop
Fri 5:00 Keynote 1: Warren Gross. Title: Stochastic Computing for Machine Learning towards an Intelligent Edge
Poster
Tue 17:00 Information Laundering for Model Privacy
Xinran Wang · Yu Xiang · Jun Gao · Jie Ding
Workshop
Fri 14:01 Contributed Talk 3 - Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
Curtis G Northcutt
Poster
Tue 9:00 Large Associative Memory Problem in Neurobiology and Machine Learning
Dmitry Krotov · John J Hopfield
Poster
Wed 1:00 New Bounds For Distributed Mean Estimation and Variance Reduction
Peter Davies · Vijaykrishna Gurunathan · Niusha Moshrefi · Saleh Ashkboos · Dan Alistarh
Poster
Mon 1:00 Isometric Transformation Invariant and Equivariant Graph Convolutional Networks
Masanobu Horie · Naoki Morita · Toshiaki Hishinuma · Yu Ihara · Naoto Mitsume
Workshop
Fri 9:40 Inference Risks for Machine Learning
David Evans
Spotlight
Mon 20:48 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini · Mohammad Yaghini · Nicolas Papernot