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Poster
Wed 11:00 Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm
Chelsea Finn · Sergey Levine
Workshop
Wed 11:00 AUTOMATED DESIGN USING NEURAL NETWORKS AND GRADIENT DESCENT
oliver hennigh
Poster
Wed 16:30 Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks
Pratik A Chaudhari · Stefano Soatto
Poster
Thu 16:30 A Bayesian Perspective on Generalization and Stochastic Gradient Descent
Samuel Smith · Quoc V Le
Poster
Thu 16:30 The Implicit Bias of Gradient Descent on Separable Data
Daniel Soudry · Elad Hoffer · Mor Shpigel Nacson · Nathan Srebro
Poster
Tue 9:00 Neural network gradient-based learning of black-box function interfaces
Alon Jacovi · guy hadash · Einat Kermany · Boaz Carmeli · Ofer Lavi · George M. Kour · Jonathan Berant
Poster
Wed 14:30 Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization
Navid Azizan · Babak Hassibi
Poster
Wed 14:30 Fluctuation-dissipation relations for stochastic gradient descent
Sho Yaida
Poster
Wed 14:30 Preconditioner on Matrix Lie Group for SGD
XI-LIN LI
Poster
Wed 14:30 Gradient descent aligns the layers of deep linear networks
Ziwei Ji · Matus Telgarsky
Poster
Wed 14:30 ANYTIME MINIBATCH: EXPLOITING STRAGGLERS IN ONLINE DISTRIBUTED OPTIMIZATION
Nuwan Ferdinand · Haider Al-Lawati · Stark Draper · Matthew Nokleby
Poster
Wed 14:30 Gradient Descent Provably Optimizes Over-parameterized Neural Networks
Simon Du · Xiyu Zhai · Barnabás Póczos · Aarti Singh