
Symmetry Breaking in Symmetric Tensor Decomposition
In this note, we consider the optimization problem associated with compu...
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Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry
We consider the optimization problem associated with fitting twolayers ...
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SecondOrder Information in NonConvex Stochastic Optimization: Power and Limitations
We design an algorithm which finds an ϵapproximate stationary point (wi...
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IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method
We introduce a framework for designing primal methods under the decentra...
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Symmetry critical points for a model shallow neural network
A detailed analysis is given of a family of critical points determining ...
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On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions
Recent advances in randomized incremental methods for minimizing Lsmoot...
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Spurious Local Minima of Shallow ReLU Networks Conform with the Symmetry of the Target Model
We consider the optimization problem associated with fitting twolayer R...
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Lower Bounds for NonConvex Stochastic Optimization
We lower bound the complexity of finding ϵstationary points (with gradi...
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A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates
We provide tight finitetime convergence bounds for gradient descent and...
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Limitations on VarianceReduction and Acceleration Schemes for Finite Sum Optimization
We study the conditions under which one is able to efficiently apply var...
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Oracle Complexity of SecondOrder Methods for FiniteSum Problems
Finitesum optimization problems are ubiquitous in machine learning, and...
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Communication Complexity of Distributed Convex Learning and Optimization
We study the fundamental limits to communicationefficient distributed m...
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Yossi Arjevani
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