
Advances in Asynchronous Parallel and Distributed Optimization
Motivated by largescale optimization problems arising in the context of...
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Communication Efficient Sparsification for Large Scale Machine Learning
The increasing scale of distributed learning problems necessitates the d...
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Convergence of a Stochastic Gradient Method with Momentum for Nonsmooth Nonconvex Optimization
Stochastic gradient methods with momentum are widely used in application...
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Anderson Acceleration of Proximal Gradient Methods
Anderson acceleration is a wellestablished and simple technique for spe...
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Efficient Stochastic Programming in Julia
We present StochasticPrograms.jl, a userfriendly and powerful opensour...
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Noisy Accelerated Power Method for Eigenproblems with Applications
This paper introduces an efficient algorithm for finding the dominant ge...
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CurvatureExploiting Acceleration of Elastic Net Computations
This paper introduces an efficient secondorder method for solving the e...
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Harnessing the Power of Serverless Runtimes for LargeScale Optimization
The eventdriven and elastic nature of serverless runtimes makes them a ...
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POLO: a POLicybased Optimization library
We present POLO  a C++ library for largescale parallel optimization ...
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The Convergence of Sparsified Gradient Methods
Distributed training of massive machine learning models, in particular d...
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Distributed learning with compressed gradients
Asynchronous computation and gradient compression have emerged as two ke...
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Continuoustime Value Function Approximation in Reproducing Kernel Hilbert Spaces
Motivated by the success of reinforcement learning (RL) for discretetim...
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Analysis and Implementation of an Asynchronous Optimization Algorithm for the Parameter Server
This paper presents an asynchronous incremental aggregated gradient algo...
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An Asynchronous MiniBatch Algorithm for Regularized Stochastic Optimization
Minibatch optimization has proven to be a powerful paradigm for larges...
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Ergodic Mirror Descent
We generalize stochastic subgradient descent methods to situations in wh...
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Mikael Johansson
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