
Communicationefficient SGD: From Local SGD to OneShot Averaging
We consider speeding up stochastic gradient descent (SGD) by parallelizi...
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Distributed TD(0) with Almost No Communication
We provide a new nonasymptotic analysis of distributed TD(0) with linea...
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Temporal Difference Learning as Gradient Splitting
Temporal difference learning with linear function approximation is a pop...
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Adversarial Crowdsourcing Through Robust RankOne Matrix Completion
We consider the problem of reconstructing a rankone matrix from a revea...
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Asymptotic Convergence Rate of Alternating Minimization for Rank One Matrix Completion
We study alternating minimization for matrix completion in the simplest ...
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Local SGD With a Communication Overhead Depending Only on the Number of Workers
We consider speeding up stochastic gradient descent (SGD) by parallelizi...
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Asymptotic Network Independence in Distributed Optimization for Machine Learning
We provide a discussion of several recent results which have overcome a ...
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A NonAsymptotic Analysis of Network Independence for Distributed Stochastic Gradient Descent
This paper is concerned with minimizing the average of n cost functions ...
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Gradient Descent for Sparse RankOne Matrix Completion for CrowdSourced Aggregation of Sparsely Interacting Workers
We consider worker skill estimation for the singlecoin DawidSkene crow...
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Graph Resistance and Learning from Pairwise Comparisons
We consider the problem of learning the qualities of a collection of ite...
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GraphTheoretic Analysis of Belief System Dynamics under Logic Constraints
Opinion formation cannot be modeled solely as an ideological deduction f...
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Network Topology and CommunicationComputation Tradeoffs in Decentralized Optimization
In decentralized optimization, nodes cooperate to minimize an overall ob...
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Improved Convergence Rates for Distributed Resource Allocation
In this paper, we develop a class of decentralized algorithms for solvin...
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Distributed Learning for Cooperative Inference
We study the problem of cooperative inference where a group of agents in...
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A Tutorial on Distributed (NonBayesian) Learning: Problem, Algorithms and Results
We overview some results on distributed learning with focus on a family ...
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Geometrically Convergent Distributed Optimization with Uncoordinated StepSizes
A recent algorithmic family for distributed optimization, DIGing's, have...
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Distributed Learning with Infinitely Many Hypotheses
We consider a distributed learning setup where a network of agents seque...
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