Distributed Subgradient Methods for Multi-Agent Optimization von Nedic, A., Ozdaglar, A.

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Why random reshuffling beats stochastic gradient descent von Gürbüzbalaban, M., Ozdaglar, A., Parrilo, P. A.

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On Distributed Averaging Algorithms and Quantization Effects von Nedic, A., Olshevsky, A., Ozdaglar, A., Tsitsiklis, J.N.

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Constrained Consensus and Optimization in Multi-Agent Networks von Nedic, A., Ozdaglar, A., Parrilo, P.A.

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On the Convergence Rate of Incremental Aggregated Gradient Algorithms von Gürbüzbalaban, M., Ozdaglar, A., Parrilo, P. A.

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Subgradient Methods for Saddle-Point Problems von Nedić, A., Ozdaglar, A.

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Global Convergence Rate of Proximal Incremental Aggregated Gradient Methods von Vanli, N. D., Gürbüzbalaban, M., Ozdaglar, A.

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Subgradient Methods for Saddle-Point Problems von NEDIE, A, OZDAGLAR, A

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A globally convergent incremental Newton method von Gürbüzbalaban, M., Ozdaglar, A., Parrilo, P.

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On the Delay and Throughput Gains of Coding in Unreliable Networks von Eryilmaz, A., Ozdaglar, A., Medard, M., Ahmed, E.

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The Price of Simplicity von Shakkottai, S., Srikant, R., Ozdaglar, A., Acemoglu, D.

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Competition in Parallel-Serial Networks von Acemoglu, D., Ozdaglar, A.

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Distributed Subgradient Methods for Convex Optimization Over Random Networks von Lobel, I, Ozdaglar, A

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Routing and wavelength assignment in optical networks von Ozdaglar, A.E., Bertsekas, D.P.

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Bayesian Learning in Social Networks von ACEMOGLU, DARON, DAHLEH, MUNTHER A., LOBEL, ILAN, OZDAGLAR, ASUMAN

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Spread of (mis)information in social networks von Acemoglu, Daron, Ozdaglar, Asuman, ParandehGheibi, Ali

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Partially Optimal Routing von Acemoglu, D., Johari, R., Ozdaglar, A.

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Pseudonormality and a Lagrange multiplier theory for constrained optimization von BERTSEKAS, D. P, OZDAGLAR, A. E

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Convergence Rate of Incremental Gradient and Incremental Newton Methods von Gürbüzbalaban, M., Ozdaglar, A., Parrilo, P. A.

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Existence of global minima for constrained optimization von OZDAGLAR, A. E, TSENG, P

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