QANM combines Nesterov-accelerated gradient descent with distributed finite-time quantized consensus to achieve linear convergence to a neighborhood of the optimum in unconstrained distributed optimization over directed graphs under strong convexity and smoothness.
Linear convergence of consensus-based quantized optimization for smooth and strongly con- vex cost functions,
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Nesterov Accelerated Distributed Optimization with Efficient Quantized Communication
QANM combines Nesterov-accelerated gradient descent with distributed finite-time quantized consensus to achieve linear convergence to a neighborhood of the optimum in unconstrained distributed optimization over directed graphs under strong convexity and smoothness.