DIPW 2018 - ACM MobiHoc Workshop on Distributed Information Processing in Wireless Networks

The unprecedented advances in sensing, communication, and storage technologies have motivated the development of a plethora of optimization and learning algorithms capable of distributed operation over networks. Some of the popular application areas where such algorithms have been widely applied include distributed signal processing in wireless sensor networks, distributed resource allocation in cellular and ad hoc networks, distributed machine learning algorithms for Big Data, and distributed localization and tracking.
Desired attributes of such decentralized information processing algorithms include parallelizability, scalability, robustness to channel impairments and network delays, low-cost operation, and the ability to handle uncertain and dynamic network topologies. Embedding such features into classical information processing techniques is challenging, and has sparked the development of a gamut of distributed algorithms.
The aim of the workshop is to provide an international forum for discussions of recent developments in distributed learning, optimization, signal processing, and resource management. The focus will be on the design and analysis of algorithms capable of handling the vagaries of wireless networks, such as delays, limited and heterogeneous abilities, channel impairments, and communication restrictions arising due to the network topology.
Topics of interest include (but are not limited to):
Machine learning over networks
Signal processing over networks
Statistical signal processing on networks
Distributed optimization for signal processing
Distributed optimization for communication systems
Distributed optimization for cyber physical systems
Distributed control over networked systems
Distributed resource management over networks
Non-convex optimization methods over networks
Robust and stochastic optimization methods over networks
Privacy preservation in distributed algorithms
Asynchronous coordination schemes