Complexity of Distributed Statistical Algorithms
نویسندگان
چکیده
This paper constructs bounds on the minimax risk under loss functions when statistical estimation is performed in a distributed environment and with communication constraints. We treat this problem using techniques from information theory and communication complexity. In many cases our bounds rely crucially on metric entropy conditions and the classical reduction from estimation to testing. A number of examples exhibit how bounds on the minimax risk play out in practice. We also study distributed statistical estimation problems in the context of PAC-learnability and derive explicit algorithms for solving classical problems. We study the communication complexity of these algorithms.
منابع مشابه
Distributed and Cooperative Compressive Sensing Recovery Algorithm for Wireless Sensor Networks with Bi-directional Incremental Topology
Recently, the problem of compressive sensing (CS) has attracted lots of attention in the area of signal processing. So, much of the research in this field is being carried out in this issue. One of the applications where CS could be used is wireless sensor networks (WSNs). The structure of WSNs consists of many low power wireless sensors. This requires that any improved algorithm for this appli...
متن کاملLow-Complexity Message-Passing Algorithms for Distributed Computation
Low-Complexity Message-Passing Algorithms for Distributed Computation by Nima Noorshams Doctor of Philosophy in Engineering-Electrical Engineering & Computer Sciences University of California, Berkeley Professor Martin J. Wainwright, Chair Central to many statistical inference problems is the computation of some quantities defined over variables that can be fruitfully modeled in terms of graphs...
متن کاملSatellite Conceptual Design Multi-Objective Optimization Using Co Framework
This paper focuses upon the development of an efficient method for conceptual design optimization of a satellite. There are many option for a satellite subsystems that could be choice, as acceptable solution to implement of a space system mission. Every option should be assessment based on the different criteria such as cost, mass, reliability and technology contraint (complexity). In this rese...
متن کاملDistributed Machine Learning with Communication Constraints
Distributed Machine Learning with Communication Constraints by Yuchen Zhang Doctor of Philosophy in Computer Science University of California, Berkeley Professor Michael I. Jordan, Co-chair Professor Martin J. Wainwright, Co-chair Distributed machine learning bridges the traditional fields of distributed systems and machine learning, nurturing a rich family of research problems. Classical machi...
متن کاملDistributed k-Means and k-Median Clustering on General Topologies
This paper provides new algorithms for distributed clustering for two popular center-based objectives, k-median and k-means. These algorithms have provable guarantees and improve communication complexity over existing approaches. Following a classic approach in clustering by [13], we reduce the problem of finding a clustering with low cost to the problem of finding a coreset of small size. We p...
متن کامل