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Network Coding for Distributed Storage Systems
This paper shows how to optimally generate MDS fragments directly from existing fragments in the system, and introduces a new scheme called regenerating codes which use slightly larger fragments than MDS but have lower overall bandwidth use.
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
A main result of this work is a sharp analysis of two robust distributed gradient descent algorithms based on median and trimmed mean operations, respectively, which are shown to achieve order-optimal statistical error rates for strongly convex losses.
Speeding Up Distributed Machine Learning Using Codes
This paper focuses on two of the most basic building blocks of distributed learning algorithms: matrix multiplication and data shuffling, and uses codes to reduce communication bottlenecks, exploiting the excess in storage.
Low-complexity image denoising based on statistical modeling of wavelet coefficients
We introduce a simple spatially adaptive statistical model for wavelet image coefficients and apply it to image denoising. Our model is inspired by a recent wavelet image compression algorithm, the
Rate-distortion methods for image and video compression
An overview of rate-distortion (R-D) based optimization techniques and their practical application to image and video coding is provided and two popular techniques for resource allocation are introduced, namely, Lagrangian optimization and dynamic programming.
Distributed source coding using syndromes (DISCUS): design and construction
This work introduces a new construction and practical framework for tackling the problem of distributed source coding based on the judicious incorporation of channel coding principles into this source coding problem and focuses in this paper on trellis-structured constructions of the framework to illustrate its utility.
Best wavelet packet bases in a rate-distortion sense
A fast rate-distortion (R-D) optimal scheme for coding adaptive trees whose individual nodes spawn descendents forming a disjoint and complete basis cover for the space spanned by their parent nodes
Fractional repetition codes for repair in distributed storage systems
We introduce a new class of exact Minimum-Bandwidth Regenerating (MBR) codes for distributed storage systems, characterized by a low-complexity uncoded repair process that can tolerate multiple node
A Solution to the Network Challenges of Data Recovery in Erasure-coded Distributed Storage Systems: A Study on the Facebook Warehouse Cluster
A new storage code is presented, using the recently proposed "Piggybacking" framework, that reduces the network and disk usage during recovery by 30% in theory, while also being storage optimal and supporting arbitrary design parameters.
A Survey on Network Codes for Distributed Storage
An overview of the research results on network coding techniques is provided, establishing that maintenance bandwidth can be reduced by orders of magnitude compared to standard erasure codes.