885 citations · 3.8k across the 104 of their papers we have counts for
49 papers · 1 filter
Communication-Efficient Gradient Coding for Straggler Mitigation in Distributed Learning
Swanand Kadhe, O. Ozan Koyluoglu, Kannan Ramchandran
Distributed implementations of gradient-based methods, wherein a server distributes gradient computations across worker machines, need to overcome two limitations: delays caused by…
Gradient Coding Based on Block Designs for Mitigating Adversarial Stragglers
Swanand Kadhe, O. Ozan Koyluoglu, Kannan Ramchandran
Distributed implementations of gradient-based methods, wherein a server distributes gradient computations across worker machines, suffer from slow running machines, called 'straggl…
A Sequential Approximation Framework for Coded Distributed Optimization
Jingge Zhu, Ye Pu, Vipul Gupta +2
Building on the previous work of Lee et al. and Ferdinand et al. on coded computation, we propose a sequential approximation framework for solving optimization problems in a distri…
Fundamental Limits of DNA Storage Systems
Reinhard Heckel, Ilan Shomorony, Kannan Ramchandran +1
Due to its longevity and enormous information density, DNA is an attractive medium for archival storage. In this work, we study the fundamental limits and tradeoffs of DNA-based st…
Density Evolution on a Class of Smeared Random Graphs: A Theoretical Framework for Fast MRI
Kabir Chandrasekher, Orhan Ocal, Kannan Ramchandran
We introduce a new ensemble of random bipartite graphs, which we term the `smearing ensemble', where each left node is connected to some number of consecutive right nodes. Such gra…
Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes
Dong Yin, Ramtin Pedarsani, Yudong Chen +1
In this paper, we consider the mixture of sparse linear regressions model. Let be unknown sparse parameter vectors with a total of $ K…