12 citations · 21 across the 3 of their papers we have counts for
5 papers
Gradient Coding from Cyclic MDS Codes and Expander Graphs
Netanel Raviv, Itzhak Tamo, Rashish Tandon +1
Gradient coding is a technique for straggler mitigation in distributed learning. In this paper we design novel gradient codes using tools from classical coding theory, namely, cycl…
Gradient Coding
Rashish Tandon, Qi Lei, Alexandros G. Dimakis +1
We propose a novel coding theoretic framework for mitigating stragglers in distributed learning. We show how carefully replicating data blocks and coding across gradients can provi…
Kernel Ridge Regression via Partitioning
Rashish Tandon, Si Si, Pradeep Ravikumar +1
In this paper, we investigate a divide and conquer approach to Kernel Ridge Regression (KRR). Given n samples, the division step involves separating the points based on some underl…
On the Information Theoretic Limits of Learning Ising Models
Karthikeyan Shanmugam, Rashish Tandon, Alexandros G. Dimakis +1
We provide a general framework for computing lower-bounds on the sample complexity of recovering the underlying graphs of Ising models, given i.i.d samples. While there have been r…
Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization
Alekh Agarwal, Animashree Anandkumar, Prateek Jain +1
We consider the problem of sparse coding, where each sample consists of a sparse linear combination of a set of dictionary atoms, and the task is to learn both the dictionary eleme…