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Rashish Tandon
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Gradient coding: Avoiding stragglers in distributed learning
R Tandon, Q Lei, AG Dimakis, N Karampatziakis
International Conference on Machine Learning, 3368-3376, 2017
566*2017
Gradient coding from cyclic mds codes and expander graphs
N Raviv, I Tamo, R Tandon, AG Dimakis
arXiv preprint arXiv:1707.03858, 2017
2002017
Learning sparsely used overcomplete dictionaries
A Agarwal, A Anandkumar, P Jain, P Netrapalli, R Tandon
Conference on Learning Theory, 123-137, 2014
1232014
Sparse nonnegative matrix approximation: new formulations and algorithms
R Tandon, S Sra
Max Planck Institute for Biological Cybernetics, 2010
462010
On the information theoretic limits of learning Ising models
R Tandon, K Shanmugam, PK Ravikumar, AG Dimakis
Advances in Neural Information Processing Systems, 2303-2311, 2014
442014
On the difficulty of learning power law graphical models
R Tandon, P Ravikumar
2013 IEEE International Symposium on Information Theory, 2493-2497, 2013
172013
Kernel Ridge Regression via Partitioning
R Tandon, S Si, P Ravikumar, I Dhillon
arXiv preprint arXiv:1608.01976, 2016
122016
Learning Graphs with a Few Hubs
R Tandon, P Ravikumar
Proceedings of The 31st International Conference on Machine Learning, 602-610, 2014
82014
On the difficulty of learning power law graphical models: Proofs
R Tandon, P Ravikumar
1
Recovering sparsely used overcomplete dictionaries via alternating minimization
A Agarwal, A Anandkumar, P Jain, P Netrapalli, R Tandon
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