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- Haim Avron, Petar Maymounkov, Sivan Toledo
- SIAM J. Scientific Computing
- 2010

Several innovative random-sampling and random-mixing techniques for solving problems in linear algebra have been proposed in the last decade, but they have not yet made a significant impact onâ€¦ (More)

- Haim Avron, Sivan Toledo
- J. ACM
- 2011

We analyze the convergence of randomized trace estimators. Starting at 1989, several algorithms have been proposed for estimating the trace of a matrix by 1/Mâˆ‘<sub>i</sub>=1<sup>M</sup>â€¦ (More)

We describe novel subgradient methods for a broad class of matrix optimization problems involving nuclear norm regularization. Unlike existing approaches, our method executes very cheap iterations byâ€¦ (More)

- Haim Avron, Christos Boutsidis
- SIAM J. Matrix Analysis Applications
- 2013

We study the following problem of subset selection for matrices: given a matrix X âˆˆ R (m > n) and an oversampling parameter k (n â‰¤ k â‰¤ m), select a subset of k columns from X such that theâ€¦ (More)

- Po-Sen Huang, Haim Avron, Tara N. Sainath, Vikas Sindhwani, Bhuvana Ramabhadran
- 2014 IEEE International Conference on Acousticsâ€¦
- 2014

Despite their theoretical appeal and grounding in tractable convex optimization techniques, kernel methods are often not the first choice for large-scale speech applications due to their significantâ€¦ (More)

- Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael W. Mahoney
- ICML
- 2014

We consider the problem of improving the efficiency of randomized Fourier feature maps to accelerate training and testing speed of kernel methods on large data sets. These approximate feature mapsâ€¦ (More)

- Haim Avron, Alex Druinsky, Anshul Gupta
- 2014 IEEE 28th International Parallel andâ€¦
- 2014

Asynchronous methods for solving systems of linear equations have been researched since Chazan and Miranker's [1969] pioneering paper on chaotic relaxation. The underlying idea of asynchronousâ€¦ (More)

- Insu Han, Dmitry Malioutov, Haim Avron, Jinwoo Shin
- ArXiv
- 2016

Computation of the trace of a matrix function plays an important role in many scientific computing applications, including applications in machine learning, computational physics (e.g., latticeâ€¦ (More)

Random Fourier features is one of the most popular techniques for scaling up kernel methods, such as kernel ridge regression. However, despite impressive empirical results, the statistical propertiesâ€¦ (More)

- Prabhanjan Kambadur, Anshul Gupta, Amol Ghoting, Haim Avron, Andrew Lumsdaine
- Proceedings of the Conference on High Performanceâ€¦
- 2009

HPC today faces new challenges due to paradigm shifts in both hardware and software. The ubiquity of multi-cores, many-cores, and GPGPUs is forcing traditional serial as well as distributed-memoryâ€¦ (More)