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- Madeleine Udell, Corinne Horn, Reza Bosagh Zadeh, Stephen P. Boyd
- Foundations and Trends in Machine Learning
- 2016

Principal components analysis (PCA) is a well-known technique for approximating a data set represented by a matrix by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data setsâ€¦ (More)

- Damek Davis, Brent Edmunds, Madeleine Udell
- NIPS
- 2016

We introduce the Stochastic Asynchronous Proximal Alternating Linearized Minimization (SAPALM) method, a block coordinate stochastic proximal-gradient method for solving nonconvex, nonsmoothâ€¦ (More)

- Madeleine Udell, Karanveer Mohan, David Zeng, Jenny Hong, Steven Diamond, Stephen P. Boyd
- 2014 First Workshop for High Performanceâ€¦
- 2014

This paper describes Convex, a convex optimization modeling framework in Julia. Convex translates problems from a user-friendly functional language into an abstract syntax tree describing theâ€¦ (More)

The problem of maximizing a sum of sigmoidal functions over a convex constraint set arises in many application areas. This objective captures the idea of decreasing marginal returns to investment,â€¦ (More)

- Elsa W. Birch, Madeleine Udell, Markus W. Covert
- Journal of theoretical biology
- 2014

We present two modifications of the flux balance analysis (FBA) metabolic modeling framework which relax implicit assumptions of the biomass reaction. Our flexible flux balance analysis (flexFBA)â€¦ (More)

- Alp Yurtsever, Madeleine Udell, Joel A. Tropp, Volkan Cevher
- AISTATS
- 2017

This paper concerns a fundamental class of convex matrix optimization problems. It presents the first algorithm that uses optimal storage and provably computes a lowrank approximation of a solution.â€¦ (More)

- Madeleine Udell
- 2014

We consider the problem of minimizing a sum of non-convex functions over a compact domain, subject to linear inequality and equality constraints. Approximate solutions can be found by solving aâ€¦ (More)

- Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher
- ArXiv
- 2016

This paper develops a suite of algorithms for constructing low-rank approximations of an input matrix from a random linear image of the matrix, called a sketch. These methods can preserve structuralâ€¦ (More)

- Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher
- NIPS
- 2017

Several important applications, such as streaming PCA and semidefinite programming, involve a large-scale positive-semidefinite (psd) matrix that is presented as a sequence of linear updates. Becauseâ€¦ (More)

- Edward H. Lee, Madeleine Udell, S. Simon Wong
- 2015 IEEE International Conference on Acousticsâ€¦
- 2015

We present matrix factorization as an enabling technique for analog-to-digital matrix multiplication (AD-MM). We show that factorization in the analog domain increases the total precision of AD-MM inâ€¦ (More)