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An Approximate, Efficient Solver for LP Rounding
Srikrishna Sridhar, Victor Bittorf, Ji Liu +3
Many problems in machine learning can be solved by rounding the solution of an appropriate linear program (LP). This paper shows that we can recover solutions of comparable quality…
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm
Ji Liu, Stephen J. Wright, Christopher Ré +2
We describe an asynchronous parallel stochastic coordinate descent algorithm for minimizing smooth unconstrained or separably constrained functions. The method achieves a linear co…
An Accelerated Randomized Kaczmarz Algorithm
Ji Liu, Stephen J. Wright
The randomized Kaczmarz ($\RK$) algorithm is a simple but powerful approach for solving consistent linear systems . This paper proposes an accelerated randomized Kaczmarz ($\…
Online Algorithms for Factorization-Based Structure from Motion
Ryan Kennedy, Laura Balzano, Stephen J. Wright +1
We present a family of online algorithms for real-time factorization-based structure from motion, leveraging a relationship between incremental singular value decomposition and rec…
On GROUSE and Incremental SVD
Laura Balzano, Stephen J. Wright
GROUSE (Grassmannian Rank-One Update Subspace Estimation) is an incremental algorithm for identifying a subspace of Rn from a sequence of vectors in this subspace, where only a sub…
Local Convergence of an Algorithm for Subspace Identification from Partial Data
Laura Balzano, Stephen J. Wright
GROUSE (Grassmannian Rank-One Update Subspace Estimation) is an iterative algorithm for identifying a linear subspace of R^n from data consisting of partial observations of random…