39 citations · 99 across the 10 of their papers we have counts for
11 papers
CVXPY 1.9: Recent Advances in Optimization Modeling Software
William Zhang, Parth Nobel, Aryaman Jeendgar +3
CVXPY is a Python-embedded domain-specific language for convex optimization that lets users express problems in mathematical notation while the system verifies convexity and reduce…
Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software
Riley Murray, James Demmel, Michael W. Mahoney +10
Randomized numerical linear algebra - RandNLA, for short - concerns the use of randomization as a resource to develop improved algorithms for large-scale linear algebra computation…
Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition
Vivek Bharadwaj, Osman Asif Malik, Riley Murray +3
We present a data structure to randomly sample rows from the Khatri-Rao product of several matrices according to the exact distribution of its leverage scores. Our proposed sampler…
Sampling-Based Decomposition Algorithms for Arbitrary Tensor Networks
Osman Asif Malik, Vivek Bharadwaj, Riley Murray
We show how to develop sampling-based alternating least squares (ALS) algorithms for decomposition of tensors into any tensor network (TN) format. Provided the TN format satisfies…
Distributed-Memory Randomized Algorithms for Sparse Tensor CP Decomposition
Vivek Bharadwaj, Osman Asif Malik, Riley Murray +2
Candecomp / PARAFAC (CP) decomposition, a generalization of the matrix singular value decomposition to higher-dimensional tensors, is a popular tool for analyzing multidimensional…
Algebraic perspectives on signomial optimization
Mareike Dressler, Riley Murray
Signomials are obtained by generalizing polynomials to allow for arbitrary real exponents. This generalization offers great expressive power, but has historically sacrificed the or…
Sublinear Circuits and the Constrained Signomial Nonnegativity Problem
Riley Murray, Helen Naumann, Thorsten Theobald
Conditional Sums-of-AM/GM-Exponentials (conditional SAGE) is a decomposition method to prove nonnegativity of a signomial or polynomial over some subset of real space. In this…
Robust Market Equilibria with Uncertain Preferences
Riley Murray, Christian Kroer, Alex Peysakhovich +1
The problem of allocating scarce items to individuals is an important practical question in market design. An increasingly popular set of mechanisms for this task uses the concept…
Signomial and Polynomial Optimization via Relative Entropy and Partial Dualization
Riley Murray, Venkat Chandrasekaran, Adam Wierman
We describe a generalization of the Sums-of-AM/GM Exponential (SAGE) relaxation methodology for obtaining bounds on constrained signomial and polynomial optimization problems. Our…
Newton Polytopes and Relative Entropy Optimization
Riley Murray, Venkat Chandrasekaran, Adam Wierman
Certifying function nonnegativity is a ubiquitous problem in computational mathematics, with especially notable applications in optimization. We study the question of certifying no…
Scheduling Distributed Clusters of Parallel Machines: Primal-Dual and LP-based Approximation Algorithms [Full Version]
Riley Murray, Samir Khuller, Megan Chao
The Map-Reduce computing framework rose to prominence with datasets of such size that dozens of machines on a single cluster were needed for individual jobs. As datasets approach t…