146 citations · 176 across the 17 of their papers we have counts for
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Approximate Supermodularity Bounds for Experimental Design
Luiz F. O. Chamon, Alejandro Ribeiro
This work provides performance guarantees for the greedy solution of experimental design problems. In particular, it focuses on A- and E-optimal designs, for which typical guarante…
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization
Aryan Mokhtari, Alejandro Ribeiro
This paper studies empirical risk minimization (ERM) problems for large-scale datasets and incorporates the idea of adaptive sample size methods to improve the guaranteed convergen…
The Dual Graph Shift Operator: Identifying the Support of the Frequency Domain
Geert Leus, Santiago Segarra, Alejandro Ribeiro +1
Contemporary data is often supported by an irregular structure, which can be conveniently captured by a graph. Accounting for this graph support is crucial to analyze the data, lea…
Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method
Mark Eisen, Aryan Mokhtari, Alejandro Ribeiro
We consider large scale empirical risk minimization (ERM) problems, where both the problem dimension and variable size is large. In these cases, most second order methods are infea…
IQN: An Incremental Quasi-Newton Method with Local Superlinear Convergence Rate
Aryan Mokhtari, Mark Eisen, Alejandro Ribeiro
The problem of minimizing an objective that can be written as the sum of a set of smooth and strongly convex functions is considered. The Incremental Quasi-Newton (IQN) method…