New Techniques for Algorithm Portfolio Design (2009)
Matthew Streeter, Stephen F. Smith
We present and evaluate new techniques for designing algorithm portfolios. In our view, the problem has both a scheduling aspect and a machine learning aspect. Prior work has largely addressed one of...
Online Learning of Assignments that Maximize Submodular Functions (2009)
Golovin, Daniel, Krause, Andreas, Streeter, Matthew
Which ads should we display in sponsored search in order to maximize our revenue? How should we dynamically rank information sources to maximize value of information? These applications exhibit...
NP-hard problems are worst-case intractable under standard assumptions But, they arise frequently in practice 2
Automated Discovery of Numerical Approximation Formulae via Genetic Programming (2008)
This paper describes the use of genetic programming to automate the discovery of numerical approximation formulae. The authors present results involving rediscovery of known approximations for...
Introduction Research Statement (2008)
My research integrates theory and experiment. I enjoy the process of coming up with mathematically precise formulations of problems that need to be solved in the world, creating and analyzing...
Combining multiple constraint solvers: Results on the CPAI’06 competition (2007)
Matthew Streeter, Daniel Golovin, Stephen F. Smith
Abstract. In a recent paper [5], we presented an algorithm that constructs a schedule for interleaving the execution of two or more solvers, with the goal of obtaining improved average-case running...
Using Online Algorithms to Solve NP-Hard Problems More Efficiently in Practice (2007)
Matthew Streeter, Avrim Blum, Carla P. Gomes
as representing the official policies of the U.S. Government.
Restart schedules for ensembles of problem instances (2007)
Matthew Streeter, Daniel Golovin, Stephen F. Smith
The mean running time of a Las Vegas algorithm can often be dramatically reduced by periodically restarting it with a fresh random seed. The optimal restart schedule depends on the Las Vegas...
Online algorithms for maximizing submodular functions. Working paper (2007)
Matthew Streeter, Daniel Golovin
This research was supported in part by NSF ITR grants CCR-0122581 and IIS-0121678 and by DARPA under Contract #FA8750-05-C-0033.
Combining multiple heuristics online (2007)
Matthew Streeter, Daniel Golovin, Stephen F. Smith
We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a set of heuristics...
An online algorithm for maximizing submodular functions (2007)
Matthew Streeter, Daniel Golovin
We present an algorithm for solving a broad class of online resource allocation jobs arrive one at a time, and one can complete the jobs by investing time in a number of abstract activities,...
Online Selection, Adaptation, and Hybridization of Algorithms (Thesis proposal) (2006)
We propose to develop black-box techniques for improving the performance of algorithms by adapting them to the sequence of problem instances on which they are run. In particular, we propose to...
NVIS: an interactive visualization tool for neural networks (2001)
Matthew Streeter, Matthew Ward, Sergio A. Alvarez
This paper presents NVIS, an interactive graphical tool used to examine the weights, topology, and activations of a single artificial neural network (ANN), as well as the genealogical relationships...