Adaptive Inference on General Graphical Models (2009)
Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu, Özgür Sümer
Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional...
Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu, Özgür Sümer
Motivated by stochastic systems in which observed evidence and conditional dependencies between states of the network change over time, and certain quantities of interest (marginal distributions,...
Lincong Wang, Ramgopal R. Mettu, Bruce Randall Donald
We describe an efficient algorithm for protein backbone structure determination from solution Nuclear Magnetic Resonance (NMR) data. A key feature of our algorithm is that it finds the conformation...
The Online Median Problem \Lambda (2008)
Ramgopal R. Mettu, C. Greg Plaxton
Abstract We introduce a natural variant of the (metric uncapac-itated) k-median problem that we call the online medianproblem. Whereas the k-median problem involves opti-mizing the simultaneous...
Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu, Özgür Sümer
Motivated by stochastic systems in which observed evidence and conditional dependencies between states of the network change over time, and certain quantities of interest (marginal distributions,...
Adaptive Bayesian inference (2008)
Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu, Özgür Sümer
Motivated by stochastic systems in which observed evidence and conditional dependencies between states of the network change over time, and certain quantities of interest (marginal distributions,...
High-throughput inference of protein-protein interfaces from unassigned NMR data (2005)
Mettu, Ramgopal R., Lilien, Ryan H., Donald, Bruce Randall
Summary: We cast the problem of identifying protein–protein interfaces, using only unassigned NMR spectra, into a geometric clustering problem. Identifying protein–protein interfaces is critical...
Lincong Wang, Ramgopal R. Mettu, Ryan Lilien, Bruce R, All Donald
We have developed a novel algorithm for protein backbone structure determination using global orientational restraints on internuclear bond vectors derived from residual dipolar couplings (RDCs)...
Lincong Wang, Ramgopal R. Mettu, Ryan Lilien, Bruce R, All Donald
We have developed a novel algorithm for protein backbone structure determination using global orientational restraints on internuclear bond vectors derived from residual dipolar couplings (RDCs)...
Optimal time bounds for approximate clustering (2002)
Ramgopal R. Mettu, C. Greg Plaxton
Clustering is a fundamental problem in unsupervised learning, and has been studied widely both as a problem of learning mixture models and as an optimization problem. In this paper, we study...
Optimal time bounds for approximate clustering (2002)
Ramgopal R. Mettu, C. Greg Plaxton
We give randomized constant-factor approximation algorithms for the k-median problem and an intimately related clustering problem. The input to each of these problems is a metric space with n...
Optimal Time Bounds for Approximate Clustering (2002)
Ramgopal R. Mettu, C. Greg Plaxton
Clustering is a fundamental problem in unsupervised learning, and has been studied widely both as a problem of learning mixture models and as an optimization problem. In this paper, we study...
Optimal time bounds for approximate clustering (2002)
Clustering is a fundamental problem in unsuper-vised learning, and has been studied widely both as a problem of learning mixture models andas an optimization problem. In this paper, we study...
Optimal time bounds for approximate clustering (2002)
Ramgopal R. Mettu, C. Greg Plaxton
We give randomized constant-factor approximation algorithms for the�-median problem and an intimately related clustering problem. The input to each of these problems is a metric space...
Optimal time bounds for approximate clustering (2002)
Ramgopal R. Mettu, C. Greg Plaxton
We give randomized constant-factor approximation algorithms for the k-median problem and an intimately related clustering problem. The input to each of these problems is a metric space with n...
The Online Median Problem (2000)
Ramgopal R. Mettu, C. Greg Plaxton
We introduce a natural variant of the (metric uncapacitated) k-median problem that we call the online median problem. Whereas the k-median problem involves optimizing the simultaneous placement of k...
The Online Median Problem (2000)
Ramgopal R. Mettu, C. Greg Plaxton
We introduce a natural variant of the (metric uncapacitated) k-median problem that we call the online median problem. Whereas the k-median problem involves optimizing the simultaneous placement of k...
The Online Median Problem (2000)
Ramgopal R. Mettu, C. Greg Plaxton
We introduce a natural variant of the (metric uncapacitated) k-median problem that we call the online median problem. Whereas the k-median problem involves optimizing the simultaneous placement of k...
The Online Median Problem (2000)
Ramgopal R. Mettu, C. Greg Plaxton
We introduce a natural variant of the (metric uncapacitated) ¡-median problem that we call the online median problem. Whereas the ¡-median problem involves optimizing the simultaneous placement of...
The Online Median Problem \Lambda (1999)
Ramgopal R. Mettu, C. Greg Plaxton
Abstract We introduce a natural variant of the (metric uncapacitated) k-median problem that we call the on-line median problem. Whereas the k-median problem involves optimizing the simultaneous...
The Online Median Problem \Lambda (1999)
Ramgopal R. Mettu, C. Greg Plaxton
Abstract We introduce a natural variant of the (metric uncapacitated) k-median problem that we call the on-line median problem. Whereas the k-median problem involves optimizing the simultaneous...