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- Ramgopal R. Mettu, C. Greg Plaxton
- FOCS
- 2000

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 facilities, the online median problem imposes the following additional constraints: the facilities are placed one at a time; a facility cannot be moved once it… (More)

- Ramgopal R. Mettu, C. Greg Plaxton
- Machine Learning
- 2002

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 clustering with respect to the k-median objective function, a natural formulation of clustering in which we attempt to minimize the average distance to cluster centers.… (More)

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 dependencies. The goal of adaptive inference is to take advantage of what is preserved in the model and perform inference more rapidly than from scratch. In… (More)

- Özgür Sümer, Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu
- Journal of Machine Learning Research
- 2011

Many algorithms and applications involve repeatedly solving variations of the same inference problem, for example to introduce new evidence to the model or to change conditional dependencies. As the model is updated, the goal of adaptive inference is to take advantage of previously computed quantities to perform inference more rapidly than from scratch. In… (More)

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 and orientation of secondary structure elements as well as the global fold in polynomial time. This is the first polynomialtime algorithm for de novo… (More)

- Lincong Wang, Ramgopal R. Mettu, Bruce Randall Donald
- 2005 IEEE Computational Systems Bioinformatics…
- 2005

Our paper describes the first provably-efficient algorithm for determining protein structures de novo, solely from experimental data. We show how the global nature of a certain kind of NMR data provides quantifiable complexity-theoretic benefits, allowing us to classify our algorithm as running in polynomial time. While our algorithm uses NMR data as input,… (More)

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, likelihood estimates etc.) must be updated, we study the problem of adaptive inference in tree-structured Bayesian networks. We describe an algorithm for adaptive… (More)

- Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu, Ozgur Sumer
- 2009 IEEE/SP 15th Workshop on Statistical Signal…
- 2009

Many applications involve repeatedly computing the optimal, maximum a posteriori (MAP) configuration of a graphical model as the model changes, often slowly or incrementally over time, e.g., due to input from a user. Small changes to the model often require updating only a small fraction of the MAP configuration, suggesting the possibility of performing… (More)

- Suraj Kumar Jaiswal, Aura Ganz, Ramgopal R. Mettu
- 2007 Fourth International Conference on Broadband…
- 2007

In this paper, we investigate the problem of scheduling flows for fair stream allocation in ad hoc networks utilizing multiple antennas at the transmitter and receiver side known as Multiple Input Multiple Output (MIMO) antenna technology. Our main contributions include: i) the concept of stream allocation to flows based on their traffic demands or class,… (More)

- Lincong Wang, Ramgopal R. Mettu, Bruce Randall Donald
- Journal of Computational Biology
- 2006

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 and orientation of secondary structure elements as well as the global fold in polynomial time. This is the first polynomial-time algorithm for de novo… (More)