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SODA
2010
ACM
176views Algorithms» more  SODA 2010»
16 years 3 months ago
Self-improving Algorithms for Convex Hulls
We describe an algorithm for computing planar convex hulls in the self-improving model: given a sequence I1, I2, . . . of planar n-point sets, the upper convex hull conv(I) of eac...
Kenneth L. Clarkson, Wolfgang Mulzer, C. Seshadhri
FOCS
2008
IEEE
16 years 10 days ago
The Bayesian Learner is Optimal for Noisy Binary Search (and Pretty Good for Quantum as Well)
We use a Bayesian approach to optimally solve problems in noisy binary search. We deal with two variants: • Each comparison is erroneous with independent probability 1 − p. â€...
Michael Ben-Or, Avinatan Hassidim
ICPR
2008
IEEE
16 years 10 days ago
Feature selection for clustering with constraints using Jensen-Shannon divergence
In semi-supervised clustering, domain knowledge can be converted to constraints and used to guide the clustering. In this paper we propose a feature selection algorithm for semi-s...
Yuanhong Li, Ming Dong, Yunqian Ma
FOCS
2005
IEEE
15 years 11 months ago
On Learning Mixtures of Heavy-Tailed Distributions
We consider the problem of learning mixtures of arbitrary symmetric distributions. We formulate sufficient separation conditions and present a learning algorithm with provable gua...
Anirban Dasgupta, John E. Hopcroft, Jon M. Kleinbe...
ICML
2005
IEEE
16 years 6 months ago
Learning first-order probabilistic models with combining rules
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
Sriraam Natarajan, Prasad Tadepalli, Eric Altendor...