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SODA
2010
ACM
176views Algorithms» more  SODA 2010»
14 years 5 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
14 years 2 months 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
14 years 2 months 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
14 years 1 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
14 years 8 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...