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Maximum likelihood from incomplete data via the EM algorithm
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1977
"... A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situat ..."
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Cited by 11827 (17 self)
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A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situations, applications to grouped, censored or truncated data, finite mixture models, variance component estimation, hyperparameter estimation, iteratively reweighted least squares and factor analysis.
On the distribution of the length of the longest increasing subsequence of random permutations
 J. Amer. Math. Soc
, 1999
"... Let SN be the group of permutations of 1, 2,...,N. If π ∈ SN,wesaythat π(i1),...,π(ik) is an increasing subsequence in π if i1 <i2 <·· · <ikand π(i1) < π(i2) < ···<π(ik). Let lN (π) be the length of the longest increasing subsequence. For example, if N =5andπis the permutation 5 1 ..."
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
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Cited by 730 (8 self)
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Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass
Depth first search and linear graph algorithms
 SIAM JOURNAL ON COMPUTING
, 1972
"... The value of depthfirst search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components of an undirect ..."
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Cited by 1395 (19 self)
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of an undirect graph are presented. The space and time requirements of both algorithms are bounded by k 1V + k2E d k for some constants kl, k2, and k a, where Vis the number of vertices and E is the number of edges of the graph being examined.
Chebyshev and Fourier Spectral Methods
, 1999
"... Contents PREFACE x Acknowledgments xiv Errata and ExtendedBibliography xvi 1 Introduction 1 1.1 Series expansions .................................. 1 1.2 First Example .................................... 2 1.3 Comparison with finite element methods .................... 4 1.4 Comparisons with ..."
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Cited by 784 (12 self)
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Contents PREFACE x Acknowledgments xiv Errata and ExtendedBibliography xvi 1 Introduction 1 1.1 Series expansions .................................. 1 1.2 First Example .................................... 2 1.3 Comparison with finite element methods .................... 4 1.4 Comparisons
An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions
 ACMSIAM SYMPOSIUM ON DISCRETE ALGORITHMS
, 1994
"... Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any po ..."
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Cited by 987 (32 self)
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query point q 2 R d , and ffl ? 0, a (1 + ffl)approximate nearest neighbor of q can be computed in O(c d;ffl log n) time, where c d;ffl d d1 + 6d=ffle d is a factor depending only on dimension and ffl. In general, we show that given an integer k 1, (1 + ffl)approximations to the k nearest neighbors
Guided search 2.0: A revised model of visual search
 PSYCHONOMIC BULLETIN & REVIEW
, 1994
"... ..."
Investor psychology and security market under and overreactions
 Journal of Finance
, 1998
"... We propose a theory of securities market under and overreactions based on two wellknown psychological biases: investor overconfidence about the precision of private information; and biased selfattribution, which causes asymmetric shifts in investors ’ confidence as a function of their investment ..."
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Cited by 661 (38 self)
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challenge to the traditional view that securities are rationally priced to ref lect all publicly available information. Some of the more pervasive anoma
Studies of transformation of Escherichia coli with plasmids
 J. Mol. Biol
, 1983
"... Factors that affect he probability of genetic transformation f Escherichia coli by plasmids have been evaluated. A set of conditions is described under which about one in every 400 plasmid molecules produces a transformed cell. These conditions include cell growth in medium containing elevated level ..."
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Cited by 1609 (1 self)
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Factors that affect he probability of genetic transformation f Escherichia coli by plasmids have been evaluated. A set of conditions is described under which about one in every 400 plasmid molecules produces a transformed cell. These conditions include cell growth in medium containing elevated
Results 1  10
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470,877