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Testing Closeness of Discrete Distributions
"... Given samples from two distributions over an nelement set, we wish to test whether these distributions are statistically close. We present an algorithm which uses sublinear in n, specifically, O(n 2/3 ǫ −8/3 log n), independent samples from each distribution, runs in time linear in the sample size, ..."
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Cited by 28 (1 self)
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Given samples from two distributions over an nelement set, we wish to test whether these distributions are statistically close. We present an algorithm which uses sublinear in n, specifically, O(n 2/3 ǫ −8/3 log n), independent samples from each distribution, runs in time linear in the sample size
Optimal algorithms for testing closeness of discrete distributions
, 2013
"... We study the question of closeness testing for two discrete distributions. More precisely, given samples from two distributions p and q over an nelement set, we wish to distinguish whether p = q versus p is at least εfar from q, in either `1 or `2 distance. Batu et al [BFR+00, BFR+13] gave the fir ..."
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Cited by 12 (1 self)
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We study the question of closeness testing for two discrete distributions. More precisely, given samples from two distributions p and q over an nelement set, we wish to distinguish whether p = q versus p is at least εfar from q, in either `1 or `2 distance. Batu et al [BFR+00, BFR+13] gave
MIXED MNL MODELS FOR DISCRETE RESPONSE
 JOURNAL OF APPLIED ECONOMETRICS J. APPL. ECON. 15: 447470 (2000)
, 2000
"... This paper considers mixed, or random coefficients, multinomial logit (MMNL) models for discrete response, and establishes the following results. Under mild regularity conditions, any discrete choice model derived from random utility maximization has choice probabilities that can be approximated as ..."
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Cited by 487 (15 self)
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specification can be tested simply as an omitted variable test with appropriately defined artificial variables. An application to a problem of demand for alternative vehicles shows that MMNL provides a flexible and computationally practical approach to discrete response analysis.
Maximum entropy markov models for information extraction and segmentation
, 2000
"... Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many textrelated tasks, such as partofspeech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled as multinomial ..."
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Cited by 561 (18 self)
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as multinomial distributions over a discrete vocabulary, and the HMM parameters are set to maximize the likelihood of the observations. This paper presents a new Markovian sequence model, closely related to HMMs, that allows observations to be represented as arbitrary overlapping features (such as word
Linear models and empirical bayes methods for assessing differential expression in microarray experiments.
 Stat. Appl. Genet. Mol. Biol.
, 2004
"... Abstract The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior odds of differential expression in a replicated twocolor experiment using a simple hierarchical parametric model. ..."
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Cited by 1321 (24 self)
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null prior for the fold changes are not required. The moderated tstatistic is shown to follow a tdistribution with augmented degrees of freedom. The moderated t inferential approach extends to accommodate tests of composite null hypotheses through the use of moderated Fstatistics. The performance
A family of algorithms for approximate Bayesian inference
, 2001
"... One of the major obstacles to using Bayesian methods for pattern recognition has been its computational expense. This thesis presents an approximation technique that can perform Bayesian inference faster and more accurately than previously possible. This method, "Expectation Propagation," ..."
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Cited by 366 (11 self)
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distribution with a simpler distribution, which is close in the sense of KLdivergence. Expectation Propagation exploits the best of both algorithms: the generality of assumeddensity filtering and the accuracy of loopy belief propagation. Loopy belief propagation, because it propagates exact belief states
Topologicallyaware overlay construction and server selection
, 2002
"... A number of largescale distributed Internet applications could potentially benefit from some level of knowledge about the relative proximity between its participating host nodes. For example, the performance of large overlay networks could be improved if the applicationlevel connectivity between ..."
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Cited by 341 (3 self)
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knowledge of a small number of wellknown landmark nodes) and completely distributed (requiring no communication or cooperation between the nodes being binned). We apply this binning strategy to the two applications mentioned above: overlay network construction and server selection. We test our binning
Estimating dynamic models of imperfect competition
, 2007
"... We describe a twostep algorithm for estimating dynamic games under the assumption that behavior is consistent with Markov perfect equilibrium. In the first step, the policy functions and the law of motion for the state variables are estimated. In the second step, the remaining structural parameters ..."
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Cited by 279 (14 self)
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and Pakes (1995) model. We test the algorithm on a class of dynamic discrete choice models with normally distributed errors and a class of dynamic oligopoly models similar to that of Pakes and McGuire (1994).
A new diamond search algorithm for fast block matching motion estimation
 in Proc. Int. Conf. Inform., Commun., Signal Process
, 1997
"... Abstract—Based on the study of motion vector distribution from several commonly used test image sequences, a new diamond search (DS) algorithm for fast blockmatching motion estimation (BMME) is proposed in this paper. Simulation results demonstrate that the proposed DS algorithm greatly outperforms ..."
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Cited by 268 (1 self)
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Abstract—Based on the study of motion vector distribution from several commonly used test image sequences, a new diamond search (DS) algorithm for fast blockmatching motion estimation (BMME) is proposed in this paper. Simulation results demonstrate that the proposed DS algorithm greatly
Testing that distributions are close
 In IEEE Symposium on Foundations of Computer Science
, 2000
"... Given two distributions over an n element set, we wish to check whether these distributions are statistically close by only sampling. We give a sublinear algorithm which uses O(n 2/3 ɛ −4 log n) independent samples from each distribution, runs in time linear in the sample size, makes no assumptions ..."
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Cited by 98 (15 self)
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Given two distributions over an n element set, we wish to check whether these distributions are statistically close by only sampling. We give a sublinear algorithm which uses O(n 2/3 ɛ −4 log n) independent samples from each distribution, runs in time linear in the sample size, makes no assumptions
Results 1  10
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5,444