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When learning a directed acyclic graph (DAG) model via observational data, one gener-ally cannot identify the underlying DAG, but can potentially obtain a Markov equivalence class. The size (the numbe...
Graphical models are popular statistical tools which are used to represent dependent or causal complex systems. Statistically equivalent causal or directed graphical models are said to belong to a Mar...
When learning a directed acyclic graph (DAG) model via observational data, one gener-ally cannot identify the underlying DAG, but can potentially obtain a Markov equivalence class. The size (the numbe...
By the criterion for surrogates proposed by Prentice (1989), a null treatment effect on a surrogate implies a null treatment effect on a true endpoint.In this paper, we show that there may exist simul...
Interest in linear programming has been intensified recently by Karmarkar's publication in 1984 of an algorithm that is claimed to be much faster than the simplex method for practical problems. We...
We consider a general class of statistical mechanical models of coherent structures in turbulence, which includes models of two-dimensional fluid motion, quasi-geostrophic flows, and dispersive waves....
This paper shows for a general class of statistical mechanical models that when the microcanonical and canonical ensembles are nonequivalent on a subset of values of the energy, there often exists a g...
Using the theory of large deviations, we analyze the phase transition structure of the Curie–Weiss–Potts spin model, which is a mean-field approximation to the nearest-neighbor Potts model. It is equi...
Given a constrained minimization problem, under what conditions does there exist a related, unconstrained problem having the same minimum points? This basic question in global optimization motivates t...
This paper is a companion piece to our previous work [J. Stat. Phys. 119, 1283 (2005)], which introduced a generalized canonical ensemble obtained by multiplying the usual Boltzmann weight factor e...
In this work, we revisit the question of stability of multibreather configurations, i.e., discrete breathers with multiple excited sites at the anti-continuum limit of uncoupled oscillators. We presen...
In many applications we have both observational and (randomized) interventional data. We propose a Gaussian likelihood framework for joint modeling of such different data-types, based on global parame...
We investigate the relation of two fundamental tools in machine learning, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression. We show that the resu...
This supplementary material includes three parts: some preliminary results, four examples, an experiment, three new algorithms, and all proofs of the results in the paper "Reversible MCMC on Markov eq...
There has been growing interest in recent years in Q-matrix based cognitive diagnosis models. Parameter estimation and respondent classification under these models may suffer due to identifiability is...

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