WorldCat Identities

Jordan, Michael Irwin 1956-

Overview
Works: 56 works in 140 publications in 2 languages and 997 library holdings
Genres: Encyclopedias  Conference proceedings  Periodicals 
Roles: Editor
Classifications: BF311, 153.03
Publication Timeline
Key
Publications about  Michael Irwin Jordan Publications about Michael Irwin Jordan
Publications by  Michael Irwin Jordan Publications by Michael Irwin Jordan
Most widely held works by Michael Irwin Jordan
Learning in graphical models by Michael Irwin Jordan ( Book )
25 editions published between 1996 and 2002 in English and Undetermined and held by 359 WorldCat member libraries worldwide
In the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points of view. There has been substantial progress in these different communities and surprising convergence has developed between the formalisms. The awareness of this convergence and the growing interest of researchers in understanding the essential unity of the subject underlies the current volume. Two research communities which have used graphical or network formalisms to particular advantage are the belief network community and the neural network community. Belief networks arose within computer science and statistics and were developed with an emphasis on prior knowledge and exact probabilistic calculations. Neural networks arose within electrical engineering, physics and neuroscience and have emphasised pattern recognition and systems modelling problems. This volume draws together researchers from these two communities and presents both kinds of networks as instances of a general unified graphical formalism. The book focuses on probabilistic methods for learning and inference in graphical models, algorithm analysis and design, theory and applications. Exact methods, sampling methods and variational methods are discussed in detail. Audience: A wide cross-section of computationally oriented researchers, including computer scientists, statisticians, electrical engineers, physicists and neuroscientists
Graphical models : foundations of neural computation ( Book )
10 editions published in 2001 in English and held by 257 WorldCat member libraries worldwide
This title seeks to exemplify the interplay between the general formal framework of graphical models and the exploration of new algorithms and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research
Advances in neural information processing systems 10 : proceedings of the 1997 conference by Neural information processing systems ( Book )
15 editions published in 1998 in English and held by 76 WorldCat member libraries worldwide
Advances in neural information processing systems 9 : proceedings of the 1996 conference by IEEE conference on neural information processing systems ( Book )
11 editions published in 1997 in English and held by 60 WorldCat member libraries worldwide
The MIT encyclopedia of the cognitive sciences by Robert A Wilson ( Book )
1 edition published in 1999 in English and held by 44 WorldCat member libraries worldwide
Alfabetisk opslagsværk. Hver artikel er skrevet af førende forskere på området
Graphical models, exponential families, and variational inference by Martin J Wainwright ( )
7 editions published between 1996 and 2008 in English and held by 39 WorldCat member libraries worldwide
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate statistical models. Graphical models have become a focus of research in many statistical, computational and mathematical fields, including bioinformatics, communication theory, statistical physics, combinatorial optimization, signal and image processing, information retrieval and statistical machine learning. Many problems that arise in specific instances -- including the key problems of computing marginals and modes of probability distributions -- are best studied in the general setting. Working with exponential family representations, and exploiting the conjugate duality between the cumulant function and the entropy for exponential families, we develop general variational representations of the problems of computing likelihoods, marginal probabilities and most probable configurations. We describe how a wide variety of algorithms -- among them sum-product, cluster variational methods, expectation-propagation, mean field methods, max-product and linear programming relaxation, as well as conic programming relaxations -- can all be understood in terms of exact or approximate forms of these variational representations. The variational approach provides a complementary alternative to Markov chain Monte Carlo as a general source of approximation methods for inference in large-scale statistical models
Advances in neural information processing systems proceedings of the first 12 conferences ( Book )
2 editions published in 2001 in English and held by 23 WorldCat member libraries worldwide
Contains the entire proceedings of the 12 Neural Information Processing Systems conferences from 1988 to 1999
Advances in neural information processing systems ( Book )
7 editions published in 1997 in English and Undetermined and held by 11 WorldCat member libraries worldwide
Advances in neural information processing systems ( Book )
3 editions published in 2001 in English and held by 9 WorldCat member libraries worldwide
Contains the entire proceedings of the twelve neural information processing system conferences from 1988 to 1999. Includes free browsers for all major platforms
Serial order : a parallel distributed processing approach by Michael Irwin Jordan ( Book )
4 editions published in 1986 in English and held by 7 WorldCat member libraries worldwide
A theory of serial order is proposed which attempts to deal both with the classical problem of the temporal organization of internally generated action sequences as well as with certain of the parallel aspects of sequential behavior. The theory describes a dynamical system which is embodied as a parallel distributed processing or connectionist network. The trajectories of this dynamical system come to follow desired paths corresponding to particular action sequences as a result of a learning process during which constraints are imposed on the system. These constraints enforce sequentiality where necessary, and as they are relaxed, performance becomes more parallel. The theory is applied to the problem of coarticulation in speech production and simulation experiments are presented
Advances in neural information processing systems 5 by IEEE conference on neural information processing systems ( Book )
1 edition published in 1993 in Undetermined and held by 6 WorldCat member libraries worldwide
An introduction to variational methods for graphical models ( Book )
1 edition published in 1998 in English and held by 5 WorldCat member libraries worldwide
Abstract: "This paper presents a tutorial introduction to the use of variational methods for inference and learning in graphical models. We present a number of examples of graphical models, including the QMR-DT database, the sigmoid belief network, the Boltzmann machine, and several variants of hidden Markov models, in which it is infeasible to run exact inference algorithms. We then introduce variational methods, showing how upper and lower bounds can be found for local probabilities, and discussing methods for extending these bounds to bounds on global probabilities of interest. Finally we return to the examples and demonstrate how variational algorithms can be formulated in each case."
Discorsi sulle reti neurali e l'apprendimento by Carlotta Domeniconi ( Book )
1 edition published in 2001 in Italian and held by 5 WorldCat member libraries worldwide
Advances in neural information processing systems 4 by IEEE conference on neural information processing systems ( Book )
1 edition published in 1992 in Undetermined and held by 5 WorldCat member libraries worldwide
Advances in neural information processing systems 6 by Annual Conference on Neural Information Processing Systems ( Book )
1 edition published in 1994 in Undetermined and held by 4 WorldCat member libraries worldwide
Convergence results for the EM approach to mixtures of experts architectures by Michael Irwin Jordan ( Book )
3 editions published in 1993 in English and held by 4 WorldCat member libraries worldwide
The Expectation-Maximization (EM) algorithm is an iterative approach to maximum likelihood parameter estimation. Jordan and Jacobs (1993) recently proposed an EM algorithm for the mixture of experts architecture of Jacobs, Jordan, Nowlan and Hinton (1991) and the hierarchical mixture of experts architecture of Jordan and Jacobs (1992). They showed empirically that the EM algorithm for these architectures yields significantly faster convergence than gradient ascent. In the current paper we provide a theoretical analysis of this algorithm. We show that the algorithm can be regarded as a variable metric algorithm with its searching direction having a positive projection on the gradient of the log likelihood. We also analyze the convergence of the algorithm and provide an explicit expression for the convergence rate. In addition, we describe an acceleration technique that yields a significant speedup in simulation experiments
Foundations and Trends Graphical Models, Exponential Families, and Variational Methods ( )
2 editions published in 2008 in English and held by 4 WorldCat member libraries worldwide
Learning spectral clustering by Francis R Bach ( Book )
1 edition published in 2003 in English and held by 4 WorldCat member libraries worldwide
On semidefinite relaxation for normalized k-cut and connections to spectral clustering by Eric P Xing ( Book )
1 edition published in 2003 in English and held by 4 WorldCat member libraries worldwide
 
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Alternative Names
Jordan, M. 1956-
Jordan, M. I. 1956-
Jordan, Michael 1956-
Jordan, Michael I.
Jordan, Michael I. 1956-
Languages
English (92)
Italian (1)
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