Papers.

MSL: a model for W3C XML Schema

Little Higgs models: New approaches to the hierarchy problem

Optimal bounded disorder

Adaptive control of nonlinearly parameterized systems with a triangular structure

Signatures of primordial helicity in the CMBR

We have studied ways in which helical primordial magnetic fields could be constrained by measurements of the cosmic microwave background radiation (CMBR). If there were helical flows in the primordial plasma at the time of recombination, they would produce parity violating temperature-polarization correlations ($C_l^{TB}$ and $C_l^{EB}$). However, the magnitude of helical flows induced by helical magnetic fields is unobservably small. We discuss an alternate scheme for extracting the helicity of a stochastically homogeneous and isotropic primordial magnetic field using Faraday rotation measure maps of the CMBR and the power spectrum of B-type polarization ($C_l^{BB}$).

A New Proof for the Existence of Mutually Unbiased Bases

Abstract. We develop a strong connection between maximally commuting bases of orthogonal unitary matrices and mutually unbiased bases. A necessary condition of the existence of mutually unbiased bases for any finite dimension is obtained. Then a constructive proof of the existence of mutually unbiased bases for dimensions that are powers of primes is presented. It is also proved that in any dimension d the number of mutually unbiased bases is at most d+1 . An explicit representation of mutually unbiased observables in terms of Pauli matrices are provided for d=2m .

Corpora for Topic Detection and Tracking

Towards a “Universal Dictionary” for Multi-Language Information Retrieval Applications

Searching Large Text Collections

Toward Terminology as Infrastructure

Foundations of information technology in the era of network and mobile computing : IFIP 17th World Computer Congress - TC1 Stream /2nd IFIP International Conference on Theoretical Computer Science (TCS 2002) August 25-30, 2002, Montréal, Québec, Canada

Experimentation in Telelearning Environments: 3 Case Studies

Morphable Multipliers

An Efficient Inclusion-Based Points-To Analysis for Strictly-Typed Languages

Agents, Crawlers, and Web Retrieval

Web Structure, Dynamics and Page Quality

An Introduction to Functional Nets

Yacas: A Do-It-Yourself Symbolic Algebra Environment

Naming in XML Documents.

Predicting levels of stress from biological assessment data: Empirical models from the Eastern Corn Belt Plains, Ohio, Usa

Matchsimile: A flexible approximate matching tool for searching proper names

XQL and proximal nodes

Preface

Deconstructing six-dimensional gauge theories with strongly coupled moose meshes

A Random Structure for Optimum Cache Size Distributed hash table (DHT) Peer-to-Peer design

A generalized mean field algorithm for variational inference in exponential families

The mean field methods, which entail approximating intractable probability distributions variationally with distributions from a tractable family, enjoy high efficiency, guaranteed convergence, and provide lower bounds on the true likelihood. But due to requirement for model-specific derivation of the optimization equations and unclear inference quality in various models, it is not widely used as a generic approximate inference algorithm. In this paper, we discuss a generalized mean field theory on variational approximation to a broad class of intractable distributions using a rich set of tractable distributions via constrained optimization over distribution spaces. We present a class of generalized mean field (GMF) algorithms for approximate inference in complex exponential family models, which entails limiting the optimization over the class of cluster-factorizable distributions. GMF is a generic method requiring no model-specific derivations. It factors a complex model into a set of disjoint variable clusters, and uses a set of canonical fix-point equations to iteratively update the cluster distributions, and converge to locally optimal cluster marginals that preserve the original dependency structure within each cluster, hence, fully decomposed the overall inference problem. We empirically analyzed the effect of different tractable family (clusters of different granularity) on inference quality, and compared GMF with BP on several canonical models. Possible extension to h

What we need from Gordon Brown's billions.

Web Structure, Dynamics and Page Quality

Web Structure and Evolution Web Structure, Age, and Page Quality.

Web Structure, Age and Page Quality

Un análisis de lenguajes de consulta para XML

The Semantic Web and the Integration of Health Data Resources

The Design and Implementation of Zap: A System for Migrating Computing Environments

Take me to your leaders.

Synthesis of Morphable Multipliers

Stop press: things are getting better.

State abstraction for programmable reinforcement learning agents

SIGIR 2002 : proceedings of the Twenty-Fifth Annual International ACM SIGIR Conference on Research and Development in information Retrieval : August 11-15, 2002, Tampere, Finland

Ringing endorsement.

Retention and recruitment. Leaving by the back door.

Recuperación de información: una disciplina con tradicción: una disciplina con tradicción

Recruitment and retention. Slip slidin' away.

Proceedings of the IFIP 17th World Computer Congress - TC1 Stream / 2nd IFIP International Conference on Theoretical Computer Science: Foundations of Information Technology in the Era of Networking and Mobile Computing

Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval

Parallel Objects: Virtualization and in-Process Components

Naval nursing. The shipping news.

Mapping social cyberspaces : measures and maps of Usenet, a computer mediated social space

Lenguajes y Sistemas Informáticos

La Web de España

Java Web Services

Introduction to building and deploying web services on the Java platform, covering SOAP, WSDL, UDDI, JAXM/JAXR and the Apache SOAP/Axis toolchain, aimed at Java enterprise developers.