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Model Selection
  • Language: en
  • Pages: 262

Model Selection

  • Type: Book
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  • Published: 2001
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  • Publisher: IMS

None

Discovery Science
  • Language: en
  • Pages: 478

Discovery Science

  • Type: Book
  • -
  • Published: 2003-08-03
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  • Publisher: Springer

This volume contains the papers presented at the 5th International Conference on Discovery Science (DS 2002) held at the Mövenpick Hotel, Lub ̈eck, G- many, November 24-26, 2002. The conference was supported by CorpoBase, DFKI GmbH, and JessenLenz. The conference was collocated with the 13th International Conference on - gorithmic Learning Theory (ALT 2002). Both conferences were held in parallel and shared?ve invited talks as well as all social events. The combination of ALT 2002 and DS 2002 allowed for a comprehensive treatment of recent de- lopments in computational learning theory and machine learning - some of the cornerstones of discovery science. In response to the call for papers 76 submissions were received. The program committee selected 17 submissions as regular papers and 29 submissions as poster presentations of which 27 have been submitted for publication. This selection was based on clarity, signi?cance, and originality, as well as on relevance to the rapidly evolving?eld of discovery science.

Learning from Data
  • Language: en
  • Pages: 444

Learning from Data

Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Artificial Intelligence and Statistics. In the early days of the Workshop series it seemed clear that researchers in AI and statistics had common interests, though with different emphases, goals, and vocabularies. In learning and model selection, for example, a historical goal of AI to build autonomous agents probably contributed to a focus on parameter-free learning systems, which relied little on an external analyst's assumptions about the data. This seemed at odds with statistical strategy, which stemmed from a view that model selection methods were tools to augment, not replace, the abilities...

Computing Science and Statistics
  • Language: en
  • Pages: 595

Computing Science and Statistics

Interface '90 is the continuation of an ext!remely successful symposium series. The series has provided a forum for the interaction of professionals in statistics, computing science, and in numerical methods, wherein they may discuss a wide range of topics at the interface of these disciplines. This, the 22nd Symposium on the Interface: Computing Science and Statistics, was held 16-19 May, 1990 at the Kellogg Center on the campus of Michigan State University and is the third Symposium to be held under the recently organized Interface Foundation of North America. The Interface Board of Directors consists of the nine most recent Symposium Chairs: James E. Gentle, Lynne Billard, David M. Allen,...

Bilinear Stochastic Models and Related Problems of Nonlinear Time Series Analysis
  • Language: en
  • Pages: 275

Bilinear Stochastic Models and Related Problems of Nonlinear Time Series Analysis

The object of the present work is a systematic statistical analysis of bilinear processes in the frequency domain. The first two chapters are devoted to the basic theory of nonlinear functions of stationary Gaussian processes, Hermite polynomials, cumulants and higher order spectra, multiple Wiener-Itô integrals and finally chaotic Wiener-Itô spectral representation of subordinated processes. There are two chapters for general nonlinear time series problems.

Discretization and MCMC Convergence Assessment
  • Language: en
  • Pages: 201

Discretization and MCMC Convergence Assessment

The exponential increase in the use of MCMC methods and the corre sponding applications in domains of even higher complexity have caused a growing concern about the available convergence assessment methods and the realization that some of these methods were not reliable enough for all-purpose analyses. Some researchers have mainly focussed on the con vergence to stationarity and the estimation of rates of convergence, in rela tion with the eigenvalues of the transition kernel. This monograph adopts a different perspective by developing (supposedly) practical devices to assess the mixing behaviour of the chain under study and, more particularly, it proposes methods based on finite (state spac...

God in the Age of Science?
  • Language: en
  • Pages: 391

God in the Age of Science?

Herman Philipse puts forward a powerful new critique of belief in God. He examines the strategies that have been used for the philosophical defence of religious belief, and by careful reasoning casts doubt on the legitimacy of relying on faith instead of evidence, and on probabilistic arguments for the existence of God.

Model Selection and Inference
  • Language: en
  • Pages: 373

Model Selection and Inference

Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.

Stochastic Networks
  • Language: en
  • Pages: 305

Stochastic Networks

Two of the most exciting topics of current research in stochastic networks are the complementary subjects of stability and rare events - roughly, the former deals with the typical behavior of networks, and the latter with significant atypical behavior. Both are classical topics, of interest since the early days of queueing theory, that have experienced renewed interest mo tivated by new applications to emerging technologies. For example, new stability issues arise in the scheduling of multiple job classes in semiconduc tor manufacturing, the so-called "re-entrant lines;" and a prominent need for studying rare events is associated with the design of telecommunication systems using the new ATM...

Agent Autonomy
  • Language: en
  • Pages: 291

Agent Autonomy

Autonomy is a characterizing notion of agents, and intuitively it is rather unambiguous. The quality of autonomy is recognized when it is perceived or experienced, yet it is difficult to limit autonomy in a definition. The desire to build agents that exhibit a satisfactory quality of autonomy includes agents that have a long life, are highly independent, can harmonize their goals and actions with humans and other agents, and are generally socially adept. Agent Autonomy is a collection of papers from leading international researchers that approximate human intuition, dispel false attributions, and point the way to scholarly thinking about autonomy. A wide array of issues about sharing control and initiative between humans and machines, as well as issues about peer level agent interaction, are addressed.