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IJCNN
2007
IEEE
14 years 3 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
IJON
2011
169views more  IJON 2011»
13 years 3 months ago
Exploiting local structure in Boltzmann machines
Restricted Boltzmann Machines (RBM) are well-studied generative models. For image data, however, standard RBMs are suboptimal, since they do not exploit the local nature of image ...
Hannes Schulz, Andreas Müller 0004, Sven Behn...
HYBRID
2000
Springer
14 years 13 days ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
ACL
2004
13 years 10 months ago
Corpus-Based Induction of Syntactic Structure: Models of Dependency and Constituency
We present a generative model for the unsupervised learning of dependency structures. We also describe the multiplicative combination of this dependency model with a model of line...
Dan Klein, Christopher D. Manning
ACL
2010
13 years 6 months ago
A Hybrid Hierarchical Model for Multi-Document Summarization
Scoring sentences in documents given abstract summaries created by humans is important in extractive multi-document summarization. In this paper, we formulate extractive summariza...
Asli Çelikyilmaz, Dilek Hakkani-Tur