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» Dynamically Adapting Kernels in Support Vector Machines
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HCI
2007
15 years 5 months ago
Augmenting Cognition: Reviewing the Symbiotic Relation Between Man and Machine
Abstract. One of the goals of augmented cognition is creation of adaptive human-machine collaboration that continually optimizes performance of the human-machine system. Augmented ...
Tjerk de Greef, Kees van Dongen, Marc Grootjen, Ja...
140
Voted
TIP
2010
141views more  TIP 2010»
14 years 10 months ago
Efficient Particle Filtering via Sparse Kernel Density Estimation
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Amit Banerjee, Philippe Burlina
KDD
2000
ACM
153views Data Mining» more  KDD 2000»
15 years 7 months ago
The generalized Bayesian committee machine
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...
Volker Tresp
166
Voted
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
15 years 7 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
154
Voted
SSPR
2010
Springer
15 years 2 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...