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» The Generalized Theory of Model Preference
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178
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ECML
1993
Springer
15 years 11 months ago
Complexity Dimensions and Learnability
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Shan-Hwei Nienhuys-Cheng, Mark Polman
209
Voted
GECCO
2006
Springer
134views Optimization» more  GECCO 2006»
15 years 10 months ago
The Baldwin effect under spatial isolation and autonomous reproduction
The impact of learning on evolution in dynamic environments undergoes recognized stages of the Baldwin Effect although its cause is not clear. To identify it experimentally, we de...
H. L. Peng, J. C. Tay
226
Voted
UAI
2000
15 years 8 months ago
Utilities as Random Variables: Density Estimation and Structure Discovery
Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat o...
Urszula Chajewska, Daphne Koller
198
Voted
WSDM
2010
ACM
215views Data Mining» more  WSDM 2010»
16 years 4 months ago
GeoFolk: Latent spatial semantics in Web 2.0 social media
We describe an approach for multi-modal characterization of social media by combining text features (e.g. tags as a prominent example of short, unstructured text labels) with spat...
Sergej Sizov
167
Voted
OOPSLA
2009
Springer
16 years 1 months ago
Typestate-oriented programming
Objects model the world, and state is fundamental to a faithful modeling. Engineers use state machines to understand and reason about state transitions, but programming languages ...
Jonathan Aldrich, Joshua Sunshine, Darpan Saini, Z...