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COLT
2006
Springer
15 years 1 months ago
Unifying Divergence Minimization and Statistical Inference Via Convex Duality
Abstract. In this paper we unify divergence minimization and statistical inference by means of convex duality. In the process of doing so, we prove that the dual of approximate max...
Yasemin Altun, Alexander J. Smola
80
Voted
OOPSLA
1991
Springer
15 years 1 months ago
Object-Oriented Type Inference
We present a new approach to inferring types in untyped object-oriented programs with inheritance, assignments, and late binding. It guarantees that all messages are understood, a...
Jens Palsberg, Michael I. Schwartzbach
93
Voted
FEGC
2008
84views Biometrics» more  FEGC 2008»
14 years 11 months ago
Structure Inference of Bayesian Networks from Data: A New Approach Based on Generalized Conditional Entropy
We propose a novel algorithm for extracting the structure of a Bayesian network from a dataset. Our approach is based on generalized conditional entropies, a parametric family of e...
Dan A. Simovici, Saaid Baraty
89
Voted
NIPS
2003
14 years 11 months ago
On the Concentration of Expectation and Approximate Inference in Layered Networks
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...
XuanLong Nguyen, Michael I. Jordan
77
Voted
AAAI
2000
14 years 11 months ago
Semantics and Inference for Recursive Probability Models
In recent years, there have been several proposals that extend the expressive power of Bayesian networks with that of relational models. These languages open the possibility for t...
Avi Pfeffer, Daphne Koller