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NIPS
2004
13 years 8 months ago
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
We consider the situation in semi-supervised learning, where the "label sampling" mechanism stochastically depends on the true response (as well as potentially on the fe...
Saharon Rosset, Ji Zhu, Hui Zou, Trevor Hastie
ESOP
2007
Springer
14 years 1 months ago
Dependent Types for Low-Level Programming
In this paper, we describe the key principles of a dependent type system for low-level imperative languages. The major contributions of this work are (1) a sound type system that c...
Jeremy Condit, Matthew Harren, Zachary R. Anderson...
COLING
2010
13 years 2 months ago
Phrase Structure Parsing with Dependency Structure
In this paper we present a novel phrase structure parsing approach with the help of dependency structure. Different with existing phrase parsers, in our approach the inference pro...
Zhiguo Wang, Chengqing Zong
UAI
2008
13 years 9 months ago
Efficient Inference in Persistent Dynamic Bayesian Networks
Numerous temporal inference tasks such as fault monitoring and anomaly detection exhibit a persistence property: for example, if something breaks, it stays broken until an interve...
Tomás Singliar, Denver Dash
IEEEARES
2006
IEEE
14 years 1 months ago
Modeling Dependable Systems using Hybrid Bayesian Networks
A hybrid Bayesian Network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment the models are...
Martin Neil, Manesh Tailor, Norman E. Fenton, Davi...