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FLAIRS
2004
15 years 7 months ago
Semi-Supervised Sequence Classification with HMMs
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...
Shi Zhong
UAI
2000
15 years 7 months ago
Probabilistic State-Dependent Grammars for Plan Recognition
Techniques for plan recognition under uncertainty require a stochastic model of the plangeneration process. We introduce probabilistic state-dependent grammars (PSDGs) to represen...
David V. Pynadath, Michael P. Wellman
JMLR
2010
173views more  JMLR 2010»
15 years 1 months ago
Elliptical slice sampling
Many probabilistic models introduce strong dependencies between variables using a latent multivariate Gaussian distribution or a Gaussian process. We present a new Markov chain Mo...
Iain Murray, Ryan Prescott Adams, David J. C. MacK...
MODELS
2009
Springer
15 years 11 months ago
On-the-Fly Construction, Correctness and Completeness of Model Transformations Based on Triple Graph Grammars
Triple graph grammars (TGGs) are a formal and intuitive concept for the specification of model transformations. Their main advantage is an automatic derivation of operational rule...
Hartmut Ehrig, Claudia Ermel, Frank Hermann, Ulrik...
SEKE
1993
Springer
15 years 10 months ago
Recovering Conceptual Data Models is Human-Intensive
1 To handle the complexity of modern software systems, a software comprehension strategy pointing out the al abstraction level is necessary. In this context, the role of technology...
Fabio Abbattista, Filippo Lanubile, Giuseppe Visag...