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NIPS
1998
14 years 11 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
ENTCS
2007
101views more  ENTCS 2007»
14 years 9 months ago
Parametric Performance Contracts: Non-Markovian Loop Modelling and an Experimental Evaluation
Even with todays hardware improvements, performance problems are still common in many software systems. An approach to tackle this problem for component-based software architectur...
Heiko Koziolek, Viktoria Firus
QEST
2006
IEEE
15 years 3 months ago
Compositional Performability Evaluation for STATEMATE
Abstract— This paper reports on our efforts to link an industrial state-of-the-art modelling tool to academic state-of-the-art analysis algorithms. In a nutshell, we enable timed...
Eckard Böde, Marc Herbstritt, Holger Hermanns...
ALGORITHMICA
2005
102views more  ALGORITHMICA 2005»
14 years 9 months ago
Effective Routing and Scheduling in Adversarial Queueing Networks
In an adversarial queueing network, the incoming traffic is decided by an adversary, who operates under a reasonable rate restriction. This model provides a valuable, complementar...
Jay Sethuraman, Chung-Piaw Teo
EACL
2006
ACL Anthology
14 years 11 months ago
Edit Machines for Robust Multimodal Language Processing
Multimodal grammars provide an expressive formalism for multimodal integration and understanding. However, handcrafted multimodal grammars can be brittle with respect to unexpecte...
Srinivas Bangalore, Michael Johnston