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» A Framework for Obfuscated Interpretation
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NIPS
2004
15 years 6 months ago
Support Vector Classification with Input Data Uncertainty
This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...
Jinbo Bi, Tong Zhang
TARK
2007
Springer
15 years 10 months ago
Explaining quantity implicatures
We give derivations of two formal models of Gricean Quantity1 implicature and strong exhaustivity (Van Rooij and Schulz, 2004; Schulz and Van Rooij, 2006), in bidirectional optima...
Tikitu de Jager, Robert van Rooij
DAC
2002
ACM
16 years 5 months ago
A factorization-based framework for passivity-preserving model reduction of RLC systems
We present a framework for passivity-preserving model reduction for RLC systems that includes, as a special case, the well-known PRIMA model reduction algorithm. This framework pr...
Q. Su, Venkataramanan Balakrishnan, Cheng-Kok Koh
EDOC
2008
IEEE
15 years 11 months ago
Augmenting the Zachman Enterprise Architecture Framework with a Systemic Conceptualization
The Zachman Framework offers a classification of the models created in an enterprise architecture project. These models form a holistic representation of the organization. Despite...
Alain Wegmann, Anders Kotsalainen, Lionel Matthey,...
SCA
2007
15 years 7 months ago
A decision network framework for the behavioral animation of virtual humans
We introduce a framework for advanced behavioral animation in virtual humans, which addresses the challenging open problem of simulating social interactions between pedestrians in...
Qinxin Yu, Demetri Terzopoulos