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QEST
2008
IEEE
14 years 1 months ago
Symbolic Magnifying Lens Abstraction in Markov Decision Processes
Magnifying Lens Abstraction in Markov Decision Processes ∗ Pritam Roy1 David Parker2 Gethin Norman2 Luca de Alfaro1 Computer Engineering Dept, UC Santa Cruz, Santa Cruz, CA, USA ...
Pritam Roy, David Parker, Gethin Norman, Luca de A...
ICDM
2007
IEEE
121views Data Mining» more  ICDM 2007»
14 years 1 months ago
Finding Predictive Runs with LAPS
We present an extension to the Lasso [9] for binary classification problems with ordered attributes. Inspired by the Fused Lasso [8] and the Group Lasso [10, 4] models, we aim to...
Suhrid Balakrishnan, David Madigan
COMPGEOM
2003
ACM
14 years 19 days ago
Local polyhedra and geometric graphs
We introduce a new realistic input model for geometric graphs and nonconvex polyhedra. A geometric graph G is local if (1) the longest edge at every vertex v is only a constant fa...
Jeff Erickson
ICCAD
1999
IEEE
81views Hardware» more  ICCAD 1999»
13 years 11 months ago
Modeling design constraints and biasing in simulation using BDDs
Constraining and input biasing are frequently used techniques in functional verification methodologies based on randomized simulation generation. Constraints confine the simulatio...
Jun Yuan, Kurt Shultz, Carl Pixley, Hillel Miller,...
KDD
1999
ACM
184views Data Mining» more  KDD 1999»
13 years 11 months ago
Mining Optimized Gain Rules for Numeric Attributes
—Association rules are useful for determining correlations between attributes of a relation and have applications in the marketing, financial, and retail sectors. Furthermore, op...
Sergey Brin, Rajeev Rastogi, Kyuseok Shim