Sciweavers

ATAL
2011
Springer
12 years 5 months ago
Quality-bounded solutions for finite Bayesian Stackelberg games: scaling up
The fastest known algorithm for solving General Bayesian Stackelberg games with a finite set of follower (adversary) types have seen direct practical use at the LAX airport for o...
Manish Jain, Christopher Kiekintveld, Milind Tambe
ACL
2004
13 years 6 months ago
Wrapping of Trees
We explore the descriptive power, in terms of syntactic phenomena, of a formalism that extends TreeAdjoining Grammar (TAG) by adding a fourth level of hierarchical decomposition t...
James Rogers
ICCAD
1997
IEEE
90views Hardware» more  ICCAD 1997»
13 years 9 months ago
A hierarchical decomposition methodology for multistage clock circuits
† This paper describes a novel methodology to automate the design of the interconnect distribution for multistage clock circuits. We introduce two key ideas. First, a hierarchica...
Gary Ellis, Lawrence T. Pileggi, Rob A. Rutenbar
KBSE
1998
IEEE
13 years 9 months ago
A Visualization Concept for Hierarchical Object Models
Most current object modeling methods and tools have weaknesses both in the concepts of hierarchical decomposition and in the visualization of these hierarchies. Some methods do no...
Stefan Berner, Stefan Joos, Martin Glinz, Martin A...
CIKM
2003
Springer
13 years 10 months ago
Hierarchical graph indexing
Traffic analysis, in the context of Telecommunications or Internet and Web data, is crucial for large network operations. Data in such networks is often provided as large graphs w...
James Abello, Yannis Kotidis
VISSOFT
2005
IEEE
13 years 10 months ago
Interactive Exploration of Semantic Clusters
Using visualization and exploration tools can be of great use for the understanding of a software system when only its source code is available. However, understanding a large sof...
Mircea Lungu, Adrian Kuhn, Tudor Gîrba, Mich...
PKDD
2009
Springer
144views Data Mining» more  PKDD 2009»
13 years 11 months ago
Compositional Models for Reinforcement Learning
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
Nicholas K. Jong, Peter Stone