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» Incremental Algorithms for Approximate Compilation
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CVPR
2007
IEEE
14 years 10 months ago
Element Rearrangement for Tensor-Based Subspace Learning
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
IJCAI
2007
13 years 10 months ago
Improving Anytime Point-Based Value Iteration Using Principled Point Selections
Planning in partially-observable dynamical systems (such as POMDPs and PSRs) is a computationally challenging task. Popular approximation techniques that have proved successful ar...
Michael R. James, Michael E. Samples, Dmitri A. Do...
NIPS
2007
13 years 10 months ago
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learn...
Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon
CP
2009
Springer
14 years 3 months ago
Reasoning about Optimal Collections of Solutions
The problem of finding a collection of solutions to a combinatorial problem that is optimal in terms of an inter-solution objective function exists in many application settings. F...
Tarik Hadzic, Alan Holland, Barry O'Sullivan
JAIR
2010
130views more  JAIR 2010»
13 years 3 months ago
Interactive Cost Configuration Over Decision Diagrams
In many AI domains such as product configuration, a user should interactively specify a solution that must satisfy a set of constraints. In such scenarios, offline compilation of ...
Henrik Reif Andersen, Tarik Hadzic, David Pisinger