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» Functional Programming in Sublinear Space
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UAI
2008
13 years 11 months ago
Partitioned Linear Programming Approximations for MDPs
Approximate linear programming (ALP) is an efficient approach to solving large factored Markov decision processes (MDPs). The main idea of the method is to approximate the optimal...
Branislav Kveton, Milos Hauskrecht
FOCS
1992
IEEE
14 years 2 months ago
Dynamic Half-Space Reporting, Geometric Optimization, and Minimum Spanning Trees
We describe dynamic data structures for half-space range reporting and for maintaining the minima of a decomposable function. Using these data structures, we obtain efficient dyna...
Pankaj K. Agarwal, David Eppstein, Jirí Mat...
DASIP
2010
13 years 5 months ago
High level design space exploration of RVC codec specifications for multi-core heterogeneous platforms
Nowadays, the design flow of complex signal processing embedded systems starts with a specification of the application by means of a large and sequential program (usually in C/C++...
Christophe Lucarz, Ghislain Roquier, Marco Mattave...
RECOMB
2006
Springer
14 years 10 months ago
Efficient Enumeration of Phylogenetically Informative Substrings
We study the problem of enumerating substrings that are common amongst genomes that share evolutionary descent. For example, one might want to enumerate all identical (therefore co...
Stanislav Angelov, Boulos Harb, Sampath Kannan, Sa...
AIPS
2004
13 years 11 months ago
Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
Branislav Kveton, Milos Hauskrecht