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AAAI
2010
15 years 6 months ago
Compressing POMDPs Using Locality Preserving Non-Negative Matrix Factorization
Partially Observable Markov Decision Processes (POMDPs) are a well-established and rigorous framework for sequential decision-making under uncertainty. POMDPs are well-known to be...
Georgios Theocharous, Sridhar Mahadevan
121
Voted
ECIR
2007
Springer
15 years 6 months ago
A Study of Global Inference Algorithms in Multi-document Summarization
Abstract. In this work we study the theoretical and empirical properties of various global inference algorithms for multi-document summarization. We start by defining a general fr...
Ryan T. McDonald
137
Voted
ECIR
2007
Springer
15 years 6 months ago
Multinomial Randomness Models for Retrieval with Document Fields
Document fields, such as the title or the headings of a document, offer a way to consider the structure of documents for retrieval. Most of the proposed approaches in the literatu...
Vassilis Plachouras, Iadh Ounis
ICMLA
2008
15 years 6 months ago
Prediction-Directed Compression of POMDPs
High dimensionality of belief space in Partially Observable Markov Decision Processes (POMDPs) is one of the major causes that severely restricts the applicability of this model. ...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
172
Voted
IPCO
2008
221views Optimization» more  IPCO 2008»
15 years 6 months ago
A Comparative Study of Linear and Semidefinite Branch-and-Cut Methods for Solving the Minimum Graph Bisection Problem
Abstract. Semidefinite relaxations are known to deliver good approximations for combinatorial optimization problems like graph bisection. Using the spectral bundle method it is pos...
Michael Armbruster, Marzena Fügenschuh, Chris...