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IJAR
2006
89views more  IJAR 2006»
15 years 6 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
STACS
2010
Springer
16 years 1 months ago
Two-phase Algorithms for the Parametric Shortest Path Problem
Abstract. A parametric weighted graph is a graph whose edges are labeled with continuous real functions of a single common variable. For any instantiation of the variable, one obta...
Sourav Chakraborty, Eldar Fischer, Oded Lachish, R...
JDA
2006
184views more  JDA 2006»
15 years 6 months ago
Dynamic shortest paths and transitive closure: Algorithmic techniques and data structures
In this paper, we survey fully dynamic algorithms for path problems on general directed graphs. In particular, we consider two fundamental problems: dynamic transitive closure and...
Camil Demetrescu, Giuseppe F. Italiano
DATAMINE
2010
161views more  DATAMINE 2010»
15 years 4 months ago
Predicting labels for dyadic data
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
Aditya Krishna Menon, Charles Elkan
SEMWEB
2009
Springer
16 years 1 months ago
Uncertainty Reasoning for Linked Data
Linked open data offers a set of design patterns and conventions for sharing data across the semantic web. In this position paper we enumerate some key uncertainty representation i...
Dave Reynolds