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» Approximability of Probability Distributions
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JNS
2010
61views more  JNS 2010»
14 years 12 months ago
Validity and Failure of the Boltzmann Approximation of Kinetic Annihilation
This paper introduces a new method to show the validity of a continuum description for the deterministic dynamics of many interacting particles. Here the many particle evolution is...
Karsten Matthies, Florian Theil
COMPGEOM
2011
ACM
14 years 5 months ago
Comparing distributions and shapes using the kernel distance
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
STOC
2009
ACM
87views Algorithms» more  STOC 2009»
16 years 2 months ago
Randomly supported independence and resistance
We prove that for any positive integer k, there is a constant ck such that a randomly selected set of cknk log n Boolean vectors with high probability supports a balanced k-wise i...
Per Austrin, Johan Håstad
OL
2011
190views Neural Networks» more  OL 2011»
14 years 8 months ago
On optimality of a polynomial algorithm for random linear multidimensional assignment problem
We demonstrate that the Linear Multidimensional Assignment Problem with iid random costs is polynomially "-approximable almost surely (a. s.) via a simple greedy heuristic, f...
Pavlo A. Krokhmal
ML
2012
ACM
413views Machine Learning» more  ML 2012»
13 years 9 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...