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SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
14 years 11 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
STOC
2010
ACM
185views Algorithms» more  STOC 2010»
15 years 1 months ago
Measuring independence of datasets
Approximating pairwise, or k-wise, independence with sublinear memory is of considerable importance in the data stream model. In the streaming model the joint distribution is give...
Vladimir Braverman, Rafail Ostrovsky
ICML
2004
IEEE
15 years 3 months ago
Online learning of conditionally I.I.D. data
In this work we consider the task of relaxing the i.i.d assumption in online pattern recognition (or classification), aiming to make existing learning algorithms applicable to a ...
Daniil Ryabko
APPROX
2005
Springer
122views Algorithms» more  APPROX 2005»
15 years 3 months ago
Finding a Maximum Independent Set in a Sparse Random Graph
We consider the problem of finding a maximum independent set in a random graph. The random graph G, which contains n vertices, is modelled as follows. Every edge is included inde...
Uriel Feige, Eran Ofek
AAAI
2008
15 years 3 days ago
Dormant Independence
The construction of causal graphs from non-experimental data rests on a set of constraints that the graph structure imposes on all probability distributions compatible with the gr...
Ilya Shpitser, Judea Pearl