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APPROX
2008
Springer
119views Algorithms» more  APPROX 2008»
15 years 6 months ago
The Complexity of Distinguishing Markov Random Fields
Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...
Andrej Bogdanov, Elchanan Mossel, Salil P. Vadhan
CDC
2010
IEEE
186views Control Systems» more  CDC 2010»
14 years 11 months ago
Approximation and limiting behavior of random models
In this paper, we investigate limiting behavior of linear dynamic systems driven by random stochastic matrices. We introduce and study the new concepts of partial ergodicity and 1-...
Behrouz Touri, Angelia Nedic
ICML
2004
IEEE
16 years 5 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
STOC
1990
ACM
108views Algorithms» more  STOC 1990»
15 years 8 months ago
Optimal Randomized Algorithms for Local Sorting and Set-Maxima
We present randomized algorithms for two sorting problems. In the local sorting problem, a graph is given in which each vertex is assigned an element of a total order, and the task...
Wayne Goddard, Valerie King, Leonard J. Schulman
NAACL
2007
15 years 5 months ago
Randomized Decoding for Selection-and-Ordering Problems
The task of selecting and ordering information appears in multiple contexts in text generation and summarization. For instance, methods for title generation construct a headline b...
Pawan Deshpande, Regina Barzilay, David R. Karger