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ICML
2010
IEEE
15 years 2 months ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
CORR
2010
Springer
116views Education» more  CORR 2010»
15 years 1 months ago
Restricted Isometries for Partial Random Circulant Matrices
In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse an...
Holger Rauhut, Justin K. Romberg, Joel A. Tropp
110
Voted
CCR
2006
117views more  CCR 2006»
15 years 1 months ago
Efficient and decentralized computation of approximate global state
Abstract-- The need for efficient computation of approximate global state lies at the heart of a wide range of problems in distributed systems. Examples include routing in the Inte...
S. Keshav
CPHYSICS
2006
124views more  CPHYSICS 2006»
15 years 1 months ago
Collision-free spatial hash functions for structural analysis of billion-vertex chemical bond networks
State-of-the-art molecular dynamics (MD) simulations generate massive datasets involving billion-vertex chemical bond networks, which makes data mining based on graph algorithms s...
Cheng Zhang, Bhupesh Bansal, Paulo S. Branicio, Ra...
FSS
2006
107views more  FSS 2006»
15 years 1 months ago
Parametric indices of fuzziness for automated image enhancement
This paper presents an automated fuzziness-driven algorithm for image enhancement.A class of parametric indices of fuzziness is introduced, which serves as the optimization criter...
Ioannis K. Vlachos, George D. Sergiadis