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143
Voted
CORR
2011
Springer
169views Education» more  CORR 2011»
14 years 9 months ago
Upper Bounds for Maximally Greedy Binary Search Trees
At SODA 2009, Demaine et al. presented a novel connection between binary search trees (BSTs) and subsets of points on the plane. This connection was independently discovered by Der...
Kyle Fox
JPDC
2008
129views more  JPDC 2008»
15 years 2 months ago
A framework for scalable greedy coloring on distributed-memory parallel computers
We present a scalable framework for parallelizing greedy graph coloring algorithms on distributed-memory computers. The framework unifies several existing algorithms and blends a ...
Doruk Bozdag, Assefaw Hadish Gebremedhin, Fredrik ...
132
Voted
ICML
2008
IEEE
16 years 3 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
135
Voted
CORR
2010
Springer
94views Education» more  CORR 2010»
15 years 1 months ago
When LP is the Cure for Your Matching Woes: Improved Bounds for Stochastic Matchings
Abstract Consider a random graph model where each possible edge e is present independently with some probability pe. Given these probabilities, we want to build a large/heavy match...
Nikhil Bansal, Anupam Gupta, Jian Li, Juliá...
CORR
2008
Springer
186views Education» more  CORR 2008»
15 years 2 months ago
Greedy Signal Recovery Review
The two major approaches to sparse recovery are L1-minimization and greedy methods. Recently, Needell and Vershynin developed Regularized Orthogonal Matching Pursuit (ROMP) that ha...
Deanna Needell, Joel A. Tropp, Roman Vershynin