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» The Shortcut Problem - Complexity and Approximation
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174
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ACL
2009
15 years 4 months ago
Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Yoshimasa Tsuruoka, Jun-ichi Tsujii, Sophia Anania...
168
Voted
AUSAI
2010
Springer
15 years 3 months ago
A Heuristic on Effective and Efficient Clustering on Uncertain Objects
We study the problem of clustering uncertain objects whose locations are uncertain and described by probability density functions. We analyze existing pruning algorithms and experi...
Edward Hung, Lei Xu, Chi-Cheong Szeto
151
Voted
FUIN
2010
143views more  FUIN 2010»
15 years 3 months ago
Cluster Tree Elimination for Distributed Constraint Optimization with Quality Guarantees
Some distributed constraint optimization algorithms use a linear number of messages in the number of agents, but of exponential size. This is often the main limitation for their pr...
Ismel Brito, Pedro Meseguer
CDC
2010
IEEE
106views Control Systems» more  CDC 2010»
15 years 1 months ago
Optimal cross-layer wireless control policies using TD learning
We present an on-line crosslayer control technique to characterize and approximate optimal policies for wireless networks. Our approach combines network utility maximization and ad...
Sean P. Meyn, Wei Chen, Daniel O'Neill
MA
2011
Springer
241views Communications» more  MA 2011»
15 years 1 months ago
On the distribution of the ratio of the largest eigenvalue to the trace of a Wishart matrix
The ratio of the largest eigenvalue divided by the trace of a p×p random Wishart matrix with n degrees of freedom and identity covariance matrix plays an important role in variou...
Boaz Nadler