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» A Simple Algorithm for Nuclear Norm Regularized Problems
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ACL
2009
13 years 5 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...
CORR
2004
Springer
177views Education» more  CORR 2004»
13 years 7 months ago
Typestate Checking and Regular Graph Constraints
We introduce regular graph constraints and explore their decidability properties. The motivation for regular graph constraints is 1) type checking of changing types of objects in ...
Viktor Kuncak, Martin C. Rinard
STRINGOLOGY
2008
13 years 8 months ago
Usefulness of Directed Acyclic Subword Graphs in Problems Related to Standard Sturmian Words
The class of finite Sturmian words consists of words having particularly simple compressed representation, which is a generalization of the Fibonacci recurrence for Fibonacci word...
Pawel Baturo, Marcin Piatkowski, Wojciech Rytter
MP
2010
154views more  MP 2010»
13 years 5 months ago
A null-space primal-dual interior-point algorithm for nonlinear optimization with nice convergence properties
Abstract. We present a null-space primal-dual interior-point algorithm for solving nonlinear optimization problems with general inequality and equality constraints. The algorithm a...
Xinwei Liu, Yaxiang Yuan
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 1 months ago
Generating large-scale neural networks through discovering geometric regularities
Connectivity patterns in biological brains exhibit many repeating motifs. This repetition mirrors inherent geometric regularities in the physical world. For example, stimuli that ...
Jason Gauci, Kenneth O. Stanley