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ACL
2009
14 years 7 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...
CHB
2011
183views more  CHB 2011»
14 years 1 months ago
Towards an ICT-based psychology: E-psychology
Cognitive science is the scientific domain which studies, analyses, simulates and infers for various aspects, functions and procedures of human mentality such as, thinking, logic, ...
Athanasios Drigas, Lefteris Koukianakis, Yannis Pa...
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
15 years 10 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
TACAS
2007
Springer
99views Algorithms» more  TACAS 2007»
15 years 3 months ago
"Don't Care" Modeling: A Logical Framework for Developing Predictive System Models
Analysis of biological data often requires an understanding of components of pathways and/or networks and their mutual dependency relationships. Such systems are often analyzed and...
Hillel Kugler, Amir Pnueli, Michael J. Stern, E. J...
PADL
2012
Springer
13 years 5 months ago
Virtualizing Real-World Objects in FRP
We begin with a functional reactive programming (FRP) model in which every program is viewed as a signal function that converts a stream of input values into a stream of output va...
Daniel Winograd-Cort, Hai Liu, Paul Hudak