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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...
CMSB
2010
Springer
15 years 1 months ago
Stochasticity in reactions: a probabilistic Boolean modeling approach
Boolean modeling frameworks have long since proved their worth for capturing and analyzing essential characteristics of complex systems. Hybrid approaches aim at exploiting the ad...
Sven Twardziok, Heike Siebert, Alexander Heyl
TSMC
2010
15 years 1 months ago
On Robust Stability of Stochastic Genetic Regulatory Networks With Time Delays: A Delay Fractioning Approach
Robust stability serves as an important regulation mechanism in system biology and synthetic biology. In this paper, the robust stability analysis problem is investigated for a cla...
Yao Wang, Zidong Wang, Jinling Liang
CVPR
2010
IEEE
14 years 3 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu
COORDINATION
2008
Springer
15 years 8 months ago
Formal Analysis of BPMN Via a Translation into COWS
A translation of the Business Process Modeling Notation into the process calculus COWS is presented. The stochastic extension of COWS is then exploited to address quantitative reas...
Davide Prandi, Paola Quaglia, Nicola Zannone