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ACL
2009
13 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...
CORR
2012
Springer
232views Education» more  CORR 2012»
12 years 1 months ago
Smoothing Proximal Gradient Method for General Structured Sparse Learning
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbone...
TOG
2012
246views Communications» more  TOG 2012»
11 years 8 months ago
Continuous penalty forces
We present a simple algorithm to compute continuous penalty forces to determine collision response between rigid and deformable models bounded by triangle meshes. Our algorithm co...
Min Tang, Dinesh Manocha, Miguel A. Otaduy, Ruofen...
PAMI
2008
137views more  PAMI 2008»
13 years 6 months ago
IRGS: Image Segmentation Using Edge Penalties and Region Growing
This paper proposes an image segmentation method named iterative region growing using semantics (IRGS), which is characterized by two aspects. First, it uses graduated increased ed...
Qiyao Yu, David A. Clausi
ICA
2010
Springer
13 years 7 months ago
Consistent Wiener Filtering: Generalized Time-Frequency Masking Respecting Spectrogram Consistency
Wiener filtering is one of the most widely used methods in audio source separation. It is often applied on time-frequency representations of signals, such as the short-time Fourier...
Jonathan Le Roux, Emmanuel Vincent, Yuu Mizuno, Hi...