Automatic Node Selection for Deep Neural Networks using Group Lasso Regularization

M. Yuan and Y. Lin, “Model selection and estimation in regression with grouped variables,” Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 68, no. 1, pp. 49-67, 2006

2006

Earlier work this paper cites.

G. E. Hinton, S. Osindero, and Y. Teh, “A fast learning algorithm for deep belief nets,” Neural Computation, vol. 18, pp. 1527-1554, 2006

2006

Earlier work this paper cites.

D. Povey, D. Kanevsky, B. Kingsbury, B. Ramabhadran, G. Saon, and K. Visweswariah, “Boosted MMI for model and feature space discriminative training,” in Proc. ICASSP, 2008, pp. 4057-4060

2008

Earlier work this paper cites.

J. Xue, J. Li, and Y. Gong, “Restructuring of deep neural network acoustic models with singular value decomposition,” in Proc. INTERSPPECH, 2013, pp. 2365-2369

2013

Earlier work this paper cites.

N. Simon, J. Friedman, T. Hastie, and R. Tibshirani, “A sparse-group lasso” Journal of Computational and Graphical Statistics, vol. 22, no. 2, pp. 231-245, 2013

2013

Cited alongside, same era.

T. Ochiai, S. Matsuda, X. Lu, C. Hori, and S. Katagiri, “Speaker adaptive training using deep neural networks,” in Proc. ICASSP, 2014, pp. 6349-6353

2014

Cited alongside, same era.

J. Xue, J. Li, D. Yu, M. Seltzer, and Y. Gong, “Singular value decomposition based low-footprint speaker adaptation and personalization for deep neural network,” in Proc. ICASSP, 2014, pp. 6359-6363

2014

Cited alongside, same era.

T. He, Y. Fan, Y. Qian, T. Tan, and Kai Yu, “Reshaping deep neural network for fast decoding by node-pruning,” in Proc. ICASSP, 2014, pp. 245-249

2014

Cited alongside, same era.

T. Ochiai, S. Matsuda, H. Watanabe, X. Lu, C. Hori, and S. Katagiri, “Speaker adaptive training for deep neural networks embedding linear transformation networks,” in Proc. ICASSP, 2015, pp. 4605-4609

2015

Later among the works it cites.

T. Shinozaki and S. Watanabe, “Structure discovery of deep neural network based on evolutionary algorithms,” in Proc. ICASSP, 2015, pp. 4979-4983

2015

Later among the works it cites.

T. Ochiai, S. Matsuda, H. Watanabe, X. Lu, H. Kawai, and S. Katagiri, “Bottleneck linear transformation network adaptation for speaker adaptive training-based hybrid DNN-HMM speech recognizer,” in Proc. ICASSP, 2016, pp. 5015-5019

2016

Closest in time.

S. Scardapane, Danilo Comminiello, Amir Hussain, and Aurelio Uncini, “Group Sparse Regularization for Deep Neural Networks,” arXiv:1607.00485v1 (2016)

Original

2016

Closest in time.