Parallel deep neural network training for LVCSR tasks using blue gene/Q
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Tara N. Sainath | Brian Kingsbury | Bhuvana Ramabhadran | George Saon | Michael Picheny | John A. Gunnels | I-Hsin Chung | Upendra V. Chaudhari | Vernon Austel
[1] Jun Doi. Peta-scale Lattice Quantum Chromodynamics on a Blue Gene/Q supercomputer , 2012, 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.
[2] Tara N. Sainath,et al. Kernel methods match Deep Neural Networks on TIMIT , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[3] Nicol N. Schraudolph,et al. Fast Curvature Matrix-Vector Products for Second-Order Gradient Descent , 2002, Neural Computation.
[4] Michael Gschwind,et al. Blue Gene/Q: design for sustained multi-petaflop computing , 2012, ICS '12.
[5] Brian Kingsbury,et al. Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.
[6] Myron Flickner,et al. Compass: A scalable simulator for an architecture for cognitive computing , 2012, 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.
[7] Navdeep Jaitly,et al. Application of Pretrained Deep Neural Networks to Large Vocabulary Speech Recognition , 2012, INTERSPEECH.
[8] Dong Yu,et al. Conversational Speech Transcription Using Context-Dependent Deep Neural Networks , 2012, ICML.
[9] George Saon,et al. A comparison of two optimization techniques for sequence discriminative training of deep neural networks , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[10] Brian Kingsbury,et al. The IBM Attila speech recognition toolkit , 2010, 2010 IEEE Spoken Language Technology Workshop.
[11] Tara N. Sainath,et al. Scalable Minimum Bayes Risk Training of Deep Neural Network Acoustic Models Using Distributed Hessian-free Optimization , 2012, INTERSPEECH.
[12] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[13] Ebru Arisoy,et al. Low-rank matrix factorization for Deep Neural Network training with high-dimensional output targets , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[14] James Martens,et al. Deep learning via Hessian-free optimization , 2010, ICML.
[15] Michael Gschwind,et al. The IBM Blue Gene/Q Compute Chip , 2012, IEEE Micro.
[16] Christina Freytag,et al. Using Mpi Portable Parallel Programming With The Message Passing Interface , 2016 .
[17] Barak A. Pearlmutter. Fast Exact Multiplication by the Hessian , 1994, Neural Computation.
[18] Tara N. Sainath,et al. Deep Neural Networks for Acoustic Modeling in Speech Recognition , 2012 .
[19] Daniel Povey,et al. Krylov Subspace Descent for Deep Learning , 2011, AISTATS.
[20] Tara N. Sainath,et al. Making Deep Belief Networks effective for large vocabulary continuous speech recognition , 2011, 2011 IEEE Workshop on Automatic Speech Recognition & Understanding.
[21] Tara N. Sainath,et al. Accelerating Hessian-free optimization for Deep Neural Networks by implicit preconditioning and sampling , 2013, 2013 IEEE Workshop on Automatic Speech Recognition and Understanding.
[22] Marc'Aurelio Ranzato,et al. Large Scale Distributed Deep Networks , 2012, NIPS.
[23] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[24] Quoc V. Le,et al. On optimization methods for deep learning , 2011, ICML.