Year  Title  Author 
2017

Deep Stochastic Radar Models 
TA Wheeler, M Holder, H Winner, M Kochenderfer

2017

HardwareDriven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks 
J Li, Z Yuan, Z Li, C Ding, A Ren, Q Qiu, J Draper

2017

Constructing a Deep Regression Model Utilizing Cascaded Sparse Autoencoders and Stochastic Gradient Descent 
A Moussavi

2017

Doubly Stochastic Adversarial Autoencoder 
M Azarafrooz

2017

Doubly Stochastic Variational Inference for Deep Gaussian Processes 
H Salimbeni, M Deisenroth

2017

Stochastic Replica Voting Machine prediction of stable Perovskite and binary alloys 
B Sun, T Mazaheri, J Scher

2017

A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks 
Q Su, X Liao, L Carin

2017

Optimizing Expectations: From Deep Reinforcement Learning To Stochastic Computation Graphs 
P Abbeel

2017

Deep Latent Dirichlet Allocation with TopicLayerAdaptive Stochastic Gradient Riemannian MCMC 
Y Cong, B Chen, H Liu, M Zhou

2017

Unifying the Stochastic Spectral Descent for Restricted Boltzmann Machines with Bernoulli or Gaussian Inputs 
K Fan

2017

Deep learningbased numerical methods for highdimensional parabolic partial differential equations and backward stochastic differential equations 
J Han, A Jentzen

2017

Stochastic reconstruction of an oolitic limestone by generative adversarial networks 
L Mosser, O Dubrule, MJ Blunt

2017

Distributed Bayesian Learning with Stochastic Naturalgradient Expectation Propagation 
L Hasenclever, S Webb, T Lienart, S Vollmer

2017

Stochastic Modeling And Uncertainty Evaluation For Performance Prognosis In Dynamical Systems 
P Wang

2017

Stochastic Decorrelation Constraint Regularized AutoEncoder for Visual Recognition 
F Mao, W Xiong, B Du, L Zhang

2017

Normalization and dropout for stochastic computingbased deep convolutional neural networks 
J Li, Z Yuan, Z Li, A Ren, C Ding, J Draper, S Nazarian

2017

CommunicationEfficient Stochastic Gradient Descent, with Applications to Neural Networks 
D Alistarh, D Grubic, J Li, R Tomioka, M Vojnovic

2017

Learning Approximate Stochastic Transition Models 
Y Song, C Grimm, X Wang, ML Littman

2017

Stochastic Computation Of Gammatone Filter Based Hearing Aid For Impaired People 
R Priyanka, M Ranjani, R Vidhya, S Vigneshwari

2017

Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution 
PW Chou, D Maturana, S Scherer

2017

Toward highperformance online HCCR: a CNN approach with DropDistortion, path signature and spatial stochastic maxpooling 
S Lai, L Jin, W Yang

2017

Stochastic Configuration Networks: Fundamentals and Algorithms 
D Wang, M Li

2017

Simplified Stochastic Feedforward Neural Networks 
K Lee, J Kim, S Chong, J Shin

2017

Area/EnergyEfficient Gammatone Filters Based on Stochastic Computation 
N Onizawa, S Koshita, S Sakamoto, M Abe

2017

Deep Stochastic Configuration Networks: Universal Approximation and Learning Representation 
D Wang, M Li

2017

Motion Prediction Under Multimodality with Conditional Stochastic Networks 
K Fragkiadaki, J Huang, A Alemi, S Vijayanarasimhan

2017

Acceleration Of Convolutional Neural Network Training Using Stochastic Perforation 
L Chang, S Gupta

2017

Evaluation of Stochastic Cascaded IIR Filters 
N Onizawa, S Koshita, S Sakamoto, M Kawamata

2017

Learning Deep Generative Models With Doubly Stochastic Gradient MCMC 
C Du, J Zhu, B Zhang

2017

A New Stochastic Computing Multiplier with Application to Deep Convolutional Neural Networks 
H Sim, J Lee

2016

SEBOOSTBoosting Stochastic Learning Using Subspace Optimization Techniques 
E Richardson, R Herskovitz, B Ginsburg, M Zibulevsky

2016

Stochastic Neural Networks with Monotonic Activation Functions 
S Ravanbakhsh, B Poczos, J Schneider

2016

An Optimized Second Order Stochastic Learning Algorithm for Neural Network Training 
SS Liew, M Khalil

2016

SCDCNN: HighlyScalable Deep Convolutional Neural Network using Stochastic Computing 
A Ren, J Li, Z Li, C Ding, X Qian, Q Qiu, B Yuan

2016

Distributed Bayesian Learning with Stochastic Naturalgradient Expectation Propagation and the Posterior Server 
YW Teh, L Hasenclever, T Lienart, S Vollmer, S Webb

2016

Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning 
S Zheng, Q Meng, T Wang, W Chen, N Yu, ZM Ma

2016

Bimodal First Impressions Recognition using Temporally Ordered Deep Audio and Stochastic Visual Features 
A Subramaniam, V Patel, A Mishra

2016

Stochastic Variational Deep Kernel Learning 
AG Wilson, Z Hu, R Salakhutdinov, EP Xing

2016

Stochastic neuromorphic learning machines for weakly labeled data 
E Neftci

2016

Simple Evolutionary Optimization Can Rival Stochastic Gradient Descent in Neural Networks 
G Morse, KO Stanley

2016

Orthogonal Echo State Networks and stochastic evaluations of likelihoods 
NM Mayer

2016

Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent 
L Wang, Y Yang, MR Min, S Chakradhar

2016

Distributed stochastic optimization for deep learning 
S Zhang

2016

Distributed stochastic optimization for deep learning (thesis) 
S Zhang

2016

Simulation of Bayesian Learning and Inference on Distributed Stochastic Spiking Neural Networks 
K Ahmed, A Shrestha, Q Qiu

2016

Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles 
S Lee, S Purushwalkam, M Cogswell, V Ranjan

2016

Guided Linear Dimensionality Reduction by Stochastic Gradient Descent 
M Richter

2016

Understanding Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning 
A Nguyen, J Yosinski, J Clune

2016

Joint Stochastic Approximation learning of Helmholtz Machines 
H Xu, Z Ou

2016

Distributed Deep Learning Using Synchronous Stochastic Gradient Descent 
D Das, S Avancha, D Mudigere, K Vaidynathan

2016

Designing Reconfigurable LargeScale Deep Learning Systems Using Stochastic Computing 
A Ren, Z Li, Y Wang, Q Qiu, B Yuan

2016

Functional Systems Network Outperforms Qlearning in Stochastic Environment 
AY Sorokin, MS Burtsev

2016

Deep Networks with Stochastic Depth 
G Huang, Y Sun, Z Liu, D Sedra, K Weinberger

2016

Dynamic energyaccuracy tradeoff using stochastic computing in deep neural networks 
K Kim, J Kim, J Yu, J Seo, J Lee, K Choi

2015

Innovation engines: Automated creativity and improved stochastic optimization via deep learning 
A Nguyen, J Yosinski, J Clune

2015

FPGA implementation of a Deep Belief Network architecture for character recognition using stochastic computation 
K Sanni, G Garreau, JL Molin, AG Andreou

2015

Systems And Methods For Combining Stochastic Average Gradient And HessianFree Optimization For Sequence Training Of Deep … 
P Dognin, V Goel

2015

Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking 
TH Wen, M Gašic, D Kim, N Mrkšic, PH Su, D Vandyke

2015

HighOrder Stochastic Gradient Thermostats for Bayesian Learning of Deep Models 
C Li, C Chen, K Fan, L Carin

2015

Analysis and Synthesis of Stochastic Nonlinear Systems 
S Zhong, J Cheng, J Cao, P Balasubramaniam, H Du

2015

Microscopic Advances with LargeScale Learning: Stochastic Optimization for CryoEM 
A Punjani, MA Brubaker

2015

Evaluating unsupervised fault detection in selfhealing systems using stochastic primitives 
C Schneider, AD Barker, SA Dobson

2015

Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks 
C Li, C Chen, D Carlson, L Carin

2015

Fast SecondOrder Stochastic Backpropagation for Variational Inference 
K Fan, Z Wang, J Beck, J Kwok, K Heller

2015

On Graduated Optimization for Stochastic NonConvex Problems 
E Hazan, KY Levy, S Shalev

2015

ASDLM: An Asynchronous Stochastic Learning Algorithm For Fast Distributed Learning 
M Khalil

2015

Learning Deep Generative Models with Doubly Stochastic MCMC 
C Du, J Zhu, B Zhang

2015

Stochastic Interpretation of Quasiperiodic Eventbased Systems 
H Mostafa, G Indiveri

2015

" Oddball SGD": Novelty Driven Stochastic Gradient Descent for Training Deep Neural Networks 
AJR Simpson

2015

Perturbed Iterate Analysis for Asynchronous Stochastic Optimization 
H Mania, X Pan, D Papailiopoulos, B Recht

2015

Large Scale Optimization with Proximal Stochastic NewtonType Gradient Descent 
Z Shi, R Liu

2015

Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization 
X Lian, Y Huang, Y Li, J Liu

2015

Accelerating Stochastic Gradient Descent via Online Learning to Sample 
G Bouchard, T Trouillon, J Perez, A Gaidon

2015

Stochastic Spectral Descent for Restricted Boltzmann Machines 
D Carlson, V Cevher, L Carin

2015

Training Deep Gaussian Processes using Stochastic Expectation Propagation and Probabilistic Backpropagation 
TD Bui, JM Hernández

2015

Stochastic gradient method with accelerated stochastic dynamics 
M Ohzeki

2015

GSNs: Generative Stochastic Networks 
G Alain, Y Bengio, L Yao, J Yosinski

2015

Beyond Convexity: Stochastic QuasiConvex Optimization 
E Hazan, KY Levy, S Shalev

2015

FPGA emulation of a spikebased, stochastic system for realtime image dewarping 
JL Molin, T Figliolia, K Sanni, I Doxas, A Andreou

2015

VLSI Implementation of Deep Neural Network Using Integral Stochastic Computing 
A Ardakani, F Leduc

2015

Fast largescale optimization by unifying stochastic gradient and quasiNewton methods 
B Poole, S EDU

2014

ADASECANT: Robust Adaptive Secant Method for Stochastic Gradient 
C Gulcehre, Y Bengio

2014

Investigation of stochastic HessianFree optimization in Deep neural networks for speech recognition 
Z You, B Xu

2014

Improving training time of deep neural networkwith asynchronous averaged stochastic gradient descent 
Z You, B Xu

2014

General Stochastic Networks for Classification 
M Zöhrer, F Pernkopf

2014

Stochastic Descent Analysis of Representation Learning Algorithms 
RM Golden

2014

A Simple Stochastic Algorithm for Structural Features Learning 
J Macák, O Drbohlav
