Table 4 Bibliographic summary of papers in ACM digital library

Zeng Yu and Tianrui Li and Ning Yu and Yi Pan and Hongmei Chen and Bing Liu

Reconstruction of hidden representation for robust feature extraction [26]

Deep architectures, auto-encoders, feature representation, reconstruction of hidden representation, unsupervised learning

ACM Trans. Intell. Syst. Technol.

Rahim Mammadli and Felix Wolf and Ali Jannesari

The art of getting deep neural networks in shape [27]

Deep neural networks, computer vision, parallel processing

ACM Trans. Archit. Code Optim.

Tinghui Zhou and Richard Tucker and John Flynn and Graham Fyffe and Noah Snavely

Stereo magnification: learning view synthesis using multiplane images [28]

Deep learning, view extrapolation

ACM Trans. Graph.

Zipei Fan and Xuan Song and Tianqi Xia and Renhe Jiang and Ryosuke Shibasaki and Ritsu Sakuramachi

Online deep ensemble learning for predicting citywide human mobility [29]

Deep learning, ensemble learning, human mobility modeling, intelligent surveillance, urban computing

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

Rana Hanocka and Noa Fish and Zhenhua Wang and Raja Giryes and Shachar Fleishman and Daniel Cohen-Or

ALIGNet: partial-shape agnostic alignment via unsupervised learning [30]

Deep learning, self-supervised learning, shape deformation

ACM Trans. Graph.

Mengwei Xu and Feng Qian and Qiaozhu Mei and Kang Huang and Xuanzhe Liu

DeepType: on-device deep learning for input personalization service with minimal privacy concern [31]

Deep Learning, Mobile Computing, Personalization

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

Thomas E. Potok and Catherine Schuman and Steven Young and Robert Patton and Federico Spedalieri and Jeremy Liu and Ke-Thia Yao and Garrett Rose and Gangotree Chakma

A study of complex deep learning networks on high-performance, neuromorphic, and quantum computers [32]

Deep learning, high-performance computing, neuromorphic computing, quantum computing

J. Emerg. Technol. Comput. Syst.

Samira Pouyanfar and Saad Sadiq and Yilin Yan and Haiman Tian and Yudong Tao and Maria Presa Reyes and Mei-Ling Shyu and Shu-Ching Chen and S. S. Iyengar

A survey on deep learning: algorithms, techniques, and applications [33]

Deep learning, big data, distributed processing, machine learning, neural networks, survey

ACM Comput. Surv.

Yonglong Tian and Guang-He Lee and Hao He and Chen-Yu Hsu and Dina Katabi

RF-based fall monitoring using convolutional neural networks [34]

Deep learning, Device–free, Fall Detection

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

Probir Roy and Shuaiwen Leon Song and Sriram Krishnamoorthy and Abhinav Vishnu and Dipanjan Sengupta and Xu Liu

NUMA-Caffe: NUMA-aware deep learning neural networks [35]

Deep learning, NUMA, neural network, stochastic gradient descent

ACM Trans. Archit. Code Optim.

Charles Lovering and Anqi Lu and Cuong Nguyen and Huyen Nguyen and David Hurley and Emmanuel Agu

Fact or fiction [36]

Deep learning, natural language processing, sentiment analysis, social collaboration, subjectivity classification, text classification, web system

Proc. ACM Hum.-Comput. Interact.

Heli Ben-Hamu and Haggai Maron and Itay Kezurer and Gal Avineri and Yaron Lipman

Multi-chart generative surface modeling [37]

Deep learning, generative adveserial networks, shape generation

ACM Trans. Graph.

Weifeng Ge and Bingchen Gong and Yizhou Yu

Image super-resolution via deterministic-stochastic synthesis and local statistical rectification [38]

Deep learning, deterministic component, image superresolution, local correlation matrix, local gram matrix, stochastic component

ACM Trans. Graph.

Peter Hedman and Julien Philip and True Price and Jan-Michael Frahm and George Drettakis and Gabriel Brostow

Deep blending for free-viewpoint image-based rendering [39]

Deep learning, free-viewpoint, image-based rendering

ACM Trans. Graph.

Kalaivani Sundararajan and Damon L. Woodard

Deep learning for biometrics: a survey [40]

Deep learning, autoencoders, convolutional neural networks, deep belief nets, face recognition, feature learning, speaker recognition

ACM Comput. Surv.

Hyungjun Kim and Taesu Kim and Jinseok Kim and Jae-Joon Kim

Deep neural network optimized to resistive memory with nonlinear current–voltage characteristics [41]

Deep neural network, I-V nonlinearity, nonvolatile memory, perceptron

J. Emerg. Technol. Comput. Syst.

Cheng Wang and Haojin Yang and Christoph Meinel

Image captioning with deep bidirectional LSTMs and multi-task learning [42]

Deep learning, LSTM, image captioning, multimodal representations, mutli-task learning

ACM Trans. Multimedia Comput. Commun. Appl.

Shuochao Yao and Yiran Zhao and Huajie Shao and Aston Zhang and Chao Zhang and Shen Li and Tarek Abdelzaher

RDeepSense: reliable deep mobile computing models with uncertainty estimations [43]

Deep Learning, Internet-of-Things, Mobile Computing, Reliability, Uncertainty Estimation

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

Dongyu Liu and Weiwei Cui and Kai Jin and Yuxiao Guo and Huamin Qu

DeepTracker: visualizing the training process of convolutional neural networks [44]

Deep learning, correlation analysis, multiple time series, training process, visual analytics

ACM Trans. Intell. Syst. Technol.

Li Yi and Haibin Huang and Difan Liu and Evangelos Kalogerakis and Hao Su and Leonidas Guibas

Deep part induction from articulated object pairs [45]

Deep learning, differentiable sequential RANSAC, motion based part segmentation, shape correspondences

ACM Trans. Graph.

Nanxuan Zhao and Ying Cao and Rynson W. H. Lau

What characterizes personalities of graphic designs? [46]

Deep learning, graphic design, personality

ACM Trans. Graph.

Jiwei Tan and Xiaojun Wan and Hui Liu and Jianguo Xiao

QuoteRec: toward quote recommendation for writing [47]

Deep learning, LSTM, document recommendation, quote recommendation

ACM Trans. Inf. Syst.

Yanru Qu and Bohui Fang and Weinan Zhang and Ruiming Tang and Minzhe Niu and Huifeng Guo and Yong Yu and Xiuqiang He

Product-based neural networks for user response prediction over multi-field categorical data [48]

Deep learning, product-based neural network, recommender system

ACM Trans. Inf. Syst.

Kangxue Yin and Hui Huang and Daniel Cohen-Or and Hao Zhang

P2P-NET: bidirectional point displacement net for shape transform [49]

Deep neural network, point cloud processing, point set transform, point-wise displacement

ACM Trans. Graph.

Shuochao Yao and Yiran Zhao and Huajie Shao and Chao Zhang and Aston Zhang and Shaohan Hu and Dongxin Liu and Shengzhong Liu and Lu Su and Tarek Abdelzaher

SenseGAN: enabling deep learning for internet of things with a semi-supervised framework [50]

Deep Learning, GAN, Internet-of-Things, Mobile Computing, Semi-Supervised Learning

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

Shunsuke Saito and Liwen Hu and Chongyang Ma and Hikaru Ibayashi and Linjie Luo and Hao Li

3D hair synthesis using volumetric variational autoencoders [51]

Deep generative model, hair synthesis, single-view modeling, volumetric variational autoencoder

ACM Trans. Graph.

Anpei Chen and Minye Wu and Yingliang Zhang and Nianyi Li and Jie Lu and Shenghua Gao and Jingyi Yu

Deep surface light fields [52]

Deep Neural Network, Image-based Rendering, Real-time Rendering

Proc. ACM Comput. Graph. Interact. Tech.