Papers
A Comparison of Word-based and Context-based Representations for Classification Problems in Health Informatics
Aditya Joshi, Sarvnaz Karimi, Ross Sparks et al.
A Compliance Checking Framework for DNN Models
Sunny Verma, Chen Wang, Liming Zhu et al.
A Composable Specification Language for Reinforcement Learning Tasks
Kishor Jothimurugan, Rajeev Alur, Osbert Bastani
A Composite Randomized Incremental Gradient Method
Junyu Zhang, Lin Xiao
A compositional view of questions
Maria Boritchev, Maxime Amblard
2019
ACL
A comprehensive, application-oriented study of catastrophic forgetting in DNNs
B. Pfülb, A. Gepperth
A Comprehensive Overhaul of Feature Distillation
Byeongho Heo, Jeesoo Kim, Sangdoo Yun et al.
A Comprehensive Study of Speech Separation: Spectrogram vs Waveform Separation
Fahimeh Bahmaninezhad, Jian Wu, Rongzhi Gu et al.
A Computational Model of Early Language Acquisition from Audiovisual Experiences of Young Infants
Okko Räsänen, Khazar Khorrami
A Conditional-Gradient-Based Augmented Lagrangian Framework
Alp Yurtsever, Olivier Fercoq, Volkan Cevher
A Condition Number for Joint Optimization of Cycle-Consistent Networks
Leonidas Guibas, Qixing Huang, Zhenxiao Liang
A Content Transformation Block for Image Style Transfer
Dmytro Kotovenko, Artsiom Sanakoyeu, Pingchuan Ma et al.
A Context-based Framework for Modeling the Role and Function of On-line Resource Citations in Scientific Literature
He Zhao, Zhunchen Luo, Chong Feng et al.
A Context-based Framework for Modeling the Role and Function of On-line Resource Citations in Scientific Literature
He Zhao, Zhunchen Luo, Chong Feng et al.
A Continuous Actor-Critic Reinforcement Learning Approach to Flocking with Fixed-Wing UAVs
Chang Wang, Chao Yan, Xiaojia Xiang et al.
A Continuous-Time View of Early Stopping for Least Squares Regression
Alnur Ali, J. Zico Kolter, Ryan J. Tibshirani
A Contrastive Divergence for Combining Variational Inference and MCMC
Francisco Ruiz, Michalis Titsias
A Contribution to the Critique of Liquid Democracy
Ioannis Caragiannis, Evi Micha
A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification
Shaohuai Shi, Kaiyong Zhao, Qiang Wang et al.
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
Sanjeev Arora, Nadav Cohen, Noah Golowich et al.
A Convergence Theory for Deep Learning via Over-Parameterization
Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
Hadi Salman, Greg Yang, Huan Zhang et al.