Papers
11,015 papers found
Four Things Everyone Should Know to Improve Batch Normalization
Cecilia Summers, Michael J. Dinneen
FreeLB: Enhanced Adversarial Training for Natural Language Understanding
Chen Zhu, Yu Cheng, Zhe Gan et al.
Frequency-based Search-control in Dyna
Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand
From Inference to Generation: End-to-end Fully Self-supervised Generation of Human Face from Speech
Hyeong-Seok Choi, Changdae Park, Kyogu Lee
From Variational to Deterministic Autoencoders
Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari et al.
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary
Yingzhen Yang, Jiahui Yu, Nebojsa Jojic et al.
FSPool: Learning Set Representations with Featurewise Sort Pooling
Yan Zhang, Jonathon Hare, Adam Prügel-Bennett
Functional Regularisation for Continual Learning with Gaussian Processes
Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews et al.
Functional vs. parametric equivalence of ReLU networks
Mary Phuong, Christoph H. Lampert
Gap-Aware Mitigation of Gradient Staleness
Saar Barkai, Ido Hakimi, Assaf Schuster
GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification
Xuwang Yin, Soheil Kolouri, Gustavo K Rohde
GenDICE: Generalized Offline Estimation of Stationary Values
Ruiyi Zhang*, Bo Dai*, Lihong Li et al.
Generalization bounds for deep convolutional neural networks
Philip M. Long, Hanie Sedghi
Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint
Jimmy Ba, Murat Erdogdu, Taiji Suzuki et al.
Generalization through Memorization: Nearest Neighbor Language Models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky et al.
Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition
Jongbin Ryu, Gitaek Kwon, Ming-Hsuan Yang et al.
Generative Models for Effective ML on Private, Decentralized Datasets
Sean Augenstein, H. Brendan McMahan, Daniel Ramage et al.
Generative Ratio Matching Networks
Akash Srivastava, Kai Xu, Michael U. Gutmann et al.
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
Martin Engelcke, Adam R. Kosiorek, Oiwi Parker Jones et al.
Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning
Qing Qu, Yuexiang Zhai, Xiao Li et al.
Geometric Insights into the Convergence of Nonlinear TD Learning
David Brandfonbrener, Joan Bruna
Geom-GCN: Geometric Graph Convolutional Networks
Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang et al.
GLAD: Learning Sparse Graph Recovery
Harsh Shrivastava, Xinshi Chen, Binghong Chen et al.
Global Relational Models of Source Code
Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh et al.
Gradient $\ell_1$ Regularization for Quantization Robustness
Milad Alizadeh, Arash Behboodi, Mart van Baalen et al.