Papers
Generalizing GANs: A Turing Perspective
Roderich Gross, Yue Gu, Wei Li et al.
Generating steganographic images via adversarial training
Jamie Hayes, George Danezis
Generative Local Metric Learning for Kernel Regression
Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim et al.
Geometric Descent Method for Convex Composite Minimization
Shixiang Chen, Shiqian Ma, Wei Liu
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks
Federico Monti, Michael Bronstein, Xavier Bresson
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models
Alex M Lamb, Devon Hjelm, Yaroslav Ganin et al.
Good Semi-supervised Learning That Requires a Bad GAN
Zihang Dai, Zhilin Yang, Fan Yang et al.
GP CaKe: Effective brain connectivity with causal kernels
Luca Ambrogioni, Max Hinne, Marcel Van Gerven et al.
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon S Du, Chi Jin, Jason Lee et al.
Gradient descent GAN optimization is locally stable
Vaishnavh Nagarajan, J. Zico Kolter
Gradient Episodic Memory for Continual Learning
David Lopez-Paz, Marc'Aurelio Ranzato
Gradient Methods for Submodular Maximization
Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi
Gradients of Generative Models for Improved Discriminative Analysis of Tandem Mass Spectra
John T Halloran, David M Rocke
Graph Matching via Multiplicative Update Algorithm
Bo Jiang, Jin Tang, Chris Ding et al.
Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees
Francesco Locatello, Michael Tschannen, Gunnar Raetsch et al.
Group Additive Structure Identification for Kernel Nonparametric Regression
Chao Pan, Michael Zhu
Group Sparse Additive Machine
Hong Chen, Xiaoqian Wang, Cheng Deng et al.
Hash Embeddings for Efficient Word Representations
Dan Tito Svenstrup, Jonas Hansen, Ole Winther
Hiding Images in Plain Sight: Deep Steganography
Shumeet Baluja
Hierarchical Attentive Recurrent Tracking
Adam Kosiorek, Alex Bewley, Ingmar Posner
Hierarchical Clustering Beyond the Worst-Case
Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn
Hierarchical Implicit Models and Likelihood-Free Variational Inference
Dustin Tran, Rajesh Ranganath, David Blei
Hierarchical Methods of Moments
Matteo Ruffini, Guillaume Rabusseau, Borja Balle
Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods
Veeranjaneyulu Sadhanala, Yu-Xiang Wang, James L Sharpnack et al.
High-Order Attention Models for Visual Question Answering
Idan Schwartz, Alexander Schwing, Tamir Hazan