Papers
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares
Junqi Tang, Mohammad Golbabaee, Mike E. Davies
Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling
Hairong Liu, Zhenyao Zhu, Xiangang Li et al.
Grammar Variational Autoencoder
Matt J. Kusner, Brooks Paige, José Miguel Hernández-Lobato
Graph-based Isometry Invariant Representation Learning
Renata Khasanova, Pascal Frossard
GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization
Li Shen, Wei Liu, Ganzhao Yuan et al.
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
Andrew An Bian, Joachim M. Buhmann, Andreas Krause et al.
Hierarchy Through Composition with Multitask LMDPs
Andrew M. Saxe, Adam C. Earle, Benjamin Rosman
High Dimensional Bayesian Optimization with Elastic Gaussian Process
Santu Rana, Cheng Li, Sunil Gupta et al.
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation
Zhuoran Yang, Krishnakumar Balasubramanian, Han Liu
High-Dimensional Structured Quantile Regression
Vidyashankar Sivakumar, Arindam Banerjee
High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm
Rongda Zhu, Lingxiao Wang, Chengxiang Zhai et al.
How to Escape Saddle Points Efficiently
Chi Jin, Rong Ge, Praneeth Netrapalli et al.
Hyperplane Clustering via Dual Principal Component Pursuit
Manolis C. Tsakiris, René Vidal
Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables
Bryant Chen, Daniel Kumor, Elias Bareinboim
Identifying Best Interventions through Online Importance Sampling
Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis et al.
Identify the Nash Equilibrium in Static Games with Random Payoffs
Yichi Zhou, Jialian Li, Jun Zhu
Image-to-Markup Generation with Coarse-to-Fine Attention
Yuntian Deng, Anssi Kanervisto, Jeffrey Ling et al.
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions
Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov et al.
Improving Gibbs Sampler Scan Quality with DoGS
Ioannis Mitliagkas, Lester Mackey
Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution
Po-Wei Chou, Daniel Maturana, Sebastian Scherer
Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms
Arturs Backurs, Christos Tzamos
Innovation Pursuit: A New Approach to the Subspace Clustering Problem
Mostafa Rahmani, George Atia
Input Convex Neural Networks
Brandon Amos, Lei Xu, J. Zico Kolter
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability
Jakob N. Foerster, Justin Gilmer, Jascha Sohl-Dickstein et al.