Papers
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.
Interactive Learning from Policy-Dependent Human Feedback
James MacGlashan, Mark K. Ho, Robert Loftin et al.
iSurvive: An Interpretable, Event-time Prediction Model for mHealth
Walter H. Dempsey, Alexander Moreno, Christy K. Scott et al.
Iterative Machine Teaching
Weiyang Liu, Bo Dai, Ahmad Humayun et al.
Joint Dimensionality Reduction and Metric Learning: A Geometric Take
Mehrtash Harandi, Mathieu Salzmann, Richard Hartley
Just Sort It! A Simple and Effective Approach to Active Preference Learning
Lucas Maystre, Matthias Grossglauser
Kernelized Support Tensor Machines
Lifang He, Chun-Ta Lu, Guixiang Ma et al.
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
Rakshit Trivedi, Hanjun Dai, Yichen Wang et al.
Language Modeling with Gated Convolutional Networks
Yann N. Dauphin, Angela Fan, Michael Auli et al.
Large-Scale Evolution of Image Classifiers
Esteban Real, Sherry Moore, Andrew Selle et al.