Papers
Hierarchical Implicit Models and Likelihood-Free Variational Inference
Dustin Tran, Rajesh Ranganath, David Blei
Hierarchical LSTMs with Joint Learning for Estimating Customer Satisfaction from Contact Center Calls
Atsushi Ando, Ryo Masumura, Hosana Kamiyama et al.
Hierarchical LSTM with Adjusted Temporal Attention for Video Captioning
Jingkuan Song, Lianli Gao, Zhao Guo et al.
Hierarchically-Attentive RNN for Album Summarization and Storytelling
Licheng Yu, Mohit Bansal, Tamara Berg
Hierarchically Compositional Kernels for Scalable Nonparametric Learning
Jie Chen, Haim Avron, Vikas Sindhwani
Hierarchically-partitioned Gaussian Process Approximation
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Hierarchical Methods of Moments
Matteo Ruffini, Guillaume Rabusseau, Borja Balle
Hierarchical Multimodal Metric Learning for Multimodal Classification
Heng Zhang, Vishal M. Patel, Rama Chellappa
Hierarchical Recurrent Neural Network for Story Segmentation
Emiru Tsunoo, Peter Bell, Steve Renals
Hierarchical Reinforcement Learning with Parameters
Maciej Klimek, Henryk Michalewski, Piotr Mi\loś
Hierarchical Task Network Planning with Task Insertion and State Constraints
Zhanhao Xiao, Andreas Herzig, Laurent Perrussel et al.
Hierarchy Through Composition with Multitask LMDPs
Andrew M. Saxe, Adam C. Earle, Benjamin Rosman
High Dimensional Bayesian Optimization using Dropout
Cheng Li, Sunil Gupta, Santu Rana et al.
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 Regression with Binary Coefficients. Estimating Squared Error and a Phase Transtition
Gamarnik David, Zadik Ilias
High-Dimensional Structured Quantile Regression
Vidyashankar Sivakumar, Arindam Banerjee
High-dimensional Time Series Clustering via Cross-Predictability
Dezhi Hong, Quanquan Gu, Kamin Whitehouse
High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm
Rongda Zhu, Lingxiao Wang, Chengxiang Zhai et al.
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
High-Quality Tabletop Rearrangement with Overhand Grasps: Hardness Results and Fast Methods
Shuai Han, Nicholas Stiffler, Athanasios Krontiris et al.
High Recall Open IE for Relation Discovery
Hady Elsahar, Christophe Gravier, Frederique Laforest
High-Resolution Image Inpainting Using Multi-Scale Neural Patch Synthesis
Chao Yang, Xin Lu, Zhe Lin et al.
High-risk learning: acquiring new word vectors from tiny data
Aurélie Herbelot, Marco Baroni