Papers
Integration Methods and Optimization Algorithms
Damien Scieur, Vincent Roulet, Francis Bach et al.
Interactive Submodular Bandit
Lin Chen, Andreas Krause, Amin Karbasi
Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning
Shixiang (Shane) Gu, Timothy Lillicrap, Richard E Turner et al.
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts
Raymond Yeh, Jinjun Xiong, Wen-Mei Hwu et al.
Introspective Classification with Convolutional Nets
Long Jin, Justin Lazarow, Zhuowen Tu
Invariance and Stability of Deep Convolutional Representations
Alberto Bietti, Julien Mairal
Inverse Filtering for Hidden Markov Models
Robert Mattila, Cristian Rojas, Vikram Krishnamurthy et al.
Inverse Reward Design
Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel et al.
Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?
Cameron Musco, David Woodruff
Is the Bellman residual a bad proxy?
Matthieu Geist, Bilal Piot, Olivier Pietquin
Joint distribution optimal transportation for domain adaptation
Nicolas Courty, Rémi Flamary, Amaury Habrard et al.
Kernel Feature Selection via Conditional Covariance Minimization
Jianbo Chen, Mitchell Stern, Martin J. Wainwright et al.
Kernel functions based on triplet comparisons
Matthäus Kleindessner, Ulrike von Luxburg
K-Medoids For K-Means Seeding
James Newling, François Fleuret
k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and Algorithms
Cong Han Lim, Stephen Wright
Label Distribution Learning Forests
Wei Shen, KAI ZHAO, Yilu Guo et al.
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks
Zelun Luo, Yuliang Zou, Judy Hoffman et al.
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
Nanyang Ye, Zhanxing Zhu, Rafal Mantiuk
Language Modeling with Recurrent Highway Hypernetworks
Joseph Suarez
Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences
Kinjal Basu, Ankan Saha, Shaunak Chatterjee
Learned D-AMP: Principled Neural Network based Compressive Image Recovery
Chris Metzler, Ali Mousavi, Richard Baraniuk
Learned in Translation: Contextualized Word Vectors
Bryan McCann, James Bradbury, Caiming Xiong et al.
Learning Active Learning from Data
Ksenia Konyushkova, Raphael Sznitman, Pascal Fua
Learning Affinity via Spatial Propagation Networks
Sifei Liu, Shalini De Mello, Jinwei Gu et al.
Learning a Multi-View Stereo Machine
Abhishek Kar, Christian Häne, Jitendra Malik