Papers
Residual Unfairness in Fair Machine Learning from Prejudiced Data
Nathan Kallus, Angela Zhou
Signal and Noise Statistics Oblivious Orthogonal Matching Pursuit
Sreejith Kallummil, Sheetal Kalyani
Learning Diffusion using Hyperparameters
Dimitris Kalimeris, Yaron Singer, Karthik Subbian et al.
Efficient Neural Audio Synthesis
Nal Kalchbrenner, Erich Elsen, Karen Simonyan et al.
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki et al.
Fast Decoding in Sequence Models Using Discrete Latent Variables
Lukasz Kaiser, Samy Bengio, Aurko Roy et al.
Kronecker Recurrent Units
Cijo Jose, Moustapha Cisse, Francois Fleuret
Composite Functional Gradient Learning of Generative Adversarial Models
Rie Johnson, Tong Zhang
Large-Scale Cox Process Inference using Variational Fourier Features
ST John, James Hensman
WSNet: Compact and Efficient Networks Through Weight Sampling
Xiaojie Jin, Yingzhen Yang, Ning Xu et al.
Regret Minimization for Partially Observable Deep Reinforcement Learning
Peter Jin, Kurt Keutzer, Sergey Levine
Network Global Testing by Counting Graphlets
Jiashun Jin, Zheng Ke, Shengming Luo
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin, Regina Barzilay, Tommi Jaakkola
The Weighted Kendall and High-order Kernels for Permutations
Yunlong Jiao, Jean-Philippe Vert
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang, Zhengyuan Zhou, Thomas Leung et al.
Quickshift++: Provably Good Initializations for Sample-Based Mean Shift
Heinrich Jiang, Jennifer Jang, Samory Kpotufe
Feedback-Based Tree Search for Reinforcement Learning
Daniel Jiang, Emmanuel Ekwedike, Han Liu
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
Zhihao Jia, Sina Lin, Charles R. Qi et al.
Efficient end-to-end learning for quantizable representations
Yeonwoo Jeong, Hyun Oh Song
A Unified Framework for Structured Low-rank Matrix Learning
Pratik Jawanpuria, Bamdev Mishra
Detecting non-causal artifacts in multivariate linear regression models
Dominik Janzing, Bernhard Schölkopf
Pathwise Derivatives Beyond the Reparameterization Trick
Martin Jankowiak, Fritz Obermeyer
Video Prediction with Appearance and Motion Conditions
Yunseok Jang, Gunhee Kim, Yale Song
Differentially Private Matrix Completion Revisited
Prateek Jain, Om Dipakbhai Thakkar, Abhradeep Thakurta
Firing Bandits: Optimizing Crowdfunding
Lalit Jain, Kevin Jamieson