Papers
Improving Sign Random Projections With Additional Information
Keegan Kang, Weipin Wong
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising
Borja Balle, Yu-Xiang Wang
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
Xueru Zhang, Mohammad Mahdi Khalili, Mingyan Liu
Inductive Two-Layer Modeling with Parametric Bregman Transfer
Vignesh Ganapathiraman, Zhan Shi, Xinhua Zhang et al.
Inference Suboptimality in Variational Autoencoders
Chris Cremer, Xuechen Li, David Duvenaud
INSPECTRE: Privately Estimating the Unseen
Jayadev Acharya, Gautam Kamath, Ziteng Sun et al.
Inter and Intra Topic Structure Learning with Word Embeddings
He Zhao, Lan Du, Wray Buntine et al.
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim, Martin Wattenberg, Justin Gilmer et al.
Invariance of Weight Distributions in Rectified MLPs
Russell Tsuchida, Fred Roosta, Marcus Gallagher
Investigating Human Priors for Playing Video Games
Rachit Dubey, Pulkit Agrawal, Deepak Pathak et al.
Is Generator Conditioning Causally Related to GAN Performance?
Augustus Odena, Jacob Buckman, Catherine Olsson et al.
Iterative Amortized Inference
Joe Marino, Yisong Yue, Stephan Mandt
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
Yunchen Pu, Shuyang Dai, Zhe Gan et al.
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin, Regina Barzilay, Tommi Jaakkola
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
Jihun Hamm, Yung-Kyun Noh
Kernelized Synaptic Weight Matrices
Lorenz Muller, Julien Martel, Giacomo Indiveri
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki et al.
K-means clustering using random matrix sparsification
Kaushik Sinha
Knowledge Transfer with Jacobian Matching
Suraj Srinivas, Francois Fleuret
Kronecker Recurrent Units
Cijo Jose, Moustapha Cisse, Francois Fleuret
Large-Scale Cox Process Inference using Variational Fourier Features
ST John, James Hensman
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
Richard Zhang, Salar Fattahi, Somayeh Sojoudi
Latent Space Policies for Hierarchical Reinforcement Learning
Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel et al.