Papers
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Lasse Espeholt, Hubert Soyer, Remi Munos et al.
Implicit Quantile Networks for Distributional Reinforcement Learning
Will Dabney, Georg Ostrovski, David Silver et al.
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion
Cong Ma, Kaizheng Wang, Yuejie Chi et al.
Importance Weighted Transfer of Samples in Reinforcement Learning
Andrea Tirinzoni, Andrea Sessa, Matteo Pirotta et al.
Improved large-scale graph learning through ridge spectral sparsification
Daniele Calandriello, Alessandro Lazaric, Ioannis Koutis et al.
Improved nearest neighbor search using auxiliary information and priority functions
Omid Keivani, Kaushik Sinha
Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems
Marc Abeille, Alessandro Lazaric
Improved Training of Generative Adversarial Networks Using Representative Features
Duhyeon Bang, Hyunjung Shim
Improving Optimization for Models With Continuous Symmetry Breaking
Robert Bamler, Stephan Mandt
Improving Regression Performance with Distributional Losses
Ehsan Imani, Martha White
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