Papers
Transfer Value Iteration Networks
Junyi Shen, Hankz Hankui Zhuo, Jin Xu et al.
Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs
Lior Shani, Yonathan Efroni, Shie Mannor
Improved PAC-Bayesian Bounds for Linear Regression
Vera Shalaeva, Alireza Fakhrizadeh Esfahani, Pascal Germain et al.
Online Active Learning of Reject Option Classifiers
Kulin Shah, Naresh Manwani
Sequential Mode Estimation with Oracle Queries
Dhruti Shah, Tuhinangshu Choudhury, Nikhil Karamchandani et al.
Universal Adversarial Training
Ali Shafahi, Mahyar Najibi, Zheng Xu et al.
Empirical Bounds on Linear Regions of Deep Rectifier Networks
Thiago Serra, Srikumar Ramalingam
Uncertainty-Aware Deep Classifiers Using Generative Models
Murat Sensoy, Lance Kaplan, Federico Cerutti et al.
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves
Patrick Schwab, Lorenz Linhardt, Stefan Bauer et al.
Graph Representation Learning via Ladder Gamma Variational Autoencoders
Arindam Sarkar, Nikhil Mehta, Piyush Rai
Weighted Sampling for Combined Model Selection and Hyperparameter Tuning
Dimitrios Sarigiannis, Thomas Parnell, Haralampos Pozidis
Rank3DGAN: Semantic Mesh Generation Using Relative Attributes
Yassir Saquil, Qun-Ce Xu, Yong-Liang Yang et al.
Random Intersection Graphs and Missing Data
Dror Salti, Yakir Berchenko
Weakly Supervised Sequence Tagging from Noisy Rules
Esteban Safranchik, Shiying Luo, Stephen Bach
Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations
Nadine Rueegg, Christoph Lassner, Michael Black et al.
Linear Context Transform Block
Dongsheng Ruan, Jun Wen, Nenggan Zheng et al.
Generative Continual Concept Learning
Mohammad Rostami, Soheil Kolouri, Praveen Pilly et al.
Actionable Ethics through Neural Learning
Daniele Rossini, Danilo Croce, Sara Mancini et al.
Ensembles of Locally Independent Prediction Models
Andrew Ross, Weiwei Pan, Leo Celi et al.
On the Role of Weight Sharing During Deep Option Learning
Matthew Riemer, Ignacio Cases, Clemens Rosenbaum et al.
Fairness for Robust Log Loss Classification
Ashkan Rezaei, Rizal Fathony, Omid Memarrast et al.
Delay-Adaptive Distributed Stochastic Optimization
Zhaolin Ren, Zhengyuan Zhou, Linhai Qiu et al.
DARB: A Density-Adaptive Regular-Block Pruning for Deep Neural Networks
Ren Ao, Zhang Tao, Wang Yuhao et al.
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains
Sathya N. Ravi, Abhay Venkatesh, Glenn M. Fung et al.
Abstract Interpretation of Decision Tree Ensemble Classifiers
Francesco Ranzato, Marco Zanella