Papers
Gradient Boosted Decision Trees for High Dimensional Sparse Output
Si Si, Huan Zhang, S. Sathiya Keerthi et al.
Attentive Recurrent Comparators
Pranav Shyam, Shubham Gupta, Ambedkar Dukkipati
Bottleneck Conditional Density Estimation
Rui Shu, Hung H. Bui, Mohammad Ghavamzadeh
Optimal Densification for Fast and Accurate Minwise Hashing
Anshumali Shrivastava
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar, Peyton Greenside, Anshul Kundaje
World of Bits: An Open-Domain Platform for Web-Based Agents
Tianlin Shi, Andrej Karpathy, Linxi Fan et al.
GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization
Li Shen, Wei Liu, Ganzhao Yuan et al.
Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use
Vatsal Sharan, Gregory Valiant
Online Learning with Local Permutations and Delayed Feedback
Ohad Shamir, Liran Szlak
Estimating individual treatment effect: generalization bounds and algorithms
Uri Shalit, Fredrik D. Johansson, David Sontag
Failures of Gradient-Based Deep Learning
Shai Shalev-Shwartz, Ohad Shamir, Shaked Shammah
Identifying Best Interventions through Online Importance Sampling
Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis et al.
Developing Bug-Free Machine Learning Systems With Formal Mathematics
Daniel Selsam, Percy Liang, David L. Dill
Adapting Kernel Representations Online Using Submodular Maximization
Matthew Schlegel, Yangchen Pan, Jiecao Chen et al.
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks
Kevin Scaman, Francis Bach, Sébastien Bubeck et al.
Hierarchy Through Composition with Multitask LMDPs
Andrew M. Saxe, Adam C. Earle, Benjamin Rosman
Analytical Guarantees on Numerical Precision of Deep Neural Networks
Charbel Sakr, Yongjune Kim, Naresh Shanbhag
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data
Tomoya Sakai, Marthinus Christoffel Plessis, Gang Niu et al.
Asymmetric Tri-training for Unsupervised Domain Adaptation
Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada
Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks
Itay Safran, Ohad Shamir
Bayesian Boolean Matrix Factorisation
Tammo Rukat, Chris C. Holmes, Michalis K. Titsias et al.
Enumerating Distinct Decision Trees
Salvatore Ruggieri
Pain-Free Random Differential Privacy with Sensitivity Sampling
Benjamin I. P. Rubinstein, Francesco Aldà