Papers
Tensor Balancing on Statistical Manifold
Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda
Ordinal Graphical Models: A Tale of Two Approaches
Arun Sai Suggala, Eunho Yang, Pradeep Ravikumar
Approximate Steepest Coordinate Descent
Sebastian U. Stich, Anant Raj, Martin Jaggi
Probabilistic Submodular Maximization in Sub-Linear Time
Serban Stan, Morteza Zadimoghaddam, Andreas Krause et al.
Robust Budget Allocation via Continuous Submodular Functions
Matthew Staib, Stefanie Jegelka
High-Dimensional Structured Quantile Regression
Vidyashankar Sivakumar, Arindam Banerjee
Nonparanormal Information Estimation
Shashank Singh, Barnabás Póczos
The Predictron: End-To-End Learning and Planning
David Silver, Hado Hasselt, Matteo Hessel et al.
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.