Papers
Re-revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method
Chenzi Zhang, Shuguang Hu, Zhihao Gavin Tang et al.
Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things
Ashish Kumar, Saurabh Goyal, Manik Varma
Risk Bounds for Transferring Representations With and Without Fine-Tuning
Daniel McNamara, Maria-Florina Balcan
Robust Adversarial Reinforcement Learning
Lerrel Pinto, James Davidson, Rahul Sukthankar et al.
Robust Budget Allocation via Continuous Submodular Functions
Matthew Staib, Stefanie Jegelka
RobustFill: Neural Program Learning under Noisy I/O
Jacob Devlin, Jonathan Uesato, Surya Bhupatiraju et al.
Robust Gaussian Graphical Model Estimation with Arbitrary Corruption
Lingxiao Wang, Quanquan Gu
Robust Guarantees of Stochastic Greedy Algorithms
Avinatan Hassidim, Yaron Singer
Robust Probabilistic Modeling with Bayesian Data Reweighting
Yixin Wang, Alp Kucukelbir, David M. Blei
Robust Structured Estimation with Single-Index Models
Sheng Chen, Arindam Banerjee
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
Ilija Bogunovic, Slobodan Mitrović, Jonathan Scarlett et al.
Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement
Jonathan Eckstein, Noam Goldberg, Ai Kagawa
Safety-Aware Algorithms for Adversarial Contextual Bandit
Wen Sun, Debadeepta Dey, Ashish Kapoor
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Lam M. Nguyen, Jie Liu, Katya Scheinberg et al.
Scalable Bayesian Rule Lists
Hongyu Yang, Cynthia Rudin, Margo Seltzer
Scalable Generative Models for Multi-label Learning with Missing Labels
Vikas Jain, Nirbhay Modhe, Piyush Rai
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation
Carlos Villacampa-Calvo, Daniel Hernández-Lobato
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Weizhong Zhang, Bin Hong, Wei Liu et al.
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics
Ken Kansky, Tom Silver, David A. Mély et al.
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
Daniele Calandriello, Alessandro Lazaric, Michal Valko
Selective Inference for Sparse High-Order Interaction Models
Shinya Suzumura, Kazuya Nakagawa, Yuta Umezu et al.
Self-Paced Co-training
Fan Ma, Deyu Meng, Qi Xie et al.
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data
Tomoya Sakai, Marthinus Christoffel Plessis, Gang Niu et al.
Sequence Modeling via Segmentations
Chong Wang, Yining Wang, Po-Sen Huang et al.
Sequence to Better Sequence: Continuous Revision of Combinatorial Structures
Jonas Mueller, David Gifford, Tommi Jaakkola