Papers
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning
Christoph Dann, Emma Brunskill
Sample Complexity of Learning Mahalanobis Distance Metrics
Nakul Verma, Kristin Branson
Sample Efficient Path Integral Control under Uncertainty
Yunpeng Pan, Evangelos Theodorou, Michail Kontitsis
Sampling from Probabilistic Submodular Models
Alkis Gotovos, Hamed Hassani, Andreas Krause
Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models
Michael C Hughes, William T Stephenson, Erik Sudderth
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods
Amir Dezfouli, Edwin V. Bonilla
Scalable Semi-Supervised Aggregation of Classifiers
Akshay Balsubramani, Yoav Freund
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients
Bo Xie, Yingyu Liang, Le Song
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly et al.
Secure Multi-party Differential Privacy
Peter Kairouz, Sewoong Oh, Pramod Viswanath
Segregated Graphs and Marginals of Chain Graph Models
Ilya Shpitser
Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization
Niao He, Zaid Harchaoui
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
Rie Johnson, Tong Zhang
Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data
Danilo Bzdok, Michael Eickenberg, Olivier Grisel et al.
Semi-supervised Learning with Ladder Networks
Antti Rasmus, Mathias Berglund, Mikko Honkala et al.
Semi-supervised Sequence Learning
Andrew M Dai, Quoc V Le
SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk
Guillaume Papa, Stéphan Clémençon, Aurélien Bellet
Shepard Convolutional Neural Networks
Jimmy SJ Ren, Li Xu, Qiong Yan et al.
Skip-Thought Vectors
Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov et al.
Smooth and Strong: MAP Inference with Linear Convergence
Ofer Meshi, Mehrdad Mahdavi, Alex Schwing
Smooth Interactive Submodular Set Cover
Bryan D He, Yisong Yue
Softstar: Heuristic-Guided Probabilistic Inference
Mathew Monfort, Brenden M Lake, Brenden M Lake et al.
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
Yuxin Chen, Emmanuel Candes
Space-Time Local Embeddings
Ke Sun, Jun Wang, Alexandros Kalousis et al.
Sparse and Low-Rank Tensor Decomposition
Parikshit Shah, Nikhil Rao, Gongguo Tang