Papers
8,340 papers found
Saddle Points and Accelerated Perceptron Algorithms
Adams Wei Yu, Fatma Kilinc-Karzan, Jaime Carbonell
Safe Screening with Variational Inequalities and Its Application to Lasso
Jun Liu, Zheng Zhao, Jie Wang et al.
Sample-based approximate regularization
Philip Bachman, Amir-Massoud Farahmand, Doina Precup
Sample Efficient Reinforcement Learning with Gaussian Processes
Robert Grande, Thomas Walsh, Jonathan How
Scalable and Robust Bayesian Inference via the Median Posterior
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin et al.
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors
Piyush Rai, Yingjian Wang, Shengbo Guo et al.
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications
Sebastien Bratieres, Novi Quadrianto, Sebastian Nowozin et al.
Scalable Semidefinite Relaxation for Maximum A Posterior Estimation
Qixing Huang, Yuxin Chen, Leonidas Guibas
Scaling SVM and Least Absolute Deviations via Exact Data Reduction
Jie Wang, Peter Wonka, Jieping Ye
Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations
Timothy Mann, Shie Mannor
Scaling Up Robust MDPs using Function Approximation
Aviv Tamar, Shie Mannor, Huan Xu
Signal recovery from Pooling Representations
Joan Bruna Estrach, Arthur Szlam, Yann LeCun
Skip Context Tree Switching
Marc Bellemare, Joel Veness, Erik Talvitie
Sparse meta-Gaussian information bottleneck
Melani Rey, Volker Roth, Thomas Fuchs
Sparse Reinforcement Learning via Convex Optimization
Zhiwei Qin, Weichang Li, Firdaus Janoos
Spectral Bandits for Smooth Graph Functions
Michal Valko, Remi Munos, Branislav Kveton et al.
Spectral Regularization for Max-Margin Sequence Tagging
Ariadna Quattoni, Borja Balle, Xavier Carreras et al.
Spherical Hamiltonian Monte Carlo for Constrained Target Distributions
Shiwei Lan, Bo Zhou, Babak Shahbaba
Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery
Cun Mu, Bo Huang, John Wright et al.
Stable and Efficient Representation Learning with Nonnegativity Constraints
Tsung-Han Lin, H. T. Kung
Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance
Simone Romano, James Bailey, Vinh Nguyen et al.
Statistical analysis of stochastic gradient methods for generalized linear models
Panagiotis Toulis, Edoardo Airoldi, Jason Rennie
Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting
Yudong Chen, Jiaming Xu
Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra