Papers
Prediction Performance After Learning in Gaussian Process Regression
Johan Wagberg, Dave Zachariah, Thomas Schon et al.
Quantifying the accuracy of approximate diffusions and Markov chains
Jonathan Huggins, James Zou
Random Consensus Robust PCA
Daniel Pimentel-Alarcon, Robert Nowak
Random projection design for scalable implicit smoothing of randomly observed stochastic processes
Francois Belletti, Evan Sparks, Alexandre Bayen et al.
Rank Aggregation and Prediction with Item Features
Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit Dhillon
Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models
Sejun Park, Yunhun Jang, Andreas Galanis et al.
Regression Uncertainty on the Grassmannian
Yi Hong, Xiao Yang, Roland Kwitt et al.
Regret Bounds for Lifelong Learning
Pierre Alquier, The Tien Mai, Massimiliano Pontil
Regret Bounds for Transfer Learning in Bayesian Optimisation
Alistair Shilton, Sunil Gupta, Santu Rana et al.
Relativistic Monte Carlo
Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever et al.
Removing Phase Transitions from Gibbs Measures
Ian Fellows, Mark Handcock
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms
Christian Naesseth, Francisco Ruiz, Scott Linderman et al.
Robust and Efficient Computation of Eigenvectors in a Generalized Spectral Method for Constrained Clustering
Chengming Jiang, Huiqing Xie, Zhaojun Bai
Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness
Ioan Gabriel Bucur, Tom Claassen, Tom Heskes
Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition
Jiong Zhang, Ian En-Hsu Yen, Pradeep Ravikumar et al.
Scalable Greedy Feature Selection via Weak Submodularity
Rajiv Khanna, Ethan Elenberg, Alex Dimakis et al.
Scalable Learning of Non-Decomposable Objectives
Elad Eban, Mariano Schain, Alan Mackey et al.
Scalable Variational Inference for Super Resolution Microscopy
Ruoxi Sun, Evan Archer, Liam Paninski
Scaling Submodular Maximization via Pruned Submodularity Graphs
Tianyi Zhou, Hua Ouyang, Jeff Bilmes et al.
Sequential Graph Matching with Sequential Monte Carlo
Seong-Hwan Jun, Samuel W.K. Wong, James Zidek et al.
Sequential Multiple Hypothesis Testing with Type I Error Control
Alan Malek, Sumeet Katariya, Yinlam Chow et al.
Signal-based Bayesian Seismic Monitoring
David Moore, Stuart Russell
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data
Jialei Wang, Jason Lee, Mehrdad Mahdavi et al.
Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage
Alp Yurtsever, Madeleine Udell, Joel Tropp et al.
Sparse Accelerated Exponential Weights
Pierre Gaillard, Olivier Wintenberger