Papers
4,025 papers found
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
Sparse Randomized Partition Trees for Nearest Neighbor Search
Kaushik Sinha, Omid Keivani
Spatial Decompositions for Large Scale SVMs
Philipp Thomann, Ingrid Blaschzyk, Mona Meister et al.
Spectral Methods for Correlated Topic Models
Forough Arabshahi, Anima Anandkumar
Stochastic Difference of Convex Algorithm and its Application to Training Deep Boltzmann Machines
Atsushi Nitanda, Taiji Suzuki
Stochastic Rank-1 Bandits
Sumeet Katariya, Branislav Kveton, Csaba Szepesvari et al.
Structured adaptive and random spinners for fast machine learning computations
Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski et al.
Tensor Decompositions via Two-Mode Higher-Order SVD (HOSVD)
Miaoyan Wang, Yun Song
Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis
Andrew Stevens, Yunchen Pu, Yannan Sun et al.
The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits
Tor Lattimore, Csaba Szepesvari