Papers
572 papers found
An Approach to One-Bit Compressed Sensing Based on Probably Approximately Correct Learning Theory
Mehmet Eren Ahsen, Mathukumalli Vidyasagar
Approximate Profile Maximum Likelihood
Dmitri S. Pavlichin, Jiantao Jiao, Tsachy Weissman
Scalable Approximate MCMC Algorithms for the Horseshoe Prior
James Johndrow, Paulo Orenstein, Anirban Bhattacharya
Nesterov's Acceleration for Approximate Newton
Haishan Ye, Luo Luo, Zhihua Zhang
Asymptotic Consistency of $\alpha$-{R}ényi-Approximate Posteriors
Prateek Jaiswal, Vinayak Rao, Harsha Honnappa
Approximate Newton Methods
Haishan Ye, Luo Luo, Zhihua Zhang
Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach
Alberto Maria Metelli, Matteo Pirotta, Daniele Calandriello et al.
Tractable Approximate Gaussian Inference for Bayesian Neural Networks
James-A. Goulet, Luong Ha Nguyen, Saeid Amiri
On Acceleration for Convex Composite Minimization with Noise-Corrupted Gradients and Approximate Proximal Mapping
Qiang Zhou, Sinno Jialin Pan
Approximate Bayesian Computation via Classification
Yuexi Wang, Tetsuya Kaji, Veronika Rockova
Tree-AMP: Compositional Inference with Tree Approximate Message Passing
Antoine Baker, Florent Krzakala, Benjamin Aubin et al.
Approximate Post-Selective Inference for Regression with the Group LASSO
Snigdha Panigrahi, Peter W MacDonald, Daniel Kessler
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees
William J. Wilkinson, Simo Särkkä, Arno Solin
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning
Wenhao Li, Bo Jin, Xiangfeng Wang et al.
Mixed Regression via Approximate Message Passing
Nelvin Tan, Ramji Venkataramanan
A Multilabel Classification Framework for Approximate Nearest Neighbor Search
Ville Hyvönen, Elias Jääsaari, Teemu Roos
Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC
Marko Järvenpää, Jukka Corander
Approximate Information Tests on Statistical Submanifolds
Michael W. Trosset, Carey E. Priebe
Inferring Change Points in High-Dimensional Regression via Approximate Message Passing
Gabriel Arpino, Xiaoqi Liu, Julia Gontarek et al.
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples
Leo L. Duan, Anirban Bhattacharya
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
Kuo-Wei Lai, Vidya Muthukumar
Bayesian Score Calibration for Approximate Models
Joshua J. Bon, David J. Warne, David J. Nott et al.
Data-driven Identification of Approximate Passive Linear Models for Nonlinear Systems
S. Sivaranjani, Etika Agarwal, Vijay Gupta
Learning Approximate Forward Reachable Sets Using Separating Kernels
Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi