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Proximal Algorithms in Statistics and Machine Learning
11 February 2015
Nicholas G. Polson
James G. Scott
Brandon T. Willard
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Papers citing
"Proximal Algorithms in Statistics and Machine Learning"
45 / 45 papers shown
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Approximation of the Proximal Operator of the
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Radu Balan
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Sparse Bayesian Lasso via a Variable-Coefficient
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Katharine M. Donato
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Multiresolution categorical regression for interpretable cell type annotation
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Keshav Motwani
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29 Aug 2022
Riesz-Quincunx-UNet Variational Auto-Encoder for Satellite Image Denoising
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Xiqi Fei
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25 Aug 2022
Equivariant Hypergraph Diffusion Neural Operators
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Shenghao Yang
Yunyu Liu
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Pan Li
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14 Jul 2022
Bayesian Learning of Parameterised Quantum Circuits
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Marcello Benedetti
Matthias Rosenkranz
282
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15 Jun 2022
Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs
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Hedi Xia
Yiwei Wang
E. Cherkaev
A. Narayan
Long Chen
Jack Xin
Andrea L. Bertozzi
Stanley J. Osher
Bao Wang
285
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0
19 Apr 2022
Robust online joint state/input/parameter estimation of linear systems
IEEE Conference on Decision and Control (CDC), 2022
Jean-Sébastien Brouillon
Keith Moffat
Florian Dorfler
Giancarlo Ferrari-Trecate
168
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12 Apr 2022
Faster Deep Reinforcement Learning with Slower Online Network
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Rasool Fakoor
Omer Gottesman
Taesup Kim
Michael L. Littman
Alexander J. Smola
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10 Dec 2021
Accelerated nonlinear primal-dual hybrid gradient methods with applications to supervised machine learning
Jérome Darbon
G. P. Langlois
238
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24 Sep 2021
Bayesian Error-in-Variables Models for the Identification of Power Networks
Jean-Sébastien Brouillon
E. Fabbiani
P. Nahata
Keith Moffat
Florian Dorfler
Giancarlo Ferrari-Trecate
120
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0
09 Jul 2021
Active-set algorithms based statistical inference for shape-restricted generalized additive Cox regression models
Journal of Statistical Computation and Simulation (JSCS), 2021
Geng Deng
Guangning Xu
Qiang Fu
Xindong Wang
Jing Qin
267
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29 Jun 2021
Scalable algorithms for semiparametric accelerated failure time models in high dimensions
Statistics in Medicine (Stat. Med.), 2021
P. Suder
Aaron J. Molstad
191
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04 Apr 2021
Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-Differentiable Priors
Journal of the American Statistical Association (JASA), 2021
Jacob Vorstrup Goldman
Torben Sell
Sumeetpal S. Singh
285
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0
16 Mar 2021
POLA: Online Time Series Prediction by Adaptive Learning Rates
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Wenyu Zhang
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190
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0
17 Feb 2021
Accelerate the Warm-up Stage in the Lasso Computation via a Homotopic Approach
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Yujie Zhao
X. Huo
303
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0
26 Oct 2020
A User-Friendly Computational Framework for Robust Structured Regression with the L
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Jocelyn T. Chi
Eric C. Chi
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356
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Distributed Proximal Splitting Algorithms with Rates and Acceleration
Frontiers in Signal Processing (FSP), 2020
Laurent Condat
Grigory Malinovsky
Peter Richtárik
343
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Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data
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Younghoon Kim
B. Fredrickson
V. Pipiras
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168
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0
09 Jul 2020
Additive stacking for disaggregate electricity demand forecasting
Christian Capezza
B. Palumbo
Y. Goude
S. Wood
Matteo Fasiolo
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326
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20 May 2020
One-Step Estimation With Scaled Proximal Methods
Mathematics of Operations Research (MOR), 2020
R. Bassett
Julio Deride
292
0
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30 Apr 2020
Dualize, Split, Randomize: Toward Fast Nonsmooth Optimization Algorithms
Journal of Optimization Theory and Applications (JOTA), 2020
Adil Salim
Laurent Condat
Konstantin Mishchenko
Peter Richtárik
420
32
0
03 Apr 2020
Estimating Multiple Precision Matrices with Cluster Fusion Regularization
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Bradley S. Price
Aaron J. Molstad
Ben Sherwood
261
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0
01 Mar 2020
High-Performance Statistical Computing in the Computing Environments of the 2020s
Statistical Science (Statist. Sci.), 2020
Seyoon Ko
Hua Zhou
Jin J. Zhou
Joong-Ho Won
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0
07 Jan 2020
GENO -- GENeric Optimization for Classical Machine Learning
Neural Information Processing Systems (NeurIPS), 2019
Soren Laue
Matthias Mitterreiter
Joachim Giesen
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139
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0
31 May 2019
Online Learning over Dynamic Graphs via Distributed Proximal Gradient Algorithm
IEEE Transactions on Automatic Control (IEEE TAC), 2019
Rishabh Dixit
Amrit Singh Bedi
K. Rajawat
165
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0
16 May 2019
A Distributed Method for Fitting Laplacian Regularized Stratified Models
Jonathan Tuck
Shane T. Barratt
Stephen P. Boyd
319
27
0
26 Apr 2019
Fast Non-Bayesian Poisson Factorization for Implicit-Feedback Recommendations
David Cortes
320
2
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05 Nov 2018
Sparse Group Inductive Matrix Completion
Ivan Nazarov
B. Shirokikh
M. Burkina
G. Fedonin
Maxim Panov
329
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27 Apr 2018
Rendition: Reclaiming what a black box takes away
SIAM Journal of Imaging Sciences (SIIMS), 2018
P. Milanfar
266
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Local Kernels that Approximate Bayesian Regularization and Proximal Operators
Frank Ong
P. Milanfar
Pascal Getreuer
218
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09 Mar 2018
Generalized Linear Model Regression under Distance-to-set Penalties
Jason Xu
Eric C. Chi
K. Lange
234
40
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03 Nov 2017
Sparse Regularization in Marketing and Economics
Guanhao Feng
Nicholas G. Polson
Yuexi Wang
Jianeng Xu
350
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01 Sep 2017
Deep Learning: A Bayesian Perspective
Nicholas G. Polson
Vadim Sokolov
BDL
448
128
0
01 Jun 2017
Bayesian
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0
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-regularized Least Squares
Applied Stochastic Models in Business and Industry (ASMBI), 2017
Nicholas G. Polson
Lei Sun
494
23
0
31 May 2017
Horseshoe Regularization for Feature Subset Selection
A. Bhadra
J. Datta
Nicholas G. Polson
Brandon T. Willard
217
10
0
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Efficient Bayesian computation by proximal Markov chain Monte Carlo: when Langevin meets Moreau
SIAM Journal of Imaging Sciences (SIAM J. Imaging Sci.), 2016
Alain Durmus
Eric Moulines
Marcelo Pereyra
276
200
0
22 Dec 2016
An MM Algorithm for Split Feasibility Problems
Jason Xu
Eric C. Chi
Meng Yang
K. Lange
197
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Deep Learning in Finance
J. B. Heaton
Nicholas G. Polson
J. Witte
261
203
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A Statistical Theory of Deep Learning via Proximal Splitting
Nicholas G. Polson
Brandon T. Willard
Massoud Heidari
165
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20 Sep 2015
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