Asymptotic Bias of Stochastic Gradient Search

30 August 2017

Papers citing "Asymptotic Bias of Stochastic Gradient Search"

42 / 42 papers shown

Title
Derivatives of Stochastic Gradient Descent F. Iutzeler Edouard Pauwels Samuel Vaiter 75 1 0 24 May 2024
Inexact subgradient methods for semialgebraic functions Jérôme Bolte Tam Le Éric Moulines Edouard Pauwels 110 2 0 30 Apr 2024
Stochastic Approximation with Biased MCMC for Expectation Maximization Samuel Gruffaz Kyurae Kim Alain Durmus Jacob R. Gardner 77 6 0 27 Feb 2024
Implicit Diffusion: Efficient Optimization through Stochastic Sampling Pierre Marion Anna Korba Peter Bartlett Mathieu Blondel Valentin De Bortoli Arnaud Doucet Felipe Llinares-López Courtney Paquette Quentin Berthet 154 15 0 08 Feb 2024
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation Sobihan Surendran Antoine Godichon-Baggioni Adeline Fermanian Sylvain Le Corff 109 2 0 05 Feb 2024
Plug-and-Play image restoration with Stochastic deNOising REgularization Marien Renaud Jean Prost Arthur Leclaire Nicolas Papadakis DiffM 166 8 0 01 Feb 2024
Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and Applications Rajeeva Laxman Karandikar M. Vidyasagar 79 10 0 05 Dec 2023
Score-Aware Policy-Gradient Methods and Performance Guarantees using Local Lyapunov Conditions: Applications to Product-Form Stochastic Networks and Queueing Systems Céline Comte Matthieu Jonckheere J. Sanders Albert Senen-Cerda 51 1 0 05 Dec 2023
Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning Hadrien Hendrikx G. Fort Eric Moulines Hoi-To Wai 81 12 0 22 Feb 2023
Regularized Rényi divergence minimization through Bregman proximal gradient algorithms Thomas Guilmeau Émilie Chouzenoux Victor Elvira 86 3 0 09 Nov 2022
Stability and Generalization for Markov Chain Stochastic Gradient Methods Puyu Wang Yunwen Lei Yiming Ying Ding-Xuan Zhou 78 18 0 16 Sep 2022
A repeated unknown game: Decentralized task offloading in vehicular fog computing Byungjin Cho Yu Xiao 37 1 0 03 Sep 2022
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling Gabriel Victorino Cardoso S. Samsonov Achille Thin Eric Moulines Jimmy Olsson 67 9 0 13 Jul 2022
Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data Abhishek Roy Krishnakumar Balasubramanian Saeed Ghadimi 85 9 0 22 Jun 2022
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients Kyurae Kim Jisu Oh Jacob R. Gardner Adji Bousso Dieng Hongseok Kim BDL 95 8 0 13 Jun 2022
Unbiased Multilevel Monte Carlo methods for intractable distributions: MLMC meets MCMC Guanyang Wang T. Wang 91 15 0 11 Apr 2022
Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data Ahmet Alacaoglu Hanbaek Lyu 64 4 0 29 Mar 2022
On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent R. Laumont Valentin De Bortoli Andrés Almansa J. Delon Alain Durmus Marcelo Pereyra 71 26 0 16 Jan 2022
Conditionally Gaussian PAC-Bayes Eugenio Clerico George Deligiannidis Arnaud Doucet 110 10 0 22 Oct 2021
Convergence of Batch Asynchronous Stochastic Approximation With Applications to Reinforcement Learning Rajeeva Laxman Karandikar M. Vidyasagar 99 0 0 08 Sep 2021
Stochastic Approximation with Discontinuous Dynamics, Differential Inclusions, and Applications N. Nguyen G. Yin 68 7 0 28 Aug 2021
Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo Ziang Niu J. Meier F. Briol 106 13 0 22 Jun 2021
On Unbiased Score Estimation for Partially Observed Diffusions J. Heng J. Houssineau Ajay Jasra 70 11 0 11 May 2021
Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie R. Laumont Valentin De Bortoli Andrés Almansa J. Delon Alain Durmus Marcelo Pereyra 96 112 0 08 Mar 2021
Maximum likelihood estimation of regularisation parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part II: Theoretical Analysis Valentin De Bortoli Alain Durmus A. F. Vidal Marcelo Pereyra 88 20 0 13 Aug 2020
Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms Tengyu Xu Zhe Wang Yingbin Liang 87 25 0 27 Apr 2020
Convergence rates and approximation results for SGD and its continuous-time counterpart Xavier Fontaine Valentin De Bortoli Alain Durmus 44 7 0 08 Apr 2020
Policy-Aware Model Learning for Policy Gradient Methods Romina Abachi Mohammad Ghavamzadeh Amir-massoud Farahmand 77 36 0 28 Feb 2020
Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling Huaqing Xiong Tengyu Xu Yingbin Liang Wei Zhang 79 33 0 15 Feb 2020
A Stochastic Gradient Method with Biased Estimation for Faster Nonconvex Optimization Jia Bi S. Gunn 61 3 0 13 May 2019
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks Jiong Zhang Hsiang-Fu Yu Inderjit S. Dhillon 58 27 0 08 May 2019
Convergence rates for optimised adaptive importance samplers Ömer Deniz Akyildiz Joaquín Míguez 133 31 0 28 Mar 2019
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme Belhal Karimi B. Miasojedow Eric Moulines Hoi-To Wai 100 91 0 02 Feb 2019
Bayesian variational inference for exponential random graph models Linda S. L. Tan Nial Friel 69 17 0 10 Nov 2018
Stability of Optimal Filter Higher-Order Derivatives V. Tadic Arnaud Doucet 57 4 0 25 Jun 2018
Bias of Particle Approximations to Optimal Filter Derivative V. Tadic Arnaud Doucet 73 1 0 25 Jun 2018
Analyticity of Entropy Rates of Continuous-State Hidden Markov Models V. Tadic Arnaud Doucet 39 3 0 25 Jun 2018
Particle-based, online estimation of tangent filters with application to parameter estimation in nonlinear state-space models Jimmy Olsson Johan Westerborn Alenlöv 85 10 0 22 Dec 2017
Unbiased Markov chain Monte Carlo with couplings Pierre E. Jacob J. O'Leary Yves F. Atchadé 136 73 0 11 Aug 2017
Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains Hadrien Hendrikx Alain Durmus Francis R. Bach 127 156 0 20 Jul 2017
Analysis of gradient descent methods with non-diminishing, bounded errors Arunselvan Ramaswamy S. Bhatnagar 54 21 0 01 Apr 2016
Gradient Estimation with Simultaneous Perturbation and Compressive Sensing Vivek Borkar Vikranth Dwaracherla Neeraja Sahasrabudhe 62 9 0 27 Nov 2015