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Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions

31 October 2015

Mohammad Emtiyaz Khan

Papers citing "Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions"

31 / 31 papers shown

Title
Understanding Stochastic Natural Gradient Variational Inference Kaiwen Wu Jacob R. Gardner BDL 89 2 0 04 Jun 2024
Batch and match: black-box variational inference with a score-based divergence Diana Cai Chirag Modi Loucas Pillaud-Vivien C. Margossian Robert Mansel Gower David M. Blei Lawrence K. Saul 77 10 0 22 Feb 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 72 4 0 19 Jan 2024
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? Kyurae Kim Yian Ma Jacob R. Gardner 113 7 0 27 Jul 2023
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift Florian Seligmann P. Becker Michael Volpp Gerhard Neumann UQCV 87 16 0 21 Jun 2023
Provable convergence guarantees for black-box variational inference Justin Domke Guillaume Garrigos Robert Mansel Gower 99 21 0 04 Jun 2023
On the Convergence of Black-Box Variational Inference Kyurae Kim Jisu Oh Kaiwen Wu Yi-An Ma Jacob R. Gardner BDL 96 17 0 24 May 2023
Variational Bayes Made Easy Mohammad Emtiyaz Khan BDL 64 1 0 27 Apr 2023
Regularized Rényi divergence minimization through Bregman proximal gradient algorithms Thomas Guilmeau Émilie Chouzenoux Victor Elvira 86 3 0 09 Nov 2022
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models Oleg Arenz Philipp Dahlinger Zihan Ye Michael Volpp Gerhard Neumann 126 17 0 23 Sep 2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning Matthew Ashman T. Bui Cuong V Nguyen Efstratios Markou Adrian Weller S. Swaroop Richard Turner FedML 65 14 0 24 Feb 2022
Dual Parameterization of Sparse Variational Gaussian Processes Vincent Adam Paul E. Chang Mohammad Emtiyaz Khan Arno Solin 93 23 0 05 Nov 2021
Sparse Algorithms for Markovian Gaussian Processes William J. Wilkinson Arno Solin Vincent Adam 62 12 0 19 Mar 2021
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent Frederik Kunstner Raunak Kumar Mark Schmidt 84 22 0 02 Nov 2020
Efficient Variational Bayes Learning of Graphical Models with Smooth Structural Changes Hang Yu Songwei Wu Justin Dauwels 68 5 0 16 Sep 2020
Trust-Region Variational Inference with Gaussian Mixture Models Oleg Arenz Mingjun Zhong Gerhard Neumann 87 20 0 10 Jul 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations Wu Lin Mohammad Emtiyaz Khan Mark Schmidt BDL 111 71 0 07 Jun 2019
Provable Smoothness Guarantees for Black-Box Variational Inference Justin Domke 74 36 0 24 Jan 2019
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language Matthew D. Hoffman Matthew J. Johnson Dustin Tran 62 17 0 29 Nov 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 91 56 0 27 Nov 2018
DAPPER: Scaling Dynamic Author Persona Topic Model to Billion Word Corpora S. Zee Alice Havrileck 32 3 0 03 Nov 2018
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 200 271 0 13 Jun 2018
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models Hugh Salimbeni Stefanos Eleftheriadis J. Hensman BDL 91 86 0 24 Mar 2018
Boosted Density Estimation Remastered Zac Cranko Richard Nock GAN 69 12 0 22 Mar 2018
Topic Modeling on Health Journals with Regularized Variational Inference Robert Giaquinto A. Banerjee 68 6 0 15 Jan 2018
Boosting Variational Inference: an Optimization Perspective Francesco Locatello Rajiv Khanna Joydeep Ghosh Gunnar Rätsch 71 36 0 05 Aug 2017
Cooperative Hierarchical Dirichlet Processes: Superposition vs. Maximization Junyu Xuan Jie Lu Guangquan Zhang R. Xu 66 4 0 18 Jul 2017
Proximity Variational Inference Jaan Altosaar Rajesh Ranganath David M. Blei BDL 43 22 0 24 May 2017
Stochastic Sequential Neural Networks with Structured Inference Hao Liu Haoli Bai Lirong He Zenglin Xu BDL 51 3 0 24 May 2017
Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models Mohammad Emtiyaz Khan Wu Lin BDL 88 137 0 13 Mar 2017
Composing graphical models with neural networks for structured representations and fast inference Matthew J. Johnson David Duvenaud Alexander B. Wiltschko S. R. Datta Ryan P. Adams BDL OCL 123 486 0 20 Mar 2016