Fetching the paper…
Reading the bibliography…
A key task in Bayesian statistics is sampling from distributions that are only specified up to a partition function (i.e., constant of proportionality).
“Criteria for recurrence and existence of invariant measures for multidimensional diffusions”
RN Bhattacharya · 1978
Earlier work this paper cites.
“Diffusions hypercontractives”
Dominique Bakry and Michel “’Emery · 1985
Earlier work this paper cites.
“Comparison theorems for reversible Markov chains”
Persi Diaconis and Laurent Saloff-Coste · 1993
Earlier work this paper cites.
“Random walks in a convex body and an improved volume algorithm”
L“’aszl“’o Lov“’asz and Mikl“’os Simonovits · 1993
Earlier work this paper cites.
“Adaptive estimation of a quadratic functional by model selection”
Beatrice Laurent and Pascal Massart · 2000
Earlier work this paper cites.
“Metastability and Low Lying Spectra in Reversible Markov Chains”
Anton Bovier, Michael Eckhoff, V“’eronique Gayrard and Markus Klein · 2002
Earlier work this paper cites.
“Markov chain decomposition for convergence rate analysis”
Neal Madras and Dana Randall · 2002
Earlier work this paper cites.
“On swapping and simulated tempering algorithms”
Zhongrong Zheng · 2003
Earlier work this paper cites.
“Metastability in reversible diffusion processes I: Sharp asymptotics for capacities and exit times”
Anton Bovier, Michael Eckhoff, V“’eronique Gayrard and Markus Klein · 2004
Earlier work this paper cites.
“Metastability in reversible diffusion processes II: Precise asymptotics for small eigenvalues”
Anton Bovier, V“’eronique Gayrard and Markus Klein · 2005
Earlier work this paper cites.
“Geometric random walks: a survey”
Santosh Vempala · 2005
Earlier work this paper cites.
“A simple proof of the Poincaré inequality for a large class of probability measures including the log-concave case”
Dominique Bakry, Franck Barthe, Patrick Cattiaux and Arnaud Guillin · 2008
Earlier work this paper cites.
“Sufficient conditions for torpid mixing of parallel and simulated tempering”
Dawn Woodard, Scott Schmidler and Mark Huber · 2009
Cited alongside, same era.
“Conditions for rapid mixing of parallel and simulated tempering on multimodal distributions”
Dawn Woodard, Scott Schmidler and Mark Huber · 2009
Cited alongside, same era.
“Complexity of inference in latent dirichlet allocation”
David Sontag and Dan Roy · 2011
Cited alongside, same era.
“Learning Topic Models – Going Beyond SVD”
S. Arora, R. Ge and A. Moitra · 2012
Cited alongside, same era.
“A spectral algorithm for latent dirichlet allocation”
Anima Anandkumar et al · 2012
Cited alongside, same era.
“A practical algorithm for topic modeling with provable guarantees”
Sanjeev Arora et al · 2013
Cited alongside, same era.
“Stochastic Backpropagation and Approximate Inference in Deep Generative Models”
Danilo Rezende, Shakir Mohamed and Daan Wierstra · 2014
Later among the works it cites.
“Simple, efficient, and neural algorithms for sparse coding”
Sanjeev Arora, Rong Ge, Tengyu Ma and Ankur Moitra · 2015
Later among the works it cites.
“Escaping the local minima via simulated annealing: Optimization of approximately convex functions”
Alexandre Belloni, Tengyuan Liang, Hariharan Narayanan and Alexander Rakhlin · 2015
Later among the works it cites.
“Sampling from a log-concave distribution with Projected Langevin Monte Carlo”
S“’ebastien Bubeck, Ronen Eldan and Joseph Lehec · 2015
Later among the works it cites.
“Theoretical guarantees for approximate sampling from smooth and log-concave densities”
Arnak Dalalyan · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
“Analysis and geometry of Markov diffusion operators”
Dominique Bakry, Ivan Gentil and Michel Ledoux · 2013
Cited alongside, same era.
“Learning mixtures of spherical gaussians: moment methods and spectral decompositions”
Daniel Hsu and Sham Kakade · 2013
Cited alongside, same era.
“Auto-encoding variational bayes”
Diederik Kingma and Max Welling · 2013
Cited alongside, same era.
“Learning Sparsely Used Overcomplete Dictionaries.”
Alekh Agarwal et al · 2014
Cited alongside, same era.
“Partitioning into expanders”
Shayan Gharan and Luca Trevisan · 2014
Cited alongside, same era.
“High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm”, 2016
Alain Durmus and Eric Moulines · 2016
Later among the works it cites.
“Algorithms and matching lower bounds for approximately-convex optimization”
Yuanzhi Li and Andrej Risteski · 2016
Later among the works it cites.
“Provable learning of Noisy-or Networks”
Sanjeev Arora, Rong Ge, Tengyu Ma and Andrej Risteski · 2017
Closest in time.
Arnak Dalalyan · 2017
Closest in time.
“Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis”
Maxim Raginsky, Alexander Rakhlin and Matus Telgarsky · 2017
Closest in time.
“On some provably correct cases of variational inference for topic models”
Pranjal Awasthi and Andrej Risteski · 2098
Closest in time.