Wu Lin
Title
Cited by
Cited by
Year
Fast and scalable bayesian deep learning by weight-perturbation in adam
M Khan, D Nielsen, V Tangkaratt, W Lin, Y Gal, A Srivastava
International Conference on Machine Learning, 2611-2620, 2018
1292018
Conjugate-computation variational inference: Converting variational inference in non-conjugate models to inferences in conjugate models
M Khan, W Lin
Artificial Intelligence and Statistics, 878-887, 2017
672017
Variational message passing with structured inference networks
W Lin, N Hubacher, ME Khan
arXiv preprint arXiv:1803.05589, 2018
342018
Faster stochastic variational inference using proximal-gradient methods with general divergence functions
ME Khan, R Babanezhad, W Lin, M Schmidt, M Sugiyama
arXiv preprint arXiv:1511.00146, 2015
312015
Fast and simple natural-gradient variational inference with mixture of exponential-family approximations
W Lin, ME Khan, M Schmidt
International Conference on Machine Learning, 3992-4002, 2019
182019
Variational adaptive-Newton method for explorative learning
ME Khan, W Lin, V Tangkaratt, Z Liu, D Nielsen
arXiv preprint arXiv:1711.05560, 2017
112017
Convergence of proximal-gradient stochastic variational inference under non-decreasing step-size sequence
ME Khan, R Babanezhad, W Lin, M Schmidt, M Sugiyama
arXiv preprint arXiv:1511.00146, 2015
82015
WaterlooClarke: TREC 2015 Total Recall Track.
H Zhang, W Lin, Y Wang, CLA Clarke, MD Smucker
TREC, 2015
72015
Stein's Lemma for the Reparameterization Trick with Exponential Family Mixtures
W Lin, ME Khan, M Schmidt
arXiv preprint arXiv:1910.13398, 2019
52019
Handling the positive-definite constraint in the bayesian learning rule
W Lin, M Schmidt, ME Khan
International Conference on Machine Learning, 6116-6126, 2020
42020
Tractable structured natural gradient descent using local parameterizations
W Lin, F Nielsen, ME Khan, M Schmidt
arXiv preprint arXiv:2102.07405, 2021
22021
Natural-gradient stochastic variational inference for non-conjugate structured variational autoencoder
W Lin, ME Khan, N Hubacher, D Nielsen
12017
Structured second-order methods via natural gradient descent
W Lin, F Nielsen, ME Khan, M Schmidt
arXiv preprint arXiv:2107.10884, 2021
2021
Variational Inference on Deep Exponential Family by using Variational Inferences on Conjugate Models
ME Khan, W Lin
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Articles 1–14