Trevor Campbell
Trevor Campbell
Assistant Professor, Statistics, UBC
Verified email at stat.ubc.ca - Homepage
TitleCited byYear
Coresets for scalable Bayesian logistic regression
J Huggins, T Campbell, T Broderick
Advances in Neural Information Processing Systems, 4080-4088, 2016
712016
Dynamic clustering via asymptotics of the dependent Dirichlet process mixture
T Campbell, M Liu, B Kulis, JP How, L Carin
Advances in Neural Information Processing Systems, 449-457, 2013
432013
Edge-exchangeable graphs and sparsity
D Cai, T Campbell, T Broderick
Advances in Neural Information Processing Systems, 4249-4257, 2016
362016
Bayesian nonparametric set construction for robust optimization
T Campbell, JP How
2015 American Control Conference (ACC), 4216-4221, 2015
312015
Streaming, distributed variational inference for Bayesian nonparametrics
T Campbell, J Straub, JW Fisher III, JP How
Advances in Neural Information Processing Systems, 280-288, 2015
292015
Automated scalable Bayesian inference via Hilbert coresets
T Campbell, T Broderick
The Journal of Machine Learning Research 20 (1), 551-588, 2019
242019
Bayesian coreset construction via greedy iterative geodesic ascent
T Campbell, T Broderick
arXiv preprint arXiv:1802.01737, 2018
222018
Small-variance nonparametric clustering on the hypersphere
J Straub, T Campbell, JP How, JW Fisher
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
222015
Efficient global point cloud alignment using Bayesian nonparametric mixtures
J Straub, T Campbell, JP How, JW Fisher
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
212017
Exchangeable trait allocations
T Campbell, D Cai, T Broderick
Electronic Journal of Statistics 12 (2), 2290-2322, 2018
112018
Approximate decentralized Bayesian inference
T Campbell, JP How
arXiv preprint arXiv:1403.7471, 2014
112014
Truncated random measures
T Campbell, JH Huggins, JP How, T Broderick
Bernoulli 25 (2), 1256-1288, 2019
62019
Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach
JH Huggins, T Campbell, M Kasprzak, T Broderick
arXiv preprint arXiv:1809.09505, 2018
62018
Multiagent allocation of markov decision process tasks
T Campbell, L Johnson, JP How
2013 American Control Conference, 2356-2361, 2013
62013
Data-dependent compression of random features for large-scale kernel approximation
R Agrawal, T Campbell, JH Huggins, T Broderick
arXiv preprint arXiv:1810.04249, 2018
42018
Scalable Gaussian process inference with finite-data mean and variance guarantees
JH Huggins, T Campbell, M Kasprzak, T Broderick
arXiv preprint arXiv:1806.10234, 2018
42018
Multiagent planning with bayesian nonparametric asymptotics
TDJ Campbell
Massachusetts Institute of Technology, 2013
32013
Dynamic Clustering Algorithms via Small-Variance Analysis of Markov Chain Mixture Models
T Campbell, B Kulis, J How
IEEE transactions on pattern analysis and machine intelligence 41 (6), 1338-1352, 2018
22018
Sparse Variational Inference: Bayesian Coresets from Scratch
T Campbell, B Beronov
arXiv preprint arXiv:1906.03329, 2019
12019
Universal Boosting Variational Inference
T Campbell, X Li
arXiv preprint arXiv:1906.01235, 2019
12019
The system can't perform the operation now. Try again later.
Articles 1–20