The University of Washington is a leader in both Computer Science and Statistics, creating a unique institution for performing cutting-edge Machine Learning research. This research occurs around many areas of campus, lead by a diverse set of faculty. The MODE Lab brings together faculty, students, and postdocs in CSE and Statistics. The focus of the lab is on Machine learning, Optimization, Distributed systems, and (E) statistics (or, for Spanish speakers, Estadística). Some example topics include:
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@inproceedings{ma:foti:fox:2017:sgmcmchmm, author = {Ma, Y. and Foti, N. J. and Fox, E. B.}, title = {Stochastic gradient {MCMC} methods for hidden {M}arkov models}, booktitle = {International Conference on Machine Learning}, year = {2017}, link = {https://arxiv.org/abs/1706.04632} }
@inproceedings{miller:foti:adams:2017:vboost, author = {Miller, A. C. and Foti, N. J. and Adams, R. P.}, title = {Variational boosting: Iteratively refining posterior approximations}, booktitle = {International Conference on Machine Learning}, year = {2017}, link = {http://proceedings.mlr.press/v70/miller17a/miller17a.pdf} }
@article{miller:foti:damour:adams:reducegv, author = {Miller, A.C. and Foti, N. J. and D'Amour, A. and Adams, R. P.}, title = {Reducing reparameterization gradient variance for {M}onte {C}arlo variational inference}, booktitle = {Advances in Neural Information Processing Systems}, year = {2017}, link = {https://arxiv.org/abs/1705.07880} }
@inproceedings{Chen:ICLR16, title = {Net2Net: Accelerating Learning via Knowledge Transfer}, author = {Chen, T. and Goodfellow, I. and Shlens, J.}, booktitle = {International Conference on Learning Representation}, link = {http://arxiv.org/abs/1511.05641}, year = {2016} }
@inproceedings{Tank:KDD_cd_16, title = {Identifiability of Non-Gaussian Structural VAR Models for Subsampled and Mixed Frequency Time Series}, author = {Tank, A. and Fox, E. B. and Shojaie, A.}, booktitle = {Causal Discovery KDD Workshop}, link = {http://nugget.unisa.edu.au/CD2016/fulltext/KDD_subsamp.pdf}, year = {2016} }
@inproceedings{Aicher:KDDMiLeTS16:Scalable, title = {Scalable clustering of correlated time series using expectation propagation}, author = {Aicher, C. and Fox, E. B.}, booktitle = {2nd SIGKDD Workshop on Mining and Learning from Time Series}, year = {2016}, link = {http://www-bcf.usc.edu/%7Eliu32/milets16/paper/MiLeTS_2016_paper_23.pdf} }
@inproceedings{Foti:Nadkarni:Lee:Fox:KDDMiLeTS16, title = {Sparse plus low-rank graphical models of time series for functional connectivity in MEG}, author = {Foti, N. and Nadkarni, R. and Lee, A. KC and Fox, E. B.}, booktitle = {2nd SIGKDD Workshop on Mining and Learning from Time Series}, link = {http://www-bcf.usc.edu/%7Eliu32/milets16/paper/MiLeTS_2016_paper_22.pdf}, year = {2016} }
@inproceedings{Tank:KDD_ts_16, title = {Granger Causality Networks for Categorical Time Series}, author = {Tank, A. and Fox, E. B. and Shojaie, A.}, booktitle = {2nd SIGKDD Workshop on Mining and Learning from Time Series}, link = {http://www-bcf.usc.edu/%7Eliu32/milets16/paper/MiLeTS_2016_paper_24.pdf}, year = {2016} }
@article{Aldor-Noiman:StatisticaSinica2016, title = {Spatio-Temporal Low Count Processes with Application to Violent Crime Events}, author = {Aldor-Noiman, S. and Brown, L.D. and Fox, E.B. and Stine, R.A.}, journal = {Statistica Sinica}, volume = {26}, pages = {1587--1610}, year = {2016} }
@article{Baldassano:JNE2016, title = {A Novel Seizure Detection Algorithm Informed by Hidden {M}arkov Model Event States}, author = {Baldassano, S. and Wulsin, D. and Ung, H. and Blevins, T. and Brown, M.-G. and Fox, E.B. and Litt, B.}, journal = {Journal of Neural Engineering}, volume = {13}, number = {3}, pages = {036011}, year = {2016} }
@article{Davis:Epilepsia2016, title = {Mining Continuous Intracranial {EEG} in Focal Canine Epilepsy: {R}elating Interictal Bursts to Seizure Onsets}, author = {Davis, K. and Ung, H. and Wulsin, D. and Wagenaar, J. and Fox, E.B. and Patterson, E. and Vite, C. and Worrell, G. and Litt, B.}, journal = {Epilepsia}, volume = {57}, number = {1}, pages = {89--98}, year = {2016} }
@unpublished{Ma:Fox:Chen:Wu:2016, title = {A Unifying Framework for Devising Efficient and Irreversible MCMC Samplers}, author = {Ma, Y.-A. and Fox, E. and Chen, T. and Wu, L.}, link = {https://arxiv.org/abs/1608.05973}, year = {2016} }
@inproceedings{Tank:Foti:Fox:2015, title = {Bayesian structure learning for stationary time series}, author = {Tank, A and Foti, N. J. and Fox, E. B.}, booktitle = {Uncertainty in Artificial Intelligence}, link = {http://arxiv.org/pdf/1505.03131v2.pdf}, year = {2015} }
@inproceedings{Gillenwater:NIPS2014, author = {Gillenwater, J. and Kulesza, A. and Fox, E.B. and Taskar, B.}, title = {Expectation-Maximization for Learning Determinantal Point Processes}, booktitle = {Neural Information Processing Systems 27}, year = {2015}, publisher = {MIT Press} }
@inproceedings{Johnson:ICML2015, author = {Johnson, T. B. and Guestrin, C.}, title = {Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization}, booktitle = {International Conference on Machine Learning}, link = {http://jmlr.org/proceedings/papers/v37/johnson15.pdf}, year = {2015} }
@inproceedings{Chen:AISTATS15, author = {Chen, T. and Singh, S. and Taskar, B. and Guestrin, C.}, title = {Efficient Second-Order Gradient Boosting for Conditional Random Fields}, link = {http://homes.cs.washington.edu/%7Etqchen/data/pdf/GBCRF-AISTATS15.pdf}, booktitle = {International Conference on Artificial Intelligence and Statistics}, year = {2015} }
@inproceedings{Tank:2015a, author = {Tank, A. and Foti, N. J. and Fox, E. B.}, title = {Streaming variational inference for {B}ayesian nonparametric mixture models}, booktitle = {International Conference on Artificial Intelligence and Statistics}, link = {http://arxiv.org/abs/1412.0694}, year = {2015} }
@inproceedings{Ma:Chen:Fox:2015, title = {A Complete Recipe for Stochastic Gradient {MCMC}}, author = {Y.-A, Ma and Chen, T. and Fox, E. B.}, booktitle = {Advances in Neural Information Processing Systems}, link = {http://papers.nips.cc/paper/5891-a-complete-recipe-for-stochastic-gradient-mcmc.pdf}, year = {2015} }
@article{AdamsFoxSudderthTeh:2015, title = {Guest Editors’ Introduction to the Special Issue on Bayesian Nonparametrics}, author = {Adams, R.P. and Fox, E.B. and Sudderth, E.B. and Teh, Y.W.}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {37}, number = {2}, pages = {209--211}, year = {2015}, publisher = {IEEE} }
@article{Fox:JMLR2015, title = {Bayesian Nonparametric Covariance Regression}, author = {Fox, E.B. and Dunson, D.B.}, journal = {Journal of Machine Learning Research}, volume = {16}, pages = {2501--2542}, year = {2015} }
@inproceedings{Affandi:ICML2014, author = {Affandi, R.H. and Fox, E.B. and Adams, R.P. and Taskar, B.}, title = {Learning the Parameters of Determinantal Point Process Kernels}, booktitle = {Proc. International Conference on Machine Learning}, year = {2014}, month = jun }
@inproceedings{Affandi:NIPS2013, author = {Affandi, R.H. and Fox, E.B. and Taskar, B.}, title = {Approximate Inference in Continuous Determinantal Processes}, booktitle = {Neural Information Processing Systems 26}, year = {2014}, publisher = {MIT Press} }
@inproceedings{Chen:ICML14, author = {Chen, T. and Fox, E. B. and Guestrin, C.}, title = {Stochastic Gradient {H}amiltonian Monte Carlo}, booktitle = {International Conference on Machine Learning}, link = {http://arxiv.org/abs/1402.4102}, code = {http://www.github.com/tqchen/ML-SGHMC}, year = {2014} }
@inproceedings{Foti:Xu:Laird:Fox:2014, title = {Stochastic variational inference for hidden {M}arkov models}, author = {Foti, N. J. and Xu, J. and Laird, D. and Fox, E. B.}, booktitle = {Advances in Neural Information Processing Systems}, link = {http://papers.nips.cc/paper/5560-stochastic-variational-inference-for-hidden-markov-models.pdf}, year = {2014} }
@article{Fox:AOAS2014, title = {Joint Modeling of Multiple Related Time Series via the Beta Process with Application to Motion Capture Segmentation}, author = {Fox, E.B. and Hughes, M.C. and Sudderth, E.B. and Jordan, M.I.}, journal = {Annals of Applied Statistics}, volume = {8}, number = {3}, pages = {1281--1313}, year = {2014} }
@inbook{FoxJordan:14, author = {Fox, E.B. and Jordan, M.I.}, chapter = {Mixed Membership Models for Time Series}, editor = {Airoldi, E. and Blei, D. and Erosheva, E. and Fienberg, S.E. and Bokalders, K.}, publisher = {Chapman \& Hall}, title = {Handbook on Mixed Membership Models}, year = {2014} }
@article{Drausin:AIJ2014, title = {Modeling the Complex Dynamics and Changing Correlations of Epileptic Events}, author = {Wulsin, D. and Fox, E.B. and Litt, B.}, journal = {Artificial Intelligence}, volume = {216}, pages = {55--75}, year = {2014} }
@article{Zaman:AOAS2014, title = {A {B}ayesian Approach for Predicting the Popularity of Tweets}, author = {Zaman, T. and Fox, E.B. and Bradlow, E.T.}, journal = {Annals of Applied Statistics}, volume = {8}, number = {3}, pages = {1583--1611}, year = {2014} }
@inproceedings{Wulsin:ICML2013, author = {Drausin, W. and Fox, E.B. and Litt, B.}, title = {Parsing Epileptic Events Using a {M}arkov Switching Process Model for Correlated Time Series}, booktitle = {Proc. International Conference on Machine Learning}, year = {2013}, month = jun }
@inproceedings{Affandi:AISTATS2013, author = {Affandi, R.H. and Kulesza, A. and Fox, E.B. and Taskar, B.}, title = {Nystrom Approximation for Large-Scale Determinantal Processes}, booktitle = {Proc. International Conference on Artificial Intelligence and Statistics}, year = {2013}, month = apr }
@inproceedings{ElArini:KDD2013, author = {El-Arini, K. and Xu, M. and Fox, E.B. and Guestrin, C.}, title = {Representing Documents Through Their Readers}, booktitle = {Proc. Conference on Knowledge, Discovery, and Data Mining}, year = {2013}, month = aug }
@inproceedings{FoxDunson:NIPS2012, author = {Fox, E.B. and Dunson, D.B.}, title = {Multiresolution {G}aussian Processes}, booktitle = {Neural Information Processing Systems 25}, year = {2013}, publisher = {MIT Press} }
@inproceedings{Hughes:NIPS2012, author = {Hughes, M.C. and Fox, E.B. and Sudderth, E.B.}, title = {Effective Split-Merge {M}onte {C}arlo Methods for Nonparametric Models of Sequential Data}, booktitle = {Neural Information Processing Systems 25}, year = {2013}, publisher = {MIT Press} }
@inproceedings{Fyshe:AISTATS2012, author = {Fyshe, A. and Fox, E.B. and Dunson, D.B. and Mitchell, T.M.}, title = {Hierarchical Latent Dictionaries for Models of Brain Activation}, booktitle = {Proc. International Conference on Artificial Intelligence and Statistics}, year = {2012}, month = apr }
@inproceedings{Affandi:UAI2012, author = {Affandi, R.H. and Kulesza, A. and Fox, E.B.}, title = {Markov Determinantal Point Processes}, booktitle = {Proc. Conference on Uncertainty in Artificial Intelligence}, year = {2012}, month = aug }