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Jennifer Gillenwater
Jennifer Gillenwater
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Title
Cited by
Cited by
Year
Posterior regularization for structured latent variable models
K Ganchev, J Graça, J Gillenwater, B Taskar
The Journal of Machine Learning Research 11, 2001-2049, 2010
5982010
Dependency grammar induction via bitext projection constraints
K Ganchev, J Gillenwater, B Taskar
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL …, 2009
1542009
Near-optimal map inference for determinantal point processes
J Gillenwater, A Kulesza, B Taskar
Advances in Neural Information Processing Systems 25, 2012
1422012
Practical diversified recommendations on youtube with determinantal point processes
M Wilhelm, A Ramanathan, A Bonomo, S Jain, EH Chi, J Gillenwater
Proceedings of the 27th ACM International Conference on Information and …, 2018
1372018
Discovering diverse and salient threads in document collections
J Gillenwater, A Kulesza, B Taskar
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural …, 2012
1062012
Expectation-maximization for learning determinantal point processes
JA Gillenwater, A Kulesza, E Fox, B Taskar
Advances in Neural Information Processing Systems 27, 2014
1012014
Federated learning via posterior averaging: A new perspective and practical algorithms
M Al-Shedivat, J Gillenwater, E Xing, A Rostamizadeh
arXiv preprint arXiv:2010.05273, 2020
892020
Sparsity in dependency grammar induction
J Gillenwater, K Ganchev, J Graça, F Pereira, B Taskar
Proceedings of the ACL 2010 Conference Short Papers, 194-199, 2010
572010
Approximate inference for determinantal point processes
J Gillenwater
University of Pennsylvania, 2014
402014
Posterior sparsity in unsupervised dependency parsing
J Gillenwater, K Ganchev, J Graça, F Pereira, B Taskar
The Journal of Machine Learning Research 12, 455-490, 2011
382011
Differentially private quantiles
J Gillenwater, M Joseph, A Kulesza
International Conference on Machine Learning, 3713-3722, 2021
302021
A tree-based method for fast repeated sampling of determinantal point processes
J Gillenwater, A Kulesza, Z Mariet, S Vassilvtiskii
International Conference on Machine Learning, 2260-2268, 2019
262019
Submodular hamming metrics
JA Gillenwater, RK Iyer, B Lusch, R Kidambi, JA Bilmes
Advances in Neural Information Processing Systems 28, 2015
202015
Synthesizable high level hardware descriptions: using statically typed two-level languages to guarantee verilog synthesizability
J Gillenwater, G Malecha, C Salama, AY Zhu, W Taha, J Grundy, ...
Proceedings of the 2008 ACM SIGPLAN symposium on Partial evaluation and …, 2008
172008
Graph-based posterior regularization for semi-supervised structured prediction
L He, J Gillenwater, B Taskar
Proceedings of the Seventeenth Conference on Computational Natural Language …, 2013
162013
Posterior regularization for structured latent variable models
K Ganchev, J Graca, J Gillenwater, B Taskar
Advances in Neural Information Processing Systems 91, 129-136, 2009
152009
Scalable learning and MAP inference for nonsymmetric determinantal point processes
M Gartrell, I Han, E Dohmatob, J Gillenwater, VE Brunel
arXiv preprint arXiv:2006.09862, 2020
142020
Plume: Differential privacy at scale
K Amin, J Gillenwater, M Joseph, A Kulesza, S Vassilvitskii
arXiv preprint arXiv:2201.11603, 2022
132022
MAP inference for customized determinantal point processes via maximum inner product search
I Han, J Gillenwater
International Conference on Artificial Intelligence and Statistics, 2797-2807, 2020
132020
Maximizing induced cardinality under a determinantal point process
JA Gillenwater, A Kulesza, S Vassilvitskii, ZE Mariet
Advances in Neural Information Processing Systems 31, 2018
132018
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