Jennifer Gillenwater

Senior Research Scientist, Google

CV

Emails:
jgillenw at gmail dot com
jengi at google dot com

Research Interests:
Machine Learning and Privacy

Code

Differential Privacy
Top-k sequences
Quantiles (ICML 2021 paper)
Medians (ICML LXAI 2020 paper)

Determinantal Point Processes
Non-sym DPP sampling (ICLR 2022 paper)
Non-sym DPP learning and approx-MAP (ICLR 2021 paper)
DPP approx-MAP (NIPS 2012 paper)
DPP learning via EM (NIPS 2013 paper)

Posterior Regularization
General PR toolkit



Publications

2022

A Joint Exponential Mechanism for Differentially Private Top-k [Bibtex]
@inproceedings{gillenwater2022arxiv,
  title =       {{A Joint Exponential Mechanism for Differentially Private Top-k}},
  author =      {Gillenwater, J. and Joseph, M. and Medina, A. and Ribero, M.},
  booktitle =   {ArXiv preprint},
  year =        2022,
}

Jennifer Gillenwater, Matthew Joseph, Andrés Muñoz Medina, and Mónica Ribero. ArXiv preprint, 2022.
[Code]


Plume: Differential Privacy at Scale [Bibtex]
@inproceedings{kamin2022arxiv,
  title =       {{Plume: Differential Privacy At Scale}},
  author =      {Amin, K. and Gillenwater, J. and Joseph, M. and Kulesza, A. and Vassilvitskii, S.},
  booktitle =   {ArXiv preprint},
  year =        2022,
}

Kareem Amin, Jennifer Gillenwater, Matthew Joseph, Alex Kulesza, and Sergei Vassilvitskii. ArXiv preprint, 2022.


Scalable Sampling for Nonsymmetric Determinantal Point Processes [Bibtex]
@inproceedings{han2022iclr,
  title =       {{Scalable Sampling for Nonsymmetric Determinantal Point Processes}},
  author =      {Han, I. and Gartrell, M. and Gillenwater, J. and Dohmatob, E. and Karbasi, A.},
  booktitle =   {Proc.\ International Conference on Learning Representations (ICLR)},
  year =        2022,
}

Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, and Amin Karbasi. International Conference on Learning Representations (ICLR), 2022.
[Code] [Open Review]



2021

Combining Public and Private Data [Bibtex]
@inproceedings{ferrando2021bpriml,
  title =       {{Combining Public and Private Data}},
  author =      {Ferrando, C. and Gillenwater, J. and Kulesza, A.},
  booktitle =   {Proc.\ Privacy in Machine Learning (PriML) Workshop at Neural Information Processing Systems (NeurIPS)},
  year =        2021,
}

Cecila Ferrando, Jennifer Gillenwater, and Alex Kulesza. Privacy in Machine Learning (PriML) Workshop at Neural Information Processing Systems (NeurIPS), 2021.


A Joint Exponential Mechanism for Differentially Private Top-k Set [Bibtex]
@inproceedings{gillenwater2021apriml,
  title =       {{A Joint Exponential Mechanism for Differentially Private Top-k Set}},
  author =      {Gillenwater, J. and Joseph, M. and Medina, A. and Ribero, M.},
  booktitle =   {Proc.\ Privacy in Machine Learning (PriML) Workshop at Neural Information Processing Systems (NeurIPS)},
  year =        2021,
}

Jennifer Gillenwater, Matthew Joseph, Andrés Muñoz Medina, and Mónica Ribero. Privacy in Machine Learning (PriML) Workshop at Neural Information Processing Systems (NIPS), 2021.


Differentially Private Quantiles [Bibtex]
@inproceedings{gillenwater2021icml,
  title =       {{Differentially Private Quantiles}},
  author =      {Gillenwater, J. and Joseph, M. and Kulesza, A.},
  booktitle =   {Proc.\ International Conference on Machine Learning (ICML)},
  year =        2021,
}

Jennifer Gillenwater, Matthew Joseph, and Alex Kulesza. International Conference on Machine Learning (ICML), 2021.
[Code]


Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms [Bibtex]
@inproceedings{alshedivat2021iclr,
  title =       {{Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms}},
  author =      {Al-Shedivat, M. and Gillenwater, J. and Xing, E. and Rostamizadeh, A.},
  booktitle =   {Proc.\ International Conference on Learning Representations (ICLR)},
  year =        2021,
}

Maruan Al-Shedivat, Jennifer Gillenwater, Eric Xing, and Afshin Rostamizadeh. International Conference on Learning Representations (ICLR), 2021.
[Code] [Poster] [Open Review] [Blog]


Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes [Bibtex]
@inproceedings{gartrell2021iclr,
  title =       {{Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes}},
  author =      {Gartrell, M. and Han, I. and Dohmatob, E. and Gillenwater, J. and Brunel V.E.},
  booktitle =   {Proc.\ International Conference on Learning Representations (ICLR)},
  year =        2021,
}

Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, and Victor-Emmanuel Brunel. International Conference on Learning Representations (ICLR), 2021.
[Code] [Open Review]



2020

Duff: A Dataset-Distance-Based Utility Function Family for the Exponential Mechanism [Bibtex]
@inproceedings{medina2020icmllxai,
  title =       {{Duff: A Dataset-Distance-Based Utility Function Family for the Exponential Mechanism}},
  author =      {Medina, A. and Gillenwater, J.},
  booktitle =   {Proc.\ LatinX in AI Workshop (LXAI) at the International Conference on Machine Learning (ICML)},
  year =        2020,
}

Andrés Muñoz Medina and Jennifer Gillenwater. LatinX in AI Workshop at the International Conference on Machine Learning (ICML LXAI), 2020.
[Code]


MAP Inference for Customized Determinantal Point Processes via Maximum Inner Product Search [Bibtex]
@inproceedings{han2020aistats,
  title =       {{MAP Inference for Customized Determinantal Point Processes via Maximum Inner Product Search}},
  author =      {Han, I. and Gillenwater, J.},
  booktitle =   {Proc.\ International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year =        2020,
}

Insu Han and Jennifer Gillenwater. International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
[Supplement]



2019

A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes [Bibtex]
@inproceedings{gillenwater2019icml,
  title =       {{A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes}},
  author =      {Gillenwater, J. and Kulesza, A. and Mariet, Z. and Vassilvitskii, S.},
  booktitle =   {Proc.\ International Conference on Machine Learning (ICML)},
  year =        2019,
}

Jennifer Gillenwater, Alex Kulesza, Zelda Mariet, and Sergei Vassilvitskii. International Conference on Machine Learning (ICML), 2019.
[Supplement] [Poster] [Slides]



2018

Maximizing Induced Cardinality Under a Determinantal Point Process [Bibtex]
@inproceedings{gillenwater2018nips,
  title =       {{Maximizing Induced Cardinality Under a Determinantal Point Process}},
  author =      {Gillenwater, J. and Kulesza, A. and Mariet, Z. and Vassilvitskii, S.},
  booktitle =   {Proc.\ Neural Information Processing Systems (NIPS)},
  year =        2018,
}

Jennifer Gillenwater, Alex Kulesza, Zelda Mariet, and Sergei Vassilvitskii. Neural Information Processing Systems (NIPS), 2018.
[Supplement] [Poster]


Practical Diversified Recommendations on YouTube with Determinantal Point Processes [Bibtex]
@inproceedings{wilhelm2018cikm,
  title = {{Practical Diversified Recommendations on YouTube with Determinantal Point Processes}},
  author = {Wilhelm, M. and Ramanathan, A. and Bonomo, A. and Jain, S. and Chi, E.H. and Gillenwater, J.},
  booktitle = {Proc.\ Conference on Information and Knowledge Management (CIKM)},
  year = 2018,
}

Mark Wilhelm, Ajith Ramanathan, Alexander Bonomo, Sagar Jain, Ed H. Chi, Jennifer Gillenwater. International Conference on Information and Knowledge Management (CIKM), 2018.



2015

Submodular Hamming Metrics [Bibtex]
@inproceedings{gillenwater2015nips,
  title =       {{Submodular Hamming Metrics}},
  author =      {Gillenwater, J. and Iyer, R. and Lusch, B. and Kidambi, R. and Bilmes, J.},
  booktitle =   {Proc.\ Neural Information Processing Systems (NIPS)},
  year =        2015,
}

Jennifer Gillenwater, Rishabh Iyer, Bethany Lusch, Rahul Kidambi, and Jeff Bilmes. Neural Information Processing Systems (NIPS), 2015.
[Supplement] [Poster]



2014

Approximate Inference for Determinantal Point Processes [Bibtex]
@phdthesis{gillenwater2014thesis,
  author       = {Gillenwater, J.}, 
  title        = {{Approximate Inference for Determinantal Point Processes}},
  school       = {University of Pennsylvania},
  year         = 2014,
}

Jennifer Gillenwater. PhD Thesis, University of Pennsylvania, 2014.
[Slides (.key) (.pdf)]


Expectation-Maximization for Learning Determinantal Point Processes [Bibtex]
@inproceedings{gillenwater2014nips,
  title =       {{Expectation-Maximization for Learning Determinantal Point Processes}},
  author =      {Gillenwater, J. and Kulesza, A. and Fox, E. and Taskar, B.},
  booktitle =   {Proc.\ Neural Information Processing Systems (NIPS)},
  year =        2014,
}

Jennifer Gillenwater, Alex Kulesza, Emily Fox, and Ben Taskar. Neural Information Processing Systems (NIPS), 2014.
[Supplement] [Code] [Poster]


Maximization of Non-Monotone Submodular Functions [Bibtex]
@techreport{gillenwater2014tr,
  title = 	{{Maximization of Non-Monotone Submodular Functions}},
  author =	{Gillenwater, J.},
  number =	{MS-CIS-14-01},
  institution =	{University of Pennsylvania},
  year = 	2014,
}

Jennifer Gillenwater. Written Preliminary Examination II (WPE-II), 2014.
[Slides]



2013

Graph-Based Posterior Regularization for Semi-Supervised Structured Prediction [Bibtex]
@inproceedings{he2013conll,
  title =	{{Graph-Based Posterior Regularization for Semi-Supervised Structured Prediction}},
  author =	{He, L. and Gillenwater, J. and Taskar, B.},
  booktitle =	{Proc.\ Conference on Computational Natural Language Learning (CoNLL)},
  year =	2013,
}

Luheng He, Jennifer Gillenwater, and Ben Taskar. Conference on Computational Natural Language Learning (CoNLL), 2013.
[Supplement] [Code] [Poster] [Slides (.key) (.pdf)]


End-to-End Learning of Parsing Models for Information Retrieval [Bibtex]
@inproceedings{gillenwater2013icassp,
  title = 	{{End-to-End Learning of Parsing Models for Information Retrieval}},
  author = 	{Gillenwater, J. and He, X. and Gao, J. and Deng, L.},
  booktitle =	{Proc.\ International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
  year =	2013,
}

Jennifer Gillenwater, Xiaodong He, Jianfeng Gao, and Li Deng. International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2013.
[Poster]



2012

Near-Optimal MAP Inference for Determinantal Point Processes [Bibtex]
@inproceedings{gillenwater2012nips,
  title =	 {{Near-Optimal MAP Inference for Determinantal Point Processes}},
  author =	 {Gillenwater, J. and Kulesza, A. and Taskar, B.},
  booktitle =	 {Proc.\ Neural Information Processing Systems (NIPS)},
  year =	 2012,
}

Jennifer Gillenwater, Alex Kulesza, and Ben Taskar. Neural Information Processing Systems (NIPS), 2012.
[Supplement] [Code and Data] [Poster] [Slides (.key) (.pdf)] [Video]


Discovering Diverse and Salient Threads in Document Collections [Bibtex]
@inproceedings{gillenwater2012emnlp,
  title =	 {{Discovering Diverse and Salient Threads in Document Collections}},
  author =	 {Gillenwater, J. and Kulesza, A. and Taskar, B.},
  booktitle =	 {Proc.\ Empirical Methods in Natural Language Processing (EMNLP)},
  year =	 2012,
}

Jennifer Gillenwater, Alex Kulesza, and Ben Taskar. Empirical Methods in Natural Language Processing (EMNLP), 2012.
[Supplement] [Poster]



2011

Large-Scale Modeling of Diverse Paths using Structured k-DPPs
Jennifer Gillenwater, Alex Kulesza, and Ben Taskar. New York Academy of Sciences (NYAS) Machine Learning Symposium, 2011.
[Poster] [Slides]

Large-Scale Modeling of Diverse Paths using Structured k-DPPs
Jennifer Gillenwater, Alex Kulesza, and Ben Taskar. Mid-Atlantic Student Colloquium on Speech, Language, and Learning, 2011.
[Poster] [Spotlight]

Posterior Sparsity in Unsupervised Dependency Parsing [Bibtex]
@article{gillenwater2011jmlr,
  title =	 {{Posterior Sparsity in Unsupervised Dependency Parsing}},
  author =	 {Gillenwater, J. and Ganchev, K. and Gra\c{c}a, J. and Pereira, F. and Taskar, B.},
  journal =	 {Journal of Machine Learning Research (JMLR)},
  year =	 2011,
}

Jennifer Gillenwater, Kuzman Ganchev, João Graça, Fernando Pereira, and Ben Taskar. Journal of Machine Learning Research (JMLR), 2011.
[PR Toolkit]



2010

Sparsity in Dependency Grammar Induction
Jennifer Gillenwater, Kuzman Ganchev, João Graça, Fernando Pereira, and Ben Taskar. New York Academy of Sciences (NYAS) Machine Learning Symposium, 2010.
[Poster] [Slides]

Sparsity in Dependency Grammar Induction [Bibtex]
@inproceedings{gillenwater2010acl,
  title =	 {{Sparsity in Dependency Grammar Induction}},
  author =	 {Gillenwater, J. and Ganchev, K. and Gra\c{c}a, J. and Pereira, F. and Taskar, B.},
  booktitle =	 {Proc.\ Association for Computational Linguistics (ACL)},
  year =	 2010,
}

Jennifer Gillenwater, Kuzman Ganchev, João Graça, Fernando Pereira, and Ben Taskar. Association for Computational Linguistics (ACL), 2010.
[Poster] [Slides]


Posterior Regularization for Structured Latent Variable Models [Bibtex]
@article{ganchev2010jmlr,
  title =	 {{Posterior Regularization for Structured Latent Variable Models}},
  author =	 {Ganchev, K. and Gra\c{c}a, J. and Gillenwater, J. and Taskar, B.},
  journal =	 {Journal of Machine Learning Research (JMLR)},
  year =	 2010,
}

Kuzman Ganchev, João Graça, Jennifer Gillenwater, and Ben Taskar. Journal of Machine Learning Research (JMLR), 2010.



2009

Sparsity in Grammar Induction
Jennifer Gillenwater, Kuzman Ganchev, João Graça, Fernando Pereira, and Ben Taskar. Neural Information Processing Systems (NIPS) Grammar Induction Workshop, 2009.
[Slides] [Video]

Dependency Grammar Induction via Bitext Projection Constraints [Bibtex]
@inproceedings{ganchev2009acl,
  title =	 {{Dependency Grammar Induction via Bitext Projection Constraints}},
  author =	 {Ganchev, K. and Gillenwater, J. and Taskar, B.},
  booktitle =	 {Proc.\ Association for Computational Linguistics (ACL)},
  year =	 2009,
}

Kuzman Ganchev, Jennifer Gillenwater, and Ben Taskar. Association for Computational Linguistics (ACL), 2009.



2008

Synthesizable High Level Hardware Descriptions [Bibtex]
@inproceedings{gillenwater2008pepm,
  title =	 {{Synthesizable High Level Hardware Descriptions}},
  author =	 {Gillenwater, J. and Malecha, G. and Salama, C. and Zhu, A. and Taha, W. and Grundy, J. and O'Leary, J.},
  booktitle =	 {Proc.\ Partial Evaluation and Program Manipulation (PEPM)},
  year =	 2008,
}

Jennifer Gillenwater, Gregory Malecha, Cherif Salama, Angela Yun Zhu, Walid Taha, Jim Grundy, and John O'Leary, Partial Evaluation and Program Manipulation (PEPM), 2008.



2007

Formalizing and Enhancing Verilog
Jennifer Gillenwater, Gregory Malecha, Cherif Salama, Angela Yun Zhu, Walid Taha, Jim Grundy, and John O'Leary. Technology and Talent for the 21st Century (TECHCON), 2007.

Synthesizable Verilog
Cherif Andraos, Jennifer Gillenwater, Gregory Malecha, Angela Yun Zhu, Walid Taha, Jim Grundy, and John O'Leary. Workshop on Hardware Design and Functional Languages (HFL), 2007.