Jennifer Gillenwater

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

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

@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,
}

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

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}

@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,
}