• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 32 matches

• 2023
• 
  Travis Dick, Jennifer Gillenwater, Matthew Joseph:
  Better Private Linear Regression Through Better Private Feature Selection. NeurIPS 2023
• 
  Travis Dick, Jennifer Gillenwater, Matthew Joseph:
  Better Private Linear Regression Through Better Private Feature Selection. CoRR abs/2306.00920 (2023)
• 2022
• 
  Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi:
  Scalable Sampling for Nonsymmetric Determinantal Point Processes. ICLR 2022
• 
  Jennifer Gillenwater, Matthew Joseph, Andres Muñoz Medina, Mónica Ribero Diaz:
  A Joint Exponential Mechanism For Differentially Private Top-k. ICML 2022: 7570-7582
• 
  Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi:
  Scalable Sampling for Nonsymmetric Determinantal Point Processes. CoRR abs/2201.08417 (2022)
• 
  Kareem Amin, Jennifer Gillenwater, Matthew Joseph, Alex Kulesza, Sergei Vassilvitskii:
  Plume: Differential Privacy at Scale. CoRR abs/2201.11603 (2022)
• 
  Jennifer Gillenwater, Matthew Joseph, Andrés Muñoz Medina, Mónica Ribero:
  A Joint Exponential Mechanism For Differentially Private Top-k. CoRR abs/2201.12333 (2022)
• 2021
• 
  Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
  Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. ICLR 2021
• 
  Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel:
  Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. ICLR 2021
• 
  Jennifer Gillenwater, Matthew Joseph, Alex Kulesza:
  Differentially Private Quantiles. ICML 2021: 3713-3722
• 
  Jennifer Gillenwater, Matthew Joseph, Alex Kulesza:
  Differentially Private Quantiles. CoRR abs/2102.08244 (2021)
• 
  Cecilia Ferrando, Jennifer Gillenwater, Alex Kulesza:
  Combining Public and Private Data. CoRR abs/2111.00115 (2021)
• 2020
• 
  Insu Han, Jennifer Gillenwater:
  MAP Inference for Customized Determinantal Point Processes via Maximum Inner Product Search. AISTATS 2020: 2797-2807
• 
  Mike Gartrell, Insu Han, Elvis Dohmatob, Jennifer Gillenwater, Victor-Emmanuel Brunel:
  Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes. CoRR abs/2006.09862 (2020)
• 
  Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
  Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. CoRR abs/2010.05273 (2020)
• 2019
• 
  Jennifer Gillenwater, Alex Kulesza, Zelda Mariet, Sergei Vassilvitskii:
  A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes. ICML 2019: 2260-2268
• 2018
• 
  Mark Wilhelm, Ajith Ramanathan, Alexander Bonomo, Sagar Jain, Ed H. Chi, Jennifer Gillenwater:
  Practical Diversified Recommendations on YouTube with Determinantal Point Processes. CIKM 2018: 2165-2173
• 
  Jennifer A. Gillenwater, Alex Kulesza, Sergei Vassilvitskii, Zelda E. Mariet:
  Maximizing Induced Cardinality Under a Determinantal Point Process. NeurIPS 2018: 6911-6920
• 2015
• 
  Jennifer Gillenwater, Rishabh K. Iyer, Bethany Lusch, Rahul Kidambi, Jeff A. Bilmes:
  Submodular Hamming Metrics. NIPS 2015: 3141-3149
• 
  Jennifer Gillenwater, Rishabh K. Iyer, Bethany Lusch, Rahul Kidambi, Jeff A. Bilmes:
  Submodular Hamming Metrics. CoRR abs/1511.02163 (2015)
• 2014
• 
  Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Benjamin Taskar:
  Expectation-Maximization for Learning Determinantal Point Processes. NIPS 2014: 3149-3157
• 
  Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Ben Taskar:
  Expectation-Maximization for Learning Determinantal Point Processes. CoRR abs/1411.1088 (2014)
• 2013
• 
  Luheng He, Jennifer Gillenwater, Ben Taskar:
  Graph-Based Posterior Regularization for Semi-Supervised Structured Prediction. CoNLL 2013: 38-46
• 
  Jennifer Gillenwater, Xiaodong He, Jianfeng Gao, Li Deng:
  End-to-end learning of parsing models for information retrieval. ICASSP 2013: 3312-3316
• 2012
• 
  Jennifer Gillenwater, Alex Kulesza, Ben Taskar:
  Discovering Diverse and Salient Threads in Document Collections. EMNLP-CoNLL 2012: 710-720
• 
  Jennifer Gillenwater, Alex Kulesza, Ben Taskar:
  Near-Optimal MAP Inference for Determinantal Point Processes. NIPS 2012: 2744-2752
• 2011
• 
  Jennifer Gillenwater, Kuzman Ganchev, João Graça, Fernando Pereira, Ben Taskar:
  Posterior Sparsity in Unsupervised Dependency Parsing. J. Mach. Learn. Res. 12: 455-490 (2011)
• 2010
• 
  Kuzman Ganchev, João Graça, Jennifer Gillenwater, Ben Taskar:
  Posterior Regularization for Structured Latent Variable Models. J. Mach. Learn. Res. 11: 2001-2049 (2010)
• 
  Jennifer Gillenwater, Gregory Malecha, Cherif R. Salama, Angela Yun Zhu, Walid Taha, Jim Grundy, John O'Leary:
  Synthesizable High Level Hardware Descriptions. New Gener. Comput. 28(4): 339-369 (2010)
• 
  Jennifer Gillenwater, Kuzman Ganchev, João Graça, Fernando Pereira, Ben Taskar:
  Sparsity in Dependency Grammar Induction. ACL (2) 2010: 194-199

skipping 2 more matches