Alex Kulesza

According to our database, Alex Kulesza authored at least 47 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Practical Considerations for Differential Privacy.

Kareem Amin, Alex Kulesza, Sergei Vassilvitskii

CoRR, 2024

Mean Estimation in the Add-Remove Model of Differential Privacy.

Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Subset-Based Instance Optimality in Private Estimation.

Travis Dick, Alex Kulesza, Ziteng Sun, Ananda Theertha Suresh

Proceedings of the International Conference on Machine Learning, 2023

2022

Plume: Differential Privacy at Scale.

Kareem Amin, Jennifer Gillenwater, Matthew Joseph, Alex Kulesza, Sergei Vassilvitskii

CoRR, 2022

2021

Combining Public and Private Data.

Cecilia Ferrando, Jennifer Gillenwater, Alex Kulesza

CoRR, 2021

Learning with User-Level Privacy.

Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentially Private Quantiles.

Jennifer Gillenwater, Matthew Joseph, Alex Kulesza

Proceedings of the 38th International Conference on Machine Learning, 2021

2019

Differentially Private Covariance Estimation.

Kareem Amin, Travis Dick, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes.

Jennifer Gillenwater, Alex Kulesza, Zelda Mariet, Sergei Vassilvitskii

Proceedings of the 36th International Conference on Machine Learning, 2019

Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy.

Kareem Amin, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Completing State Representations using Spectral Learning.

Nan Jiang, Alex Kulesza, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Maximizing Induced Cardinality Under a Determinantal Point Process.

Jennifer A. Gillenwater, Alex Kulesza, Sergei Vassilvitskii, Zelda E. Mariet

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

The Dependence of Effective Planning Horizon on Model Accuracy.

Nan Jiang, Alex Kulesza, Satinder Singh, Richard L. Lewis

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Improving Predictive State Representations via Gradient Descent.

Nan Jiang, Alex Kulesza, Satinder Singh

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Information Extraction from Larger Multi-layer Social Networks.

Brandon Oselio, Alex Kulesza, Alfred O. Hero III

CoRR, 2015

Socio-Spatial Pareto Frontiers of Twitter Networks.

Brandon Oselio, Alex Kulesza, Alfred O. Hero III

Proceedings of the Social Computing, Behavioral-Cultural Modeling, and Prediction, 2015

Abstraction Selection in Model-based Reinforcement Learning.

Nan Jiang, Alex Kulesza, Satinder Singh

Proceedings of the 32nd International Conference on Machine Learning, 2015

Information extraction from large multi-layer social networks.

Brandon Oselio, Alex Kulesza, Alfred O. Hero III

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Low-Rank Spectral Learning with Weighted Loss Functions.

Alex Kulesza, Nan Jiang, Satinder Singh

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Spectral Learning of Predictive State Representations with Insufficient Statistics.

Alex Kulesza, Nan Jiang, Satinder Singh

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Multi-Layer Graph Analysis for Dynamic Social Networks.

Brandon Oselio, Alex Kulesza, Alfred O. Hero III

IEEE J. Sel. Top. Signal Process., 2014

Social Collaborative Retrieval.

Ko-Jen Hsiao, Alex Kulesza, Alfred O. Hero III

IEEE J. Sel. Top. Signal Process., 2014

Diversifying Sparsity Using Variational Determinantal Point Processes.

Nematollah Kayhan Batmanghelich, Gerald T. Quon, Alex Kulesza, Manolis Kellis, Polina Golland, Luke Bornn

CoRR, 2014

Multi-objective Optimization for Multi-level Networks.

Brandon Oselio, Alex Kulesza, Alfred O. Hero III

Proceedings of the Social Computing, Behavioral-Cultural Modeling and Prediction, 2014

Expectation-Maximization for Learning Determinantal Point Processes.

Jennifer Gillenwater, Alex Kulesza, Emily B. Fox, Benjamin Taskar

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

A Repository of State of the Art and Competitive Baseline Summaries for Generic News Summarization.

Kai Hong, John M. Conroy, Benoît Favre, Alex Kulesza, Hui Lin, Ani Nenkova

Proceedings of the Ninth International Conference on Language Resources and Evaluation, 2014

Low-Rank Spectral Learning.

Alex Kulesza, N. Raj Rao, Satinder Singh

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Adaptive regularization of weight vectors.

Koby Crammer, Alex Kulesza, Mark Dredze

Mach. Learn., 2013

Multi-layer graph analytics for dynamic social networks.

Brandon Oselio, Alex Kulesza, Alfred O. Hero III

CoRR, 2013

Multi-layer graph analytics for social networks.

Brandon Oselio, Alex Kulesza, Alfred O. Hero III

Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

Nystrom Approximation for Large-Scale Determinantal Processes.

Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox, Ben Taskar

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Determinantal Point Processes for Machine Learning.

Alex Kulesza, Ben Taskar

Found. Trends Mach. Learn., 2012

Markov Determinantal Point Processes.

Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Near-Optimal MAP Inference for Determinantal Point Processes.

Jennifer Gillenwater, Alex Kulesza, Ben Taskar

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

New ℌ^∞ bounds for the recursive least squares algorithm exploiting input structure.

Koby Crammer, Alex Kulesza, Mark Dredze

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Discovering Diverse and Salient Threads in Document Collections.

Jennifer Gillenwater, Alex Kulesza, Ben Taskar

Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012

2011

Learning Determinantal Point Processes.

Alex Kulesza, Ben Taskar

Proceedings of the UAI 2011, 2011

k-DPPs: Fixed-Size Determinantal Point Processes.

Alex Kulesza, Ben Taskar

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

Multi-domain learning by confidence-weighted parameter combination.

Mark Dredze, Alex Kulesza, Koby Crammer

Mach. Learn., 2010

A theory of learning from different domains.

Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman Vaughan

Mach. Learn., 2010

Exploiting Feature Covariance in High-Dimensional Online Learning.

Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer, Lawrence K. Saul, Fernando Pereira

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Structured Determinantal Point Processes.

Alex Kulesza, Ben Taskar

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

Multi-Class Confidence Weighted Algorithms.

Koby Crammer, Mark Dredze, Alex Kulesza

Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 2009

2007

Empirical Price Modeling for Sponsored Search.

Kuzman Ganchev, Alex Kulesza, Jinsong Tan, Ryan Gabbard, Qian Liu, Michael J. Kearns

Proceedings of the Internet and Network Economics, Third International Workshop, 2007

Structured Learning with Approximate Inference.

Alex Kulesza, Fernando Pereira

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Learning Bounds for Domain Adaptation.

John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2004

Confidence Estimation for Machine Translation.

John Blatz, Erin Fitzgerald, George F. Foster, Simona Gandrabur, Cyril Goutte, Alex Kulesza, Alberto Sanchís, Nicola Ueffing

Proceedings of the COLING 2004, 2004