| 2026 | COLT | Ripple Mechanisms for Discrete and Private Statistics. | Matthew Joseph, Alex Kulesza, Yuyan Wang, Alexander Yu |
| 2025 | AISTATS | General Staircase Mechanisms for Optimal Differential Privacy. | Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang |
| 2025 | ICML | Approximate Differential Privacy of the ℓ2 Mechanism. | Matthew Joseph, Alex Kulesza, Alexander Yu |
| 2024 | ICML | Mean Estimation in the Add-Remove Model of Differential Privacy. | Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang |
| 2023 | ICML | Subset-Based Instance Optimality in Private Estimation. | Travis Dick, Alex Kulesza, Ziteng Sun, Ananda Theertha Suresh |
| 2021 | ICML | Differentially Private Quantiles. | Jennifer Gillenwater, Matthew Joseph, Alex Kulesza |
| 2019 | ICML | Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy. | Kareem Amin, Alex Kulesza, Andres Muoz Medina, Sergei Vassilvitskii |
| 2019 | ICML | A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes. | Jennifer Gillenwater, Alex Kulesza, Zelda Mariet, Sergei Vassilvitskii |
| 2016 | AAAI | Improving Predictive State Representations via Gradient Descent. | Nan Jiang, Alex Kulesza, Satinder Singh |
| 2016 | IJCAI | The Dependence of Effective Planning Horizon on Model Accuracy. | Nan Jiang, Alex Kulesza, Satinder Singh, Richard L. Lewis |
| 2015 | AAAI | Spectral Learning of Predictive State Representations with Insufficient Statistics. | Alex Kulesza, Nan Jiang, Satinder Singh |
| 2015 | AISTATS | Low-Rank Spectral Learning with Weighted Loss Functions. | Alex Kulesza, Nan Jiang, Satinder Singh |
| 2015 | ICASSP | Information extraction from large multi-layer social networks. | Brandon Oselio, Alex Kulesza, Alfred O. Hero III |
| 2015 | ICML | Abstraction Selection in Model-based Reinforcement Learning. | Nan Jiang, Alex Kulesza, Satinder Singh |
| 2014 | AISTATS | Low-Rank Spectral Learning. | Alex Kulesza, N. Raj Rao, Satinder Singh |
| 2014 | LREC | A Repository of State of the Art and Competitive Baseline Summaries for Generic News Summarization. | Kai Hong, John M. Conroy, Benot Favre, Alex Kulesza, Hui Lin, Ani Nenkova |
| 2014 | WSDM | Social collaborative retrieval. | Ko-Jen Hsiao, Alex Kulesza, Alfred O. Hero III |
| 2013 | AISTATS | Nystrom Approximation for Large-Scale Determinantal Processes. | Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox, Ben Taskar |
| 2012 | EMNLP | Discovering Diverse and Salient Threads in Document Collections. | Jennifer Gillenwater, Alex Kulesza, Ben Taskar |
| 2012 | ICASSP | New ℌ | Koby Crammer, Alex Kulesza, Mark Dredze |
| 2012 | UAI | Markov Determinantal Point Processes. | Raja Hafiz Affandi, Alex Kulesza, Emily B. Fox |
| 2011 | ICML | k-DPPs: Fixed-Size Determinantal Point Processes. | Alex Kulesza, Ben Taskar |
| 2011 | UAI | Learning Determinantal Point Processes. | Alex Kulesza, Ben Taskar |
| 2009 | EMNLP | Multi-Class Confidence Weighted Algorithms. | Koby Crammer, Mark Dredze, Alex Kulesza |
| 2004 | COLING | Confidence Estimation for Machine Translation. | John Blatz, Erin Fitzgerald, George F. Foster, Simona Gandrabur, Cyril Goutte, Alex Kulesza, Alberto Sanchs, Nicola Ueffing |