| 2026 | AAAI | Scaling Up AI Alignment. | Aarti Singh |
| 2025 | AISTATS | Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect. | Ojash Neopane, Aaditya Ramdas, Aarti Singh |
| 2025 | ICML | Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects. | Santiago Cortes-Gomez, Naveen Janaki Raman, Aarti Singh, Bryan Wilder |
| 2025 | ICML | Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect. | Ojash Neopane, Aaditya Ramdas, Aarti Singh |
| 2025 | ICML | Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF. | Nuoya Xiong, Aarti Singh |
| 2024 | EACL | Goodhart's Law Applies to NLP's Explanation Benchmarks. | Jennifer Hsia, Danish Pruthi, Aarti Singh, Zachary C. Lipton |
| 2024 | ICLR | Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs. | Aakash Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li |
| 2024 | ICML | Hybrid Reinforcement Learning from Offline Observation Alone. | Yuda Song, Drew Bagnell, Aarti Singh |
| 2023 | AISTATS | Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. | Yusha Liu, Aarti Singh |
| 2023 | ICML | Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality. | Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh |
| 2023 | ICML | The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms. | Anirudh Vemula, Yuda Song, Aarti Singh, Drew Bagnell, Sanjiban Choudhury |
| 2022 | COLT | Complete Policy Regret Bounds for Tallying Bandits. | Dhruv Malik, Yuanzhi Li, Aarti Singh |
| 2021 | AAAI | Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. | Ivan Stelmakh, Nihar B. Shah, Aarti Singh |
| 2021 | AAAI | A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. | Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daum III |
| 2021 | ACSSC | Best Arm Identification under Additive Transfer Bandits. | Ojash Neopane, Aaditya Ramdas, Aarti Singh |
| 2021 | AISTATS | Smooth Bandit Optimization: Generalization to Holder Space. | Yusha Liu, Yining Wang, Aarti Singh |
| 2020 | AISTATS | Thresholding Bandit Problem with Both Duels and Pulls. | Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski |
| 2020 | ISIT | Two-Sample Testing on Pairwise Comparison Data and the Role of Modeling Assumptions. | Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh |
| 2020 | UAI | Zeroth Order Non-convex optimization with Dueling-Choice Bandits. | Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski |
| 2019 | AISTATS | Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. | Yifan Wu, Barnabs Pczos, Aarti Singh |
| 2019 | ALT | PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. | Ivan Stelmakh, Nihar B. Shah, Aarti Singh |
| 2019 | ICLR | Gradient Descent Provably Optimizes Over-parameterized Neural Networks. | Simon S. Du, Xiyu Zhai, Barnabs Pczos, Aarti Singh |
| 2018 | ACSSC | Interactive Linear Regression with Pairwise Comparisons. | Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski |
| 2018 | AISTATS | Stochastic Zeroth-order Optimization in High Dimensions. | Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh |
| 2018 | ICASSP | Linear Quantization by Effective-Resistance Sampling. | Yining Wang, Aarti Singh |
| 2018 | ICML | Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. | Simon S. Du, Jason D. Lee, Yuandong Tian, Aarti Singh, Barnabs Pczos |
| 2018 | ICML | Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. | Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski |
| 2018 | SMC | Local White Matter Architecture Defines Functional Brain Dynamics. | Sivaraman Balakrishnan, Yo Joong Choe, Aarti Singh, Jean M. Vettel, Timothy D. Verstynen |
| 2017 | COLT | Computationally Efficient Robust Sparse Estimation in High Dimensions. | Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh |
| 2017 | ICML | Near-Optimal Design of Experiments via Regret Minimization. | Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang |
| 2017 | ICML | Uncorrelation and Evenness: a New Diversity-Promoting Regularizer. | Pengtao Xie, Aarti Singh, Eric P. Xing |
| 2016 | AAAI | Noise-Adaptive Margin-Based Active Learning and Lower Bounds under Tsybakov Noise Condition. | Yining Wang, Aarti Singh |
| 2016 | AISTATS | Active Learning Algorithms for Graphical Model Selection. | Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park |
| 2016 | AISTATS | Graph Connectivity in Noisy Sparse Subspace Clustering. | Yining Wang, Yu-Xiang Wang, Aarti Singh |
| 2016 | ICASSP | Representations of piecewise smooth signals on graphs. | Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic |
| 2016 | ISIT | A statistical perspective of sampling scores for linear regression. | Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic |
| 2016 | ISIT | Minimax lower bounds for linear independence testing. | Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman |
| 2015 | AAAI | On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions. | Aaditya Ramdas, Sashank Jakkam Reddi, Barnabs Pczos, Aarti Singh, Larry A. Wasserman |
| 2015 | AISTATS | Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures. | Martin Azizyan, Aarti Singh, Larry A. Wasserman |
| 2015 | AISTATS | On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives. | Sashank J. Reddi, Aaditya Ramdas, Barnabs Pczos, Aarti Singh, Larry A. Wasserman |
| 2015 | AISTATS | Column Subset Selection with Missing Data via Active Sampling. | Yining Wang, Aarti Singh |
| 2015 | ICML | A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data. | Yining Wang, Yu-Xiang Wang, Aarti Singh |
| 2014 | ACSSC | Subspace learning from extremely compressed measurements. | Martin Azizyan, Akshay Krishnamurthy, Aarti Singh |
| 2014 | AISTATS | FuSSO: Functional Shrinkage and Selection Operator. | Junier B. Oliva, Barnabs Pczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng |
| 2014 | AISTATS | An Analysis of Active Learning with Uniform Feature Noise. | Aaditya Ramdas, Barnabs Pczos, Aarti Singh, Larry A. Wasserman |
| 2013 | ACSSC | Recovering graph-structured activations using adaptive compressive measurements. | Akshay Krishnamurthy, James Sharpnack, Aarti Singh |
| 2013 | AISTATS | Distribution-Free Distribution Regression. | Barnabs Pczos, Aarti Singh, Alessandro Rinaldo, Larry A. Wasserman |
| 2013 | AISTATS | Detecting Activations over Graphs using Spanning Tree Wavelet Bases. | James Sharpnack, Aarti Singh, Akshay Krishnamurthy |
| 2013 | AISTATS | Changepoint Detection over Graphs with the Spectral Scan Statistic. | James Sharpnack, Aarti Singh, Alessandro Rinaldo |
| 2013 | ALT | Algorithmic Connections between Active Learning and Stochastic Convex Optimization. | Aaditya Ramdas, Aarti Singh |
| 2013 | ICML | Optimal rates for stochastic convex optimization under Tsybakov noise condition. | Aaditya Ramdas, Aarti Singh |
| 2012 | ICML | Efficient Active Algorithms for Hierarchical Clustering. | Akshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu, Aarti Singh |
| 2012 | INFOCOM | Robust multi-source network tomography using selective probes. | Akshay Krishnamurthy, Aarti Singh |
| 2008 | COLT | Adaptive Hausdorff Estimation of Density Level Sets. | Aarti Singh, Robert D. Nowak, Clayton D. Scott |
| 2005 | GLOBECOM | Spatial reuse through adaptive interference cancellation in multi-antenna wireless networks. | Aarti Singh, Parmesh Ramanathan, Barry D. Van Veen |