Singh, Aarti

81 publications

TMLR 2025 Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts Youngseog Chung, Dhruv Malik, Jeff Schneider, Yuanzhi Li, Aarti Singh

ICML 2025 Data-Driven Design of Randomized Control Trials with Guaranteed Treatment Effects Santiago Cortes-Gomez, Naveen Janaki Raman, Aarti Singh, Bryan Wilder

AISTATS 2025 Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect Ojash Neopane, Aaditya Ramdas, Aarti Singh

ICML 2025 Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect Ojash Neopane, Aaditya Ramdas, Aarti Singh

ICML 2025 Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF Nuoya Xiong, Aarti Singh

NeurIPS 2025 To Distill or Decide? Understanding the Algorithmic Trade-Off in Partially Observable RL Yuda Song, Dhruv Rohatgi, Aarti Singh, Drew Bagnell

NeurIPS 2025 Transformers Provably Learn Chain-of-Thought Reasoning with Length Generalization Yu Huang, Zixin Wen, Aarti Singh, Yuejie Chi, Yuxin Chen

ICML 2024 Hybrid Reinforcement Learning from Offline Observation Alone Yuda Song, Drew Bagnell, Aarti Singh

NeurIPS 2024 Learning Social Welfare Functions Kanad Shrikar Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh

ICLR 2024 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

NeurIPS 2024 The Importance of Online Data: Understanding Preference Fine-Tuning via Coverage Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun

ICMLW 2024 The Importance of Online Data: Understanding Preference Fine-Tuning via Coverage Yuda Song, Gokul Swamy, Aarti Singh, Drew Bagnell, Wen Sun

AISTATS 2023 Adaptation to Misspecified Kernel Regularity in Kernelised Bandits Yusha Liu, Aarti Singh

NeurIPSW 2023 Out of Domain Stress Prediction on a Dataset of Simulated 3D Polycrystalline Microstructures Thomas Lu, Aarti Singh

NeurIPSW 2023 Predicting the Initial Conditions of the Universe Using a Deterministic Neural Network Vaibhav Jindal, Albert Liang, Aarti Singh, Shirley Ho, Drew Jamieson

ICML 2023 The Virtues of Laziness in Model-Based RL: A Unified Objective and Algorithms Anirudh Vemula, Yuda Song, Aarti Singh, Drew Bagnell, Sanjiban Choudhury

ICML 2023 Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh

COLT 2022 Complete Policy Regret Bounds for Tallying Bandits Dhruv Malik, Yuanzhi Li, Aarti Singh

TMLR 2022 Integrating Rankings into Quantized Scores in Peer Review Yusha Liu, Yichong Xu, Nihar B Shah, Aarti Singh

JMLR 2022 Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh

AISTATS 2021 Smooth Bandit Optimization: Generalization to Holder Space Yusha Liu, Yining Wang, Aarti Singh

AAAI 2021 A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé Iii

AAAI 2021 Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment Ivan Stelmakh, Nihar B. Shah, Aarti Singh

NeurIPS 2021 Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels Stefani Karp, Ezra Winston, Yuanzhi Li, Aarti Singh

JMLR 2021 PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review Ivan Stelmakh, Nihar Shah, Aarti Singh

NeurIPSW 2020 Evidential Reasoning with Expert-Guided Machine Learning Xueying Ding, Gopaljee Atulya, Aarti Singh, Alex Davis, Shane Fazzio

NeurIPS 2020 Preference-Based Reinforcement Learning with Finite-Time Guarantees Yichong Xu, Ruosong Wang, Lin Yang, Aarti Singh, Artur Dubrawski

JMLR 2020 Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski

AISTATS 2020 Thresholding Bandit Problem with Both Duels and Pulls Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski

UAI 2020 Zeroth Order Non-Convex Optimization with Dueling-Choice Bandits Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski

ICLR 2019 Gradient Descent Provably Optimizes Over-Parameterized Neural Networks Simon S. Du, Xiyu Zhai, Barnabas Poczos, Aarti Singh

NeurIPS 2019 On Testing for Biases in Peer Review Ivan Stelmakh, Nihar Shah, Aarti Singh

ALT 2019 PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review Ivan Stelmakh, Nihar B. Shah, Aarti Singh

AISTATS 2019 Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent Yifan Wu, Barnabas Poczos, Aarti Singh

ICML 2018 Gradient Descent Learns One-Hidden-Layer CNN: Don’t Be Afraid of Spurious Local Minima Simon Du, Jason Lee, Yuandong Tian, Aarti Singh, Barnabas Poczos

NeurIPS 2018 How Many Samples Are Needed to Estimate a Convolutional Neural Network? Simon S Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh

ICML 2018 Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski

NeurIPS 2018 Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates Yining Wang, Sivaraman Balakrishnan, Aarti Singh

AISTATS 2018 Stochastic Zeroth-Order Optimization in High Dimensions Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh

COLT 2017 Computationally Efficient Robust Sparse Estimation in High Dimensions Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh

NeurIPS 2017 Gradient Descent Can Take Exponential Time to Escape Saddle Points Simon S Du, Chi Jin, Jason Lee, Michael I Jordan, Aarti Singh, Barnabas Poczos

NeurIPS 2017 Hypothesis Transfer Learning via Transformation Functions Simon S Du, Jayanth Koushik, Aarti Singh, Barnabas Poczos

ICML 2017 Near-Optimal Design of Experiments via Regret Minimization Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang

NeurIPS 2017 Noise-Tolerant Interactive Learning Using Pairwise Comparisons Yichong Xu, Hongyang Zhang, Kyle Miller, Aarti Singh, Artur Dubrawski

JMLR 2017 On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models Yining Wang, Adams Wei Yu, Aarti Singh

NeurIPS 2017 On the Power of Truncated SVD for General High-Rank Matrix Estimation Problems Simon S Du, Yining Wang, Aarti Singh

AISTATS 2017 Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA Aarti Singh, Xiaojin (Jerry) Zhu

ICML 2017 Uncorrelation and Evenness: A New Diversity-Promoting Regularizer Pengtao Xie, Aarti Singh, Eric P. Xing

AISTATS 2016 Active Learning Algorithms for Graphical Model Selection Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park

NeurIPS 2016 Data Poisoning Attacks on Factorization-Based Collaborative Filtering Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik

AISTATS 2016 Graph Connectivity in Noisy Sparse Subspace Clustering Yining Wang, Yu-Xiang Wang, Aarti Singh

AAAI 2016 Noise-Adaptive Margin-Based Active Learning and Lower Bounds Under Tsybakov Noise Condition Yining Wang, Aarti Singh

ICML 2015 A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-Reduced Data Yining Wang, Yu-Xiang Wang, Aarti Singh

AISTATS 2015 Column Subset Selection with Missing Data via Active Sampling Yining Wang, Aarti Singh

NeurIPS 2015 Differentially Private Subspace Clustering Yining Wang, Yu-Xiang Wang, Aarti Singh

AISTATS 2015 Efficient Sparse Clustering of High-Dimensional Non-Spherical Gaussian Mixtures Martin Azizyan, Aarti Singh, Larry A. Wasserman

AAAI 2015 On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions Aaditya Ramdas, Sashank Jakkam Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman

AISTATS 2015 On the High Dimensional Power of a Linear-Time Two Sample Test Under Mean-Shift Alternatives Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman

AISTATS 2014 An Analysis of Active Learning with Uniform Feature Noise Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman

AISTATS 2014 FuSSO: Functional Shrinkage and Selection Operator Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng

ALT 2013 Algorithmic Connections Between Active Learning and Stochastic Convex Optimization Aaditya Ramdas, Aarti Singh

AISTATS 2013 Changepoint Detection over Graphs with the Spectral Scan Statistic James Sharpnack, Aarti Singh, Alessandro Rinaldo

NeurIPS 2013 Cluster Trees on Manifolds Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry Wasserman

AISTATS 2013 Detecting Activations over Graphs Using Spanning Tree Wavelet Bases James Sharpnack, Aarti Singh, Akshay Krishnamurthy

AISTATS 2013 Distribution-Free Distribution Regression Barnabás Póczos, Aarti Singh, Alessandro Rinaldo, Larry A. Wasserman

NeurIPS 2013 Low-Rank Matrix and Tensor Completion via Adaptive Sampling Akshay Krishnamurthy, Aarti Singh

NeurIPS 2013 Minimax Theory for High-Dimensional Gaussian Mixtures with Sparse Mean Separation Martin Azizyan, Aarti Singh, Larry Wasserman

NeurIPS 2013 Near-Optimal Anomaly Detection in Graphs Using Lovasz Extended Scan Statistic James L Sharpnack, Akshay Krishnamurthy, Aarti Singh

ICML 2013 Optimal Rates for Stochastic Convex Optimization Under Tsybakov Noise Condition Aaditya Ramdas, Aarti Singh

ICML 2012 Efficient Active Algorithms for Hierarchical Clustering Akshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu, Aarti Singh

AISTATS 2012 Minimax Rates for Homology Inference Sivaraman Balakrishnan, Alesandro Rinaldo, Don Sheehy, Aarti Singh, Larry Wasserman

AISTATS 2012 Sparsistency of the Edge Lasso over Graphs James Sharpnack, Aarti Singh, Alessandro Rinaldo

JMLR 2012 Stability of Density-Based Clustering Alessandro Rinaldo, Aarti Singh, Rebecca Nugent, Larry Wasserman

AISTATS 2011 Active Clustering: Robust and Efficient Hierarchical Clustering Using Adaptively Selected Similarities Brian Eriksson, Gautam Dasarathy, Aarti Singh, Rob Nowak

NeurIPS 2011 Minimax Localization of Structural Information in Large Noisy Matrices Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh

NeurIPS 2011 Noise Thresholds for Spectral Clustering Sivaraman Balakrishnan, Min Xu, Akshay Krishnamurthy, Aarti Singh

AISTATS 2010 Detecting Weak but Hierarchically-Structured Patterns in Networks Aarti Singh, Robert Nowak, Robert Calderbank

NeurIPS 2010 Identifying Graph-Structured Activation Patterns in Networks James Sharpnack, Aarti Singh

AISTATS 2009 Multi-Manifold Semi-Supervised Learning Andrew Goldberg, Xiaojin Zhu, Aarti Singh, Zhiting Xu, Robert Nowak

COLT 2008 Adaptive Hausdorff Estimation of Density Level Sets Aarti Singh, Robert D. Nowak, Clayton D. Scott

NeurIPS 2008 Unlabeled Data: Now It Helps, Now It Doesn't Aarti Singh, Robert Nowak, Xiaojin Zhu