Spatial reuse through adaptive interference cancellation in multi-antenna wireless networks. - Aarti Singh; Parmesh Ramanathan; Barry D. Van Veen (GLOBECOM, 2005)

Decentralized compression and predistribution via randomized gossiping. - Michael G. Rabbat; Jarvis D. Haupt; Aarti Singh; Robert D. Nowak (IPSN, 2006)

Active learning for adaptive mobile sensing networks. - Aarti Singh; Robert D. Nowak; Parameswaran Ramanathan (IPSN, 2006)

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

Delay-Differentiated Gossiping in Delay Tolerant Networks. - Parameswaran Ramanathan; Aarti Singh (ICC, 2008)

Controlling the error in FMRI: Hypothesis testing or set estimation? - Zachary T. Harmany; Rebecca Willett; Aarti Singh; Robert D. Nowak (ISBI, 2008)

Unlabeled data: Now it helps, now it doesn't. - Aarti Singh; Robert D. Nowak; Xiaojin Zhu 001 (NIPS, 2008)

A Hybrid Computational Grid Architecture for Comparative Genomics. - Aarti Singh; Chen Chen; Weiguo Liu; Wayne P. Mitchell; Bertil Schmidt (IEEE Trans. Inf. Technol. Biomed., 2008)

Multi-Manifold Semi-Supervised Learning. - Andrew B. Goldberg; Xiaojin Zhu 001; Aarti Singh; Zhiting Xu 001; Robert D. Nowak (AISTATS, 2009)

Identifying graph-structured activation patterns in networks. - James Sharpnack; Aarti Singh (NIPS, 2010)

Detecting Weak but Hierarchically-Structured Patterns in Networks. - Aarti Singh; Robert D. Nowak; A. Robert Calderbank (AISTATS, 2010)

Design of an Intelligent and Adaptive Mapping Mechanism for Multiagent Interface. - Aarti Singh; Dimple Juneja; A. K. Sharma (HPAGC, 2011)

Noise Thresholds for Spectral Clustering. - Sivaraman Balakrishnan; Min Xu 010; Akshay Krishnamurthy; Aarti Singh (NIPS, 2011)

Minimax Localization of Structural Information in Large Noisy Matrices. - Mladen Kolar; Sivaraman Balakrishnan; Alessandro Rinaldo; Aarti Singh (NIPS, 2011)

Agent Development Toolkits - Aarti Singh; Dimple Juneja; A. K. Sharma (CoRR, 2011)

Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities. - Brian Eriksson; Gautam Dasarathy; Aarti Singh; Robert D. Nowak (AISTATS, 2011)

Efficient Active Algorithms for Hierarchical Clustering. - Akshay Krishnamurthy; Sivaraman Balakrishnan; Min Xu 010; Aarti Singh (ICML, 2012)

Robust multi-source network tomography using selective probes. - Akshay Krishnamurthy; Aarti Singh (INFOCOM, 2012)

Subspace detection of high-dimensional vectors using compressive sampling. - Martin Azizyan; Aarti Singh (SSP, 2012)

Density-Sensitive Semisupervised Inference - Martin Azizyan; Aarti Singh; Larry A. Wasserman (CoRR, 2012)

Optimal Stochastic Convex Optimization Through The Lens Of Active Learning - Aaditya Ramdas; Aarti Singh (CoRR, 2012)

Minimax rates for homology inference. - Sivaraman Balakrishnan; Alessandro Rinaldo; Don Sheehy; Aarti Singh; Larry A. Wasserman (AISTATS, 2012)

Stability of density-based clustering. - Alessandro Rinaldo; Aarti Singh; Rebecca Nugent; Larry A. Wasserman (J. Mach. Learn. Res., 2012)

Sparsistency of the Edge Lasso over Graphs. - James Sharpnack; Aarti Singh; Alessandro Rinaldo (AISTATS, 2012)

Recovering graph-structured activations using adaptive compressive measurements. - Akshay Krishnamurthy; James Sharpnack; Aarti Singh (ACSSC, 2013)

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

Detecting Activations over Graphs using Spanning Tree Wavelet Bases. - James Sharpnack; Aarti Singh; Akshay Krishnamurthy (AISTATS, 2013)

Changepoint Detection over Graphs with the Spectral Scan Statistic. - James Sharpnack; Aarti Singh; Alessandro Rinaldo (AISTATS, 2013)

Algorithmic Connections between Active Learning and Stochastic Convex Optimization. - Aaditya Ramdas; Aarti Singh (ALT, 2013)

Exploring the intersection of active learning and stochastic convex optimization. - Aaditya Ramdas; Aarti Singh (GlobalSIP, 2013)

Near-optimal and computationally efficient detectors for weak and sparse graph-structured patterns. - James Sharpnack; Aarti Singh (GlobalSIP, 2013)

Optimal rates for stochastic convex optimization under Tsybakov noise condition. - Aaditya Ramdas; Aarti Singh (ICML (1), 2013)

Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation. - Martin Azizyan; Aarti Singh; Larry A. Wasserman (NIPS, 2013)

Cluster Trees on Manifolds. - Sivaraman Balakrishnan; Srivatsan Narayanan; Alessandro Rinaldo; Aarti Singh; Larry A. Wasserman (NIPS, 2013)

Low-Rank Matrix and Tensor Completion via Adaptive Sampling. - Akshay Krishnamurthy; Aarti Singh (NIPS, 2013)

Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic. - James Sharpnack; Akshay Krishnamurthy; Aarti Singh (NIPS, 2013)

Tight Lower Bounds for Homology Inference. - Sivaraman Balakrishnan; Alessandro Rinaldo; Aarti Singh; Larry A. Wasserman (CoRR, 2013)

On the Bootstrap for Persistence Diagrams and Landscapes. - Frédéric Chazal; Brittany Terese Fasy; Fabrizio Lecci; Alessandro Rinaldo; Aarti Singh; Larry A. Wasserman (CoRR, 2013)

Statistical Inference For Persistent Homology - Sivaraman Balakrishnan; Brittany Terese Fasy; Fabrizio Lecci; Alessandro Rinaldo; Aarti Singh; Larry A. Wasserman (CoRR, 2013)

Subspace learning from extremely compressed measurements. - Martin Azizyan; Akshay Krishnamurthy; Aarti Singh (ACSSC, 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 (AISTATS, 2014)

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

On the Power of Adaptivity in Matrix Completion and Approximation. - Akshay Krishnamurthy; Aarti Singh (CoRR, 2014)

On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives. - Aaditya Ramdas; Sashank J. Reddi; Barnabás Póczos; Aarti Singh; Larry A. Wasserman (CoRR, 2014)

Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions. - Sashank J. Reddi; Aaditya Ramdas; Barnabás Póczos; Aarti Singh; Larry A. Wasserman (CoRR, 2014)

Noise-adaptive Margin-based Active Learning for Multi-dimensional Data. - Yining Wang 001; Aarti Singh (CoRR, 2014)

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 (AAAI, 2015)

Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures. - Martin Azizyan; 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, 2015)

Column Subset Selection with Missing Data via Active Sampling. - Yining Wang 001; Aarti Singh (AISTATS, 2015)

An empirical comparison of sampling techniques for matrix column subset selection. - Yining Wang 001; Aarti Singh (Allerton, 2015)

A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (ICML, 2015)

Differentially private subspace clustering. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (NIPS, 2015)

Risk Bounds For Mode Clustering. - Martin Azizyan; Yen-Chi Chen; Aarti Singh; Larry A. Wasserman (CoRR, 2015)

Signal Recovery on Graphs: Random versus Experimentally Designed Sampling. - Siheng Chen; Rohan Varma; Aarti Singh; Jelena Kovacevic (CoRR, 2015)

Signal Representations on Graphs: Tools and Applications. - Siheng Chen; Rohan Varma; Aarti Singh; Jelena Kovacevic (CoRR, 2015)

Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing. - Aaditya Ramdas; Sashank J. Reddi; Barnabás Póczos; Aarti Singh; Larry A. Wasserman (CoRR, 2015)

Provably Correct Active Sampling Algorithms for Matrix Column Subset Selection with Missing Data. - Yining Wang 001; Aarti Singh (CoRR, 2015)

Clustering Consistent Sparse Subspace Clustering. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (CoRR, 2015)

Agent based Resource Allocation Mechanism Focusing Cost Optimization in Cloud Computing. - Aarti Singh; Manisha Malhotra (Int. J. Cloud Appl. Comput., 2015)

Semantics and Agents Oriented Web Personalization: State of the Art. - Aarti Singh; Anu Sharma; Nilanjan Dey (Int. J. Serv. Sci. Manag. Eng. Technol., 2015)

Noise-Adaptive Margin-Based Active Learning and Lower Bounds under Tsybakov Noise Condition. - Yining Wang 001; Aarti Singh (AAAI, 2016)

Active Learning Algorithms for Graphical Model Selection. - Gautam Dasarathy; Aarti Singh; Maria-Florina Balcan; Jong Hyuk Park 004 (AISTATS, 2016)

Graph Connectivity in Noisy Sparse Subspace Clustering. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (AISTATS, 2016)

Signal detection on graphs: Bernoulli noise model. - Siheng Chen; Yaoqing Yang; Aarti Singh; Jelena Kovacevic (GlobalSIP, 2016)

Representations of piecewise smooth signals on graphs. - Siheng Chen; Rohan Varma; Aarti Singh; Jelena Kovacevic (ICASSP, 2016)

Optimal Cluster Head Election Algorithm for Mobile Wireless Sensor Networks. - Aarti Singh; Kavita Gupta (ICTCS, 2016)

A statistical perspective of sampling scores for linear regression. - Siheng Chen; Rohan Varma; Aarti Singh; Jelena Kovacevic (ISIT, 2016)

Minimax lower bounds for linear independence testing. - Aaditya Ramdas; David Isenberg; Aarti Singh; Larry A. Wasserman (ISIT, 2016)

Data Poisoning Attacks on Factorization-Based Collaborative Filtering. - Bo Li 026; Yining Wang 001; Aarti Singh; Yevgeniy Vorobeychik (NIPS, 2016)

Detecting Structure-correlated Attributes on Graphs. - Siheng Chen; Yaoqing Yang; Shi Zong; Aarti Singh; Jelena Kovacevic (CoRR, 2016)

Transformation Function Based Methods for Model Shift. - Simon Shaolei Du; Jayanth Koushik; Aarti Singh; Barnabás Póczos (CoRR, 2016)

Classification Accuracy as a Proxy for Two Sample Testing. - Aaditya Ramdas; Aarti Singh; Larry A. Wasserman (CoRR, 2016)

Minimax Subsampling for Estimation and Prediction in Low-Dimensional Linear Regression. - Yining Wang 001; Aarti Singh (CoRR, 2016)

Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints. - Fang-Cheng Yeh; Jean M. Vettel; Aarti Singh; Barnabás Póczos; Scott T. Grafton; Kirk I. Erickson; Wen-Yih Isaac Tseng; Timothy D. Verstynen (PLoS Comput. Biol., 2016)

Automatic builder of class diagram (ABCD): an application of UML generation from functional requirements. - Wahiba Ben Abdessalem Karaa; Zeineb Ben Azzouz; Aarti Singh; Nilanjan Dey; Amira S. Ashour; Henda Ben Ghézala (Softw. Pract. Exp., 2016)

Signal Recovery on Graphs: Fundamental Limits of Sampling Strategies. - Siheng Chen; Rohan Varma; Aarti Singh; Jelena Kovacevic (IEEE Trans. Signal Inf. Process. over Networks, 2016)

Detecting Anomalous Activity on Networks With the Graph Fourier Scan Statistic. - James Sharpnack; Alessandro Rinaldo; Aarti Singh (IEEE Trans. Signal Process., 2016)

Computationally Efficient Robust Sparse Estimation in High Dimensions. - Sivaraman Balakrishnan; Simon S. Du; Jerry Li 001; Aarti Singh (COLT, 2017)

Near-Optimal Design of Experiments via Regret Minimization. - Zeyuan Allen-Zhu; Yuanzhi Li; Aarti Singh; Yining Wang 001 (ICML, 2017)

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

Gradient Descent Can Take Exponential Time to Escape Saddle Points. - Simon S. Du; Chi Jin 001; Jason D. Lee; Michael I. Jordan; Aarti Singh; Barnabás Póczos (NIPS, 2017)

Hypothesis Transfer Learning via Transformation Functions. - Simon S. Du; Jayanth Koushik; Aarti Singh; Barnabás Póczos (NIPS, 2017)

On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. - Simon S. Du; Yining Wang 001; Aarti Singh (NIPS, 2017)

Noise-Tolerant Interactive Learning Using Pairwise Comparisons. - Yichong Xu; Hongyang Zhang 001; Aarti Singh; Artur Dubrawski; Kyle Miller 001 (NIPS, 2017)

Computationally Efficient Robust Estimation of Sparse Functionals. - Simon S. Du; Sivaraman Balakrishnan; Aarti Singh (CoRR, 2017)

A Thorough Insight into Theoretical and Practical Developments in MultiAgent Systems. - Dimple Juneja; Aarti Singh; Rashmi Singh; Saurabh Mukherjee (Int. J. Ambient Comput. Intell., 2017)

A novel agent based autonomous and service composition framework for cost optimization of resource provisioning in cloud computing. - Aarti Singh; Dimple Juneja; Manisha Malhotra (J. King Saud Univ. Comput. Inf. Sci., 2017)

Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data. - Yining Wang 001; Aarti Singh (J. Mach. Learn. Res., 2017)

On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models. - Yining Wang 001; Adams Wei Yu; Aarti Singh (J. Mach. Learn. Res., 2017)

Detecting Localized Categorical Attributes on Graphs. - Siheng Chen; Yaoqing Yang; Shi Zong; Aarti Singh; Jelena Kovacevic (IEEE Trans. Signal Process., 2017)

Interactive Linear Regression with Pairwise Comparisons. - Yichong Xu; Sivaraman Balakrishnan; Aarti Singh; Artur Dubrawski (ACSSC, 2018)

Stochastic Zeroth-order Optimization in High Dimensions. - Yining Wang 001; Simon S. Du; Sivaraman Balakrishnan; Aarti Singh (AISTATS, 2018)

Linear Quantization by Effective-Resistance Sampling. - Yining Wang 001; Aarti Singh (ICASSP, 2018)

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; Barnabás Póczos (ICML, 2018)

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

How Many Samples are Needed to Estimate a Convolutional Neural Network? - Simon S. Du; Yining Wang 001; Xiyu Zhai; Sivaraman Balakrishnan; Ruslan Salakhutdinov; Aarti Singh (NeurIPS, 2018)

Local White Matter Architecture Defines Functional Brain Dynamics. - Sivaraman Balakrishnan; Yo Joong Choe; Aarti Singh; Jean M. Vettel; Timothy D. Verstynen (SMC, 2018)

Multiresolution Representations for Piecewise-Smooth Signals on Graphs. - Siheng Chen; Aarti Singh; Jelena Kovacevic (CoRR, 2018)

How Many Samples are Needed to Learn a Convolutional Neural Network? - Simon S. Du; Yining Wang 001; Xiyu Zhai; Sivaraman Balakrishnan; Ruslan Salakhutdinov; Aarti Singh (CoRR, 2018)

Robust Nonparametric Regression under Huber's ε-contamination Model. - Simon S. Du; Yining Wang 001; Sivaraman Balakrishnan; Pradeep Ravikumar; Aarti Singh (CoRR, 2018)

Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty. - Yining Wang 001; Erva Ulu; Aarti Singh; Levent Burak Kara (CoRR, 2018)

A clustering-based recommendation engine for restaurants. - Aarti Singh; Anu Sharma (Int. J. Adv. Intell. Paradigms, 2018)

Extreme Compressive Sampling for Covariance Estimation. - Martin Azizyan; Akshay Krishnamurthy; Aarti Singh (IEEE Trans. Inf. Theory, 2018)

Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. - Yifan Wu; Barnabás Póczos; Aarti Singh (AISTATS, 2019)

Gradient Descent Provably Optimizes Over-parameterized Neural Networks. - Simon S. Du; Xiyu Zhai; Barnabás Póczos; Aarti Singh (ICLR (Poster), 2019)

On Testing for Biases in Peer Review. - Ivan Stelmakh; Nihar B. Shah; Aarti Singh (NeurIPS, 2019)

Active Learning for Graph Neural Networks via Node Feature Propagation. - Yuexin Wu; Yichong Xu; Aarti Singh; Yiming Yang; Artur Dubrawski (CoRR, 2019)

A clustered neighbourhood consensus algorithm for a generic agent interaction protocol. - Aarti Singh; Dimple Juneja; Rashmi Singh; Saurabh Mukherjee (Int. J. Adv. Intell. Paradigms, 2019)

Rate optimal estimation and confidence intervals for high-dimensional regression with missing covariates. - Yining Wang 001; Jialei Wang; Sivaraman Balakrishnan; Aarti Singh (J. Multivar. Anal., 2019)

Optimization of Smooth Functions With Noisy Observations: Local Minimax Rates. - Yining Wang 001; Sivaraman Balakrishnan; Aarti Singh (IEEE Trans. Inf. Theory, 2019)

A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. - Yining Wang 001; Yu-Xiang Wang 003; Aarti Singh (IEEE Trans. Inf. Theory, 2019)

Thresholding Bandit Problem with Both Duels and Pulls. - Yichong Xu; Xi Chen; Aarti Singh; Artur Dubrawski (AISTATS, 2020)

Two-Sample Testing on Pairwise Comparison Data and the Role of Modeling Assumptions. - Charvi Rastogi; Sivaraman Balakrishnan; Nihar B. Shah; Aarti Singh (ISIT, 2020)

Preference-based Reinforcement Learning with Finite-Time Guarantees. - Yichong Xu; Ruosong Wang; Lin F. Yang; Aarti Singh; Artur Dubrawski (NeurIPS, 2020)

Zeroth Order Non-convex optimization with Dueling-Choice Bandits. - Yichong Xu; Aparna Joshi; Aarti Singh; Artur Dubrawski (UAI, 2020)

A Large Scale Randomized Controlled Trial on Herding in Peer-Review Discussions. - Ivan Stelmakh; Charvi Rastogi; Nihar B. Shah; Aarti Singh; Hal Daumé III (CoRR, 2020)

Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. - Yichong Xu; Sivaraman Balakrishnan; Aarti Singh; Artur Dubrawski (J. Mach. Learn. Res., 2020)

Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. - Ivan Stelmakh; Nihar B. Shah; 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)

Best Arm Identification under Additive Transfer Bandits. - Ojash Neopane; Aaditya Ramdas; Aarti Singh (ACSCC, 2021)

Smooth Bandit Optimization: Generalization to Holder Space. - Yusha Liu; Yining Wang 001; Aarti Singh (AISTATS, 2021)

Range-based Collision Prediction for Dynamic Motion. - Aarti Singh; Neal Patwari (CCNC, 2021)

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

PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. - Ivan Stelmakh; Nihar B. Shah; Aarti Singh (J. Mach. Learn. Res., 2021)

Near-optimal discrete optimization for experimental design: a regret minimization approach. - Zeyuan Allen-Zhu; Yuanzhi Li; Aarti Singh; Yining Wang 001 (Math. Program., 2021)

Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. - Ivan Stelmakh; Nihar B. Shah; Aarti Singh; Hal Daumé III (Proc. ACM Hum. Comput. Interact., 2021)

Complete Policy Regret Bounds for Tallying Bandits. - Dhruv Malik; Yuanzhi Li; Aarti Singh (COLT, 2022)

Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions. - Charvi Rastogi; Sivaraman Balakrishnan; Nihar B. Shah; Aarti Singh (J. Mach. Learn. Res., 2022)

Integrating Rankings into Quantized Scores in Peer Review. - Yusha Liu; Yichong Xu; Nihar B. Shah; Aarti Singh (Trans. Mach. Learn. Res., 2022)

Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. - Yusha Liu; Aarti Singh (AISTATS, 2023)

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

The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms. - Anirudh Vemula; Yuda Song 001; Aarti Singh; Drew Bagnell; Sanjiban Choudhury (ICML, 2023)

Predicting the Initial Conditions of the Universe using Deep Learning. - Vaibhav Jindal; Drew Jamieson; Albert Liang; Aarti Singh; Shirley Ho (CoRR, 2023)

Deep learning powered real-time identification of insects using citizen science data. - Shivani Chiranjeevi; Mojdeh Saadati; Zi K. Deng; Jayanth Koushik; Talukder Z. Jubery; Daren S. Mueller; Matthew E. O. Neal; Nirav C. Merchant; Aarti Singh; Asheesh K. Singh; Soumik Sarkar; Arti Singh; et al. (CoRR, 2023)

A Novel Software Defined Radio for Practical, Mobile Crowdsourced Spectrum Sensing. - Phillip Smith; Anh Luong; Shamik Sarkar; Harsimran Singh; Aarti Singh; Neal Patwari; Sneha Kumar Kasera; Kurt Derr (IEEE Trans. Mob. Comput., 2023)

Learning Decision-Making Functions Given Cardinal and Ordinal Consensus Data. - Kanad Pardeshi; Itai Shapira; Ariel D. Procaccia; Aarti Singh (AAAI Spring Symposia, 2024)

Goodhart's Law Applies to NLP's Explanation Benchmarks. - Jennifer Hsia; Danish Pruthi; Aarti Singh; Zachary C. Lipton (EACL (Findings), 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 (ICLR, 2024)

Hybrid Reinforcement Learning from Offline Observation Alone. - Yuda Song 001; Drew Bagnell; Aarti Singh (ICML, 2024)

The Importance of Online Data: Understanding Preference Fine-tuning via Coverage. - Yuda Song 001; Gokul Swamy; Aarti Singh; J. Andrew Bagnell; Wen Sun 002 (NeurIPS, 2024)

Learning Social Welfare Functions. - Kanad Pardeshi; Itai Shapira; Ariel D. Procaccia; Aarti Singh (NeurIPS, 2024)

Understanding Preference Fine-Tuning Through the Lens of Coverage. - Yuda Song 001; Gokul Swamy; Aarti Singh; J. Andrew Bagnell; Wen Sun 002 (CoRR, 2024)

Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects. - Santiago Cortes-Gomez; Naveen Raman 001; Aarti Singh; Bryan Wilder (CoRR, 2024)

Online Learning for Dynamic Impending Collision Prediction using FMCW Radar. - Aarti Singh; Neal Patwari (ACM Trans. Internet Things, 2024)

Specifying and Solving Robust Empirical Risk Minimization Problems Using CVXPY. - Eric Luxenberg; Dhruv Malik; Yuanzhi Li; Aarti Singh; Stephen P. Boyd (J. Optim. Theory Appl., 2024)

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

Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts. - Youngseog Chung; Dhruv Malik; Jeff Schneider 001; Yuanzhi Li; Aarti Singh (Trans. Mach. Learn. Res., 2025)

Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect. - Ojash Neopane; Aaditya Ramdas; Aarti Singh (CoRR, 2025)

Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF. - Nuoya Xiong; Aarti Singh (CoRR, 2025)