Aarti Singh

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 135

Top Venues

Publications

Yuda Song, J. Andrew Bagnell, Aarti Singh
Hybrid Reinforcement Learning from Offline Observation Alone. CoRR (2024)
Jennifer Hsia, Danish Pruthi, Aarti Singh, Zachary C. Lipton
Goodhart's Law Applies to NLP's Explanation Benchmarks. EACL (Findings) (2024)
Aakash Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs. ICLR (2024)
Kanad Shrikar Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh
Learning Social Welfare Functions. CoRR (2024)
Aarti Singh, Neal Patwari
Online Learning for Dynamic Impending Collision Prediction using FMCW Radar. ACM Trans. Internet Things 5 (1) (2024)
Kanad Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh
Learning Decision-Making Functions Given Cardinal and Ordinal Consensus Data. AAAI Spring Symposia (2024)
Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun
Understanding Preference Fine-Tuning Through the Lens of Coverage. CoRR (2024)
Aakash Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs. CoRR (2024)
Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality. ICML (2023)
Phillip Smith, Anh Luong, Shamik Sarkar, Harsimran Singh, Aarti Singh, Neal Patwari, Sneha Kumar Kasera, Kurt Derr
A Novel Software Defined Radio for Practical, Mobile Crowdsourced Spectrum Sensing. IEEE Trans. Mob. Comput. 22 (3) (2023)
Shivani Chiranjeevi, Mojdeh Saadati, Zi K. Deng, Jayanth Koushik, Talukder Z. Jubery, Daren Mueller, Matthew E. O. Neal, Nirav Merchant, Aarti Singh, Asheesh K. Singh, Soumik Sarkar, Arti Singh, Baskar Ganapathysubramanian
Deep learning powered real-time identification of insects using citizen science data. CoRR (2023)
Anirudh Vemula, Yuda Song, Aarti Singh, J. Andrew Bagnell, Sanjiban Choudhury
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms. CoRR (2023)
Eric Luxenberg, Dhruv Malik, Yuanzhi Li, Aarti Singh, Stephen P. Boyd
Specifying and Solving Robust Empirical Risk Minimization Problems Using CVXPY. CoRR (2023)
Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality. CoRR (2023)
Vaibhav Jindal, Drew Jamieson, Albert Liang, Aarti Singh, Shirley Ho
Predicting the Initial Conditions of the Universe using Deep Learning. CoRR (2023)
Jennifer Hsia, Danish Pruthi, Aarti Singh, Zachary C. Lipton
Goodhart's Law Applies to NLP's Explanation Benchmarks. CoRR (2023)
Yusha Liu, Aarti Singh
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. CoRR (2023)
Anirudh Vemula, Yuda Song, Aarti Singh, Drew Bagnell, Sanjiban Choudhury
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms. ICML (2023)
Yusha Liu, Aarti Singh
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. AISTATS (2023)
Yusha Liu, Yichong Xu, Nihar B. Shah, Aarti Singh
Integrating Rankings into Quantized Scores in Peer Review. Trans. Mach. Learn. Res. 2022 (2022)
Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions. J. Mach. Learn. Res. 23 (2022)
Dhruv Malik, Yuanzhi Li, Aarti Singh
Complete Policy Regret Bounds for Tallying Bandits. CoRR (2022)
Dhruv Malik, Yuanzhi Li, Aarti Singh
Complete Policy Regret Bounds for Tallying Bandits. COLT (2022)
Yusha Liu, Yichong Xu, Nihar B. Shah, Aarti Singh
Integrating Rankings into Quantized Scores in Peer Review. CoRR (2022)
Stefani Karp, Ezra Winston, Yuanzhi Li, Aarti Singh
Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels. NeurIPS (2021)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III
Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. Proc. ACM Hum. Comput. Interact. 5 (CSCW1) (2021)
Ojash Neopane, Aaditya Ramdas, Aarti Singh
Best Arm Identification under Additive Transfer Bandits. ACSCC (2021)
Aarti Singh, Neal Patwari
Range-based Collision Prediction for Dynamic Motion. CCNC (2021)
Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang
Near-optimal discrete optimization for experimental design: a regret minimization approach. Math. Program. 186 (1) (2021)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. J. Mach. Learn. Res. 22 (2021)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh
Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. AAAI (2021)
Yusha Liu, Yining Wang, Aarti Singh
Smooth Bandit Optimization: Generalization to Holder Space. AISTATS (2021)
Ojash Neopane, Aaditya Ramdas, Aarti Singh
Best Arm Identification under Additive Transfer Bandits. CoRR (2021)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III
A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. AAAI (2021)
Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski
Thresholding Bandit Problem with Both Duels and Pulls. AISTATS (2020)
Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski
Preference-based Reinforcement Learning with Finite-Time Guarantees. NeurIPS (2020)
Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski
Preference-based Reinforcement Learning with Finite-Time Guarantees. CoRR (2020)
Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski
Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. J. Mach. Learn. Res. 21 (2020)
Yusha Liu, Yining Wang, Aarti Singh
Smooth Bandit Optimization: Generalization to Hölder Space. CoRR (2020)
Ivan Stelmakh, Charvi Rastogi, Nihar B. Shah, Aarti Singh, Hal Daumé III
A Large Scale Randomized Controlled Trial on Herding in Peer-Review Discussions. CoRR (2020)
Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions. CoRR (2020)
Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski
Zeroth Order Non-convex optimization with Dueling-Choice Bandits. UAI (2020)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III
Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. CoRR (2020)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh
Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. CoRR (2020)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III
A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. CoRR (2020)
Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh
Two-Sample Testing on Pairwise Comparison Data and the Role of Modeling Assumptions. ISIT (2020)
Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski
Thresholding Bandit Problem with Both Duels and Pulls. CoRR (2019)
Yuexin Wu, Yichong Xu, Aarti Singh, Yiming Yang, Artur Dubrawski
Active Learning for Graph Neural Networks via Node Feature Propagation. CoRR (2019)
Yining Wang, Sivaraman Balakrishnan, Aarti Singh
Optimization of Smooth Functions With Noisy Observations: Local Minimax Rates. IEEE Trans. Inf. Theory 65 (11) (2019)
Yifan Wu, Barnabás Póczos, Aarti Singh
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. AISTATS (2019)
Aarti Singh, Dimple Juneja, Rashmi Singh, Saurabh Mukherjee
A clustered neighbourhood consensus algorithm for a generic agent interaction protocol. Int. J. Adv. Intell. Paradigms 12 (3/4) (2019)
Simon S. Du, Xiyu Zhai, Barnabás Póczos, Aarti Singh
Gradient Descent Provably Optimizes Over-parameterized Neural Networks. ICLR (Poster) (2019)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh
On Testing for Biases in Peer Review. NeurIPS (2019)
Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski
Zeroth Order Non-convex optimization with Dueling-Choice Bandits. CoRR (2019)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. ALT (2019)
Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh
Rate optimal estimation and confidence intervals for high-dimensional regression with missing covariates. J. Multivar. Anal. 174 (2019)
Yining Wang, Yu-Xiang Wang, Aarti Singh
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. IEEE Trans. Inf. Theory 65 (2) (2019)
Siheng Chen, Aarti Singh, Jelena Kovacevic
Multiresolution Representations for Piecewise-Smooth Signals on Graphs. CoRR (2018)
Yifan Wu, Barnabás Póczos, Aarti Singh
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. CoRR (2018)
Aarti Singh, Anu Sharma
A clustering-based recommendation engine for restaurants. Int. J. Adv. Intell. Paradigms 11 (3/4) (2018)
Yining Wang, Erva Ulu, Aarti Singh, Levent Burak Kara
Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty. CoRR (2018)
Simon S. Du, Yining Wang, Sivaraman Balakrishnan, Pradeep Ravikumar, Aarti Singh
Robust Nonparametric Regression under Huber's ε-contamination Model. CoRR (2018)
Yining Wang, Aarti Singh
Linear Quantization by Effective-Resistance Sampling. ICASSP (2018)
Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh
How Many Samples are Needed to Estimate a Convolutional Neural Network? NeurIPS (2018)
Simon S. Du, Xiyu Zhai, Barnabás Póczos, Aarti Singh
Gradient Descent Provably Optimizes Over-parameterized Neural Networks. CoRR (2018)
Simon S. Du, Jason D. Lee, Yuandong Tian, Aarti Singh, Barnabás Póczos
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. ICML (2018)
Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. ICML (2018)
Yining Wang, Sivaraman Balakrishnan, Aarti Singh
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. CoRR (2018)
Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. CoRR (2018)
Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh
How Many Samples are Needed to Learn a Convolutional Neural Network? CoRR (2018)
Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh
Stochastic Zeroth-order Optimization in High Dimensions. AISTATS (2018)
Martin Azizyan, Akshay Krishnamurthy, Aarti Singh
Extreme Compressive Sampling for Covariance Estimation. IEEE Trans. Inf. Theory 64 (12) (2018)
Sivaraman Balakrishnan, Yo Joong Choe, Aarti Singh, Jean M. Vettel, Timothy D. Verstynen
Local White Matter Architecture Defines Functional Brain Dynamics. SMC (2018)
Ivan Stelmakh, Nihar B. Shah, Aarti Singh
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. CoRR (2018)
Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski
Interactive Linear Regression with Pairwise Comparisons. ACSSC (2018)
Yining Wang, Sivaraman Balakrishnan, Aarti Singh
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. NeurIPS (2018)
Simon S. Du, Yining Wang, Aarti Singh
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. CoRR (2017)
Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang
Near-Optimal Design of Experiments via Regret Minimization. ICML (2017)
Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh
Stochastic Zeroth-order Optimization in High Dimensions. CoRR (2017)
Yining Wang, Aarti Singh
Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data. J. Mach. Learn. Res. 18 (2017)
Simon S. Du, Sivaraman Balakrishnan, Aarti Singh
Computationally Efficient Robust Estimation of Sparse Functionals. CoRR (2017)
Simon S. Du, Jayanth Koushik, Aarti Singh, Barnabás Póczos
Hypothesis Transfer Learning via Transformation Functions. NIPS (2017)
Siheng Chen, Yaoqing Yang, Shi Zong, Aarti Singh, Jelena Kovacevic
Detecting Localized Categorical Attributes on Graphs. IEEE Trans. Signal Process. 65 (10) (2017)
Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang
Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach. CoRR (2017)
Yichong Xu, Hongyang Zhang, Aarti Singh, Artur Dubrawski, Kyle Miller
Noise-Tolerant Interactive Learning Using Pairwise Comparisons. NIPS (2017)
Dimple Juneja, Aarti Singh, Rashmi Singh, Saurabh Mukherjee
A Thorough Insight into Theoretical and Practical Developments in MultiAgent Systems. Int. J. Ambient Comput. Intell. 8 (1) (2017)
Simon S. Du, Chi Jin, Jason D. Lee, Michael I. Jordan, Barnabás Póczos, Aarti Singh
Gradient Descent Can Take Exponential Time to Escape Saddle Points. CoRR (2017)
Simon S. Du, Yining Wang, Aarti Singh
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. NIPS (2017)
Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates. CoRR (2017)
Yining Wang, Adams Wei Yu, Aarti Singh
On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models. J. Mach. Learn. Res. 18 (2017)
Pengtao Xie, Aarti Singh, Eric P. Xing
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer. ICML (2017)
Simon S. Du, Chi Jin, Jason D. Lee, Michael I. Jordan, Aarti Singh, Barnabás Póczos
Gradient Descent Can Take Exponential Time to Escape Saddle Points. NIPS (2017)
Simon S. Du, Jason D. Lee, Yuandong Tian, Barnabás Póczos, Aarti Singh
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. CoRR (2017)
Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh
Computationally Efficient Robust Sparse Estimation in High Dimensions. COLT (2017)
Aarti Singh, Dimple Juneja, Manisha Malhotra
A novel agent based autonomous and service composition framework for cost optimization of resource provisioning in cloud computing. J. King Saud Univ. Comput. Inf. Sci. 29 (1) (2017)
Yining Wang, Aarti Singh
Noise-Adaptive Margin-Based Active Learning and Lower Bounds under Tsybakov Noise Condition. AAAI (2016)
Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic
A statistical perspective of sampling scores for linear regression. ISIT (2016)
Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park
Active Learning Algorithms for Graphical Model Selection. CoRR (2016)
James Sharpnack, Alessandro Rinaldo, Aarti Singh
Detecting Anomalous Activity on Networks With the Graph Fourier Scan Statistic. IEEE Trans. Signal Process. 64 (2) (2016)
Fang-Cheng Yeh, Jean M. Vettel, Aarti Singh, Barnabás Póczos, Scott T. Grafton, Kirk I. Erickson, Wen-Yih Isaac Tseng, Timothy D. Verstynen
Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints. PLoS Comput. Biol. 12 (11) (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Aarti Singh