Aarti Singh - RankMe

223 papers A* 30A 23B 7Misc 5Journal 126Unranked 32

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI+HW 2035: Shaping the Next Decade. CoRR Deming Chen, Jason Cong, Azalia Mirhoseini, Christos Kozyrakis, Subhasish Mitra, Jinjun Xiong, Cliff Young, Anima Anandkumar, Michael L. Littman, Aron Kirschen, Sophia Shao, Serge Leef, Naresh R. Shanbhag, Dejan S. Milojicic, Michael Schulte, Gert Cauwenberghs, Jerry M. Chow, Tri Dao, Kailash Gopalakrishnan, Richard Ho, Hoshik Kim, Kunle Olukotun, David Z. Pan, Mark Ren, Dan Roth, Aarti Singh, Yizhou Sun, Yusu Wang, Yann LeCun, Ruchir Puri
2026	J	`jnl`	Cooperative Multi-agent RL with Communication Constraints. CoRR Nuoya Xiong, Aarti Singh
2026	J	`jnl`	Developing and evaluating a chatbot to support maternal health care. CoRR Smriti Jha, Vidhi Jain, Jianyu Xu, Grace Liu, Sowmya Ramesh, Jitender Nagpal, Gretchen Chapman, Benjamin Bellows, Siddhartha Goyal, Aarti Singh, Bryan Wilder
2026	J	`jnl`	Expanding the Capabilities of Reinforcement Learning via Text Feedback. CoRR Yuda Song, Lili Chen, Fahim Tajwar, Rémi Munos, Deepak Pathak, J. Andrew Bagnell, Aarti Singh, Andrea Zanette
2026	J	`jnl`	Feynman: Knowledge-Infused Diagramming Agent for Scalable Visual Designs. CoRR Zixin Wen, Yifu Cai, Kyle Lee, Sam Estep, Joshua Sunshine, Aarti Singh, Yuejie Chi, Wode Ni
2026	J	`jnl`	On the Learning Dynamics of RLVR at the Edge of Competence. CoRR Yu Huang, Zixin Wen, Yuejie Chi, Yuting Wei, Aarti Singh, Yingbin Liang, Yuxin Chen
2026	J	`jnl`	Online Social Welfare Function-based Resource Allocation. CoRR Kanad Pardeshi, Samsara Foubert, Aarti Singh
2026	A*	`conf`	Scaling Up AI Alignment. AAAI Aarti Singh
2025	J	`jnl`	Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts. Trans. Mach. Learn. Res. Youngseog Chung, Dhruv Malik, Jeff Schneider, Yuanzhi Li, Aarti Singh
2025	J	`jnl`	CaRT: Teaching LLM Agents to Know When They Know Enough. CoRR Grace Liu, Yuxiao Qu, Jeff G. Schneider, Aarti Singh, Aviral Kumar
2025	A*	`conf`	Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects. ICML Santiago Cortes-Gomez, Naveen Janaki Raman, Aarti Singh, Bryan Wilder
2025	A*	`ed.`	Forty-second International Conference on Machine Learning, ICML 2025, Vancouver, BC, Canada, July 13-19, 2025 ICML Aarti Singh, Maryam Fazel, Daniel Hsu, Simon Lacoste-Julien, Felix Berkenkamp, Tegan Maharaj, Kiri Wagstaff, Jerry Zhu
2025	A	`conf`	Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect. AISTATS Ojash Neopane, Aaditya Ramdas, Aarti Singh
2025	J	`jnl`	OEUVRE: OnlinE Unbiased Variance-Reduced loss Estimation. CoRR Kanad Pardeshi, Bryan Wilder, Aarti Singh
2025	J	`jnl`	Online Decision Making with Generative Action Sets. CoRR Jianyu Xu, Vidhi Jain, Bryan Wilder, Aarti Singh
2025	A*	`conf`	Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect. ICML Ojash Neopane, Aaditya Ramdas, Aarti Singh
2025	J	`jnl`	Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect. CoRR Ojash Neopane, Aaditya Ramdas, Aarti Singh
2025	A*	`conf`	Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF. ICML Nuoya Xiong, Aarti Singh
2025	J	`jnl`	Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF. CoRR Nuoya Xiong, Aarti Singh
2025	J	`jnl`	To Distill or Decide? Understanding the Algorithmic Trade-off in Partially Observable Reinforcement Learning. CoRR Yuda Song, Dhruv Rohatgi, Aarti Singh, J. Andrew Bagnell
2025	J	`jnl`	Transformers Provably Learn Chain-of-Thought Reasoning with Length Generalization. CoRR Yu Huang, Zixin Wen, Aarti Singh, Yuejie Chi, Yuxin Chen
2024	—	`conf`	Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts. ENLSP Youngseog Chung, Dhruv Malik, Jeff Schneider, Yuanzhi Li, Aarti Singh
2024	J	`jnl`	Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts. CoRR Youngseog Chung, Dhruv Malik, Jeff G. Schneider, Yuanzhi Li, Aarti Singh
2024	J	`jnl`	Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects. CoRR Santiago Cortes-Gomez, Naveen Raman, Aarti Singh, Bryan Wilder
2024	—	`conf`	Goodhart's Law Applies to NLP's Explanation Benchmarks. EACL (Findings) Jennifer Hsia, Danish Pruthi, Aarti Singh, Zachary C. Lipton
2024	A*	`conf`	Hybrid Reinforcement Learning from Offline Observation Alone. ICML Yuda Song, Drew Bagnell, Aarti Singh
2024	J	`jnl`	Hybrid Reinforcement Learning from Offline Observation Alone. CoRR Yuda Song, J. Andrew Bagnell, Aarti Singh
2024	—	`conf`	Learning Decision-Making Functions Given Cardinal and Ordinal Consensus Data. AAAI Spring Symposia Kanad Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh
2024	A*	`conf`	Learning Social Welfare Functions. NeurIPS Kanad Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh
2024	J	`jnl`	Learning Social Welfare Functions. CoRR Kanad Shrikar Pardeshi, Itai Shapira, Ariel D. Procaccia, Aarti Singh
2024	J	`jnl`	Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect. CoRR Ojash Neopane, Aaditya Ramdas, Aarti Singh
2024	J	`jnl`	Online Learning for Dynamic Impending Collision Prediction using FMCW Radar. ACM Trans. Internet Things Aarti Singh, Neal Patwari
2024	A*	`conf`	Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs. ICLR Aakash Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li
2024	J	`jnl`	Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs. CoRR Aakash Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li
2024	J	`jnl`	Specifying and Solving Robust Empirical Risk Minimization Problems Using CVXPY. J. Optim. Theory Appl. Eric Luxenberg, Dhruv Malik, Yuanzhi Li, Aarti Singh, Stephen P. Boyd
2024	A*	`conf`	The Importance of Online Data: Understanding Preference Fine-tuning via Coverage. NeurIPS Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun
2024	J	`jnl`	Understanding Preference Fine-Tuning Through the Lens of Coverage. CoRR Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun
2023	J	`jnl`	A Novel Software Defined Radio for Practical, Mobile Crowdsourced Spectrum Sensing. IEEE Trans. Mob. Comput. Phillip Smith, Anh Luong, Shamik Sarkar, Harsimran Singh, Aarti Singh, Neal Patwari, Sneha Kumar Kasera, Kurt Derr
2023	A	`conf`	Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. AISTATS Yusha Liu, Aarti Singh
2023	J	`jnl`	Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. CoRR Yusha Liu, Aarti Singh
2023	J	`jnl`	Deep learning powered real-time identification of insects using citizen science data. CoRR 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, Baskar Ganapathysubramanian
2023	J	`jnl`	Goodhart's Law Applies to NLP's Explanation Benchmarks. CoRR Jennifer Hsia, Danish Pruthi, Aarti Singh, Zachary C. Lipton
2023	J	`jnl`	Predicting the Initial Conditions of the Universe using Deep Learning. CoRR Vaibhav Jindal, Drew Jamieson, Albert Liang, Aarti Singh, Shirley Ho
2023	J	`jnl`	Specifying and Solving Robust Empirical Risk Minimization Problems Using CVXPY. CoRR Eric Luxenberg, Dhruv Malik, Yuanzhi Li, Aarti Singh, Stephen P. Boyd
2023	A*	`conf`	The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms. ICML Anirudh Vemula, Yuda Song, Aarti Singh, Drew Bagnell, Sanjiban Choudhury
2023	J	`jnl`	The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms. CoRR Anirudh Vemula, Yuda Song, Aarti Singh, J. Andrew Bagnell, Sanjiban Choudhury
2023	A*	`conf`	Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality. ICML Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh
2023	J	`jnl`	Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality. CoRR Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh
2022	A*	`conf`	Complete Policy Regret Bounds for Tallying Bandits. COLT Dhruv Malik, Yuanzhi Li, Aarti Singh
2022	J	`jnl`	Complete Policy Regret Bounds for Tallying Bandits. CoRR Dhruv Malik, Yuanzhi Li, Aarti Singh
2022	J	`jnl`	Integrating Rankings into Quantized Scores in Peer Review. CoRR Yusha Liu, Yichong Xu, Nihar B. Shah, Aarti Singh
2022	J	`jnl`	Integrating Rankings into Quantized Scores in Peer Review. Trans. Mach. Learn. Res. Yusha Liu, Yichong Xu, Nihar B. Shah, Aarti Singh
2022	J	`jnl`	Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions. J. Mach. Learn. Res. Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh
2021	A*	`conf`	A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. AAAI Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III
2021	—	`conf`	Best Arm Identification under Additive Transfer Bandits. ACSCC Ojash Neopane, Aaditya Ramdas, Aarti Singh
2021	J	`jnl`	Best Arm Identification under Additive Transfer Bandits. CoRR Ojash Neopane, Aaditya Ramdas, Aarti Singh
2021	A*	`conf`	Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. AAAI Ivan Stelmakh, Nihar B. Shah, Aarti Singh
2021	A*	`conf`	Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels. NeurIPS Stefani Karp, Ezra Winston, Yuanzhi Li, Aarti Singh
2021	J	`jnl`	Near-optimal discrete optimization for experimental design: a regret minimization approach. Math. Program. Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang
2021	J	`jnl`	PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. J. Mach. Learn. Res. Ivan Stelmakh, Nihar B. Shah, Aarti Singh
2021	J	`jnl`	Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. Proc. ACM Hum. Comput. Interact. Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III
2021	—	`conf`	Range-based Collision Prediction for Dynamic Motion. CCNC Aarti Singh, Neal Patwari
2021	A	`conf`	Smooth Bandit Optimization: Generalization to Holder Space. AISTATS Yusha Liu, Yining Wang, Aarti Singh
2020	J	`jnl`	A Large Scale Randomized Controlled Trial on Herding in Peer-Review Discussions. CoRR Ivan Stelmakh, Charvi Rastogi, Nihar B. Shah, Aarti Singh, Hal Daumé III
2020	J	`jnl`	A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. CoRR Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III
2020	J	`jnl`	Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. CoRR Ivan Stelmakh, Nihar B. Shah, Aarti Singh
2020	A*	`conf`	Preference-based Reinforcement Learning with Finite-Time Guarantees. NeurIPS Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski
2020	J	`jnl`	Preference-based Reinforcement Learning with Finite-Time Guarantees. CoRR Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski
2020	J	`jnl`	Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. CoRR Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III
2020	J	`jnl`	Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. J. Mach. Learn. Res. Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski
2020	J	`jnl`	Smooth Bandit Optimization: Generalization to Hölder Space. CoRR Yusha Liu, Yining Wang, Aarti Singh
2020	A	`conf`	Thresholding Bandit Problem with Both Duels and Pulls. AISTATS Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski
2020	B	`conf`	Two-Sample Testing on Pairwise Comparison Data and the Role of Modeling Assumptions. ISIT Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh
2020	J	`jnl`	Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions. CoRR Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh
2020	A	`conf`	Zeroth Order Non-convex optimization with Dueling-Choice Bandits. UAI Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski
2019	J	`jnl`	A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. IEEE Trans. Inf. Theory Yining Wang, Yu-Xiang Wang, Aarti Singh
2019	J	`jnl`	A clustered neighbourhood consensus algorithm for a generic agent interaction protocol. Int. J. Adv. Intell. Paradigms Aarti Singh, Dimple Juneja, Rashmi Singh, Saurabh Mukherjee
2019	J	`jnl`	Active Learning for Graph Neural Networks via Node Feature Propagation. CoRR Yuexin Wu, Yichong Xu, Aarti Singh, Yiming Yang, Artur Dubrawski
2019	—	`conf`	Gradient Descent Provably Optimizes Over-parameterized Neural Networks. ICLR (Poster) Simon S. Du, Xiyu Zhai, Barnabás Póczos, Aarti Singh
2019	A*	`conf`	On Testing for Biases in Peer Review. NeurIPS Ivan Stelmakh, Nihar B. Shah, Aarti Singh
2019	J	`jnl`	Optimization of Smooth Functions With Noisy Observations: Local Minimax Rates. IEEE Trans. Inf. Theory Yining Wang, Sivaraman Balakrishnan, Aarti Singh
2019	B	`conf`	PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. ALT Ivan Stelmakh, Nihar B. Shah, Aarti Singh
2019	J	`jnl`	Rate optimal estimation and confidence intervals for high-dimensional regression with missing covariates. J. Multivar. Anal. Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh
2019	J	`jnl`	Thresholding Bandit Problem with Both Duels and Pulls. CoRR Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski
2019	A	`conf`	Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. AISTATS Yifan Wu, Barnabás Póczos, Aarti Singh
2019	J	`jnl`	Zeroth Order Non-convex optimization with Dueling-Choice Bandits. CoRR Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski
2018	J	`jnl`	A clustering-based recommendation engine for restaurants. Int. J. Adv. Intell. Paradigms Aarti Singh, Anu Sharma
2018	J	`jnl`	Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty. CoRR Yining Wang, Erva Ulu, Aarti Singh, Levent Burak Kara
2018	J	`jnl`	Extreme Compressive Sampling for Covariance Estimation. IEEE Trans. Inf. Theory Martin Azizyan, Akshay Krishnamurthy, Aarti Singh
2018	A*	`conf`	Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. ICML Simon S. Du, Jason D. Lee, Yuandong Tian, Aarti Singh, Barnabás Póczos
2018	J	`jnl`	Gradient Descent Provably Optimizes Over-parameterized Neural Networks. CoRR Simon S. Du, Xiyu Zhai, Barnabás Póczos, Aarti Singh
2018	A*	`conf`	How Many Samples are Needed to Estimate a Convolutional Neural Network? NeurIPS Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh
2018	J	`jnl`	How Many Samples are Needed to Learn a Convolutional Neural Network? CoRR Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh
2018	Misc	`conf`	Interactive Linear Regression with Pairwise Comparisons. ACSSC Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski
2018	Misc	`conf`	Linear Quantization by Effective-Resistance Sampling. ICASSP Yining Wang, Aarti Singh
2018	B	`conf`	Local White Matter Architecture Defines Functional Brain Dynamics. SMC Sivaraman Balakrishnan, Yo Joong Choe, Aarti Singh, Jean M. Vettel, Timothy D. Verstynen
2018	J	`jnl`	Multiresolution Representations for Piecewise-Smooth Signals on Graphs. CoRR Siheng Chen, Aarti Singh, Jelena Kovacevic
2018	A*	`conf`	Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. ICML Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski
2018	J	`jnl`	Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. CoRR Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski
2018	A*	`conf`	Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. NeurIPS Yining Wang, Sivaraman Balakrishnan, Aarti Singh
2018	J	`jnl`	Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. CoRR Yining Wang, Sivaraman Balakrishnan, Aarti Singh
2018	J	`jnl`	PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. CoRR Ivan Stelmakh, Nihar B. Shah, Aarti Singh
2018	J	`jnl`	Robust Nonparametric Regression under Huber's ε-contamination Model. CoRR Simon S. Du, Yining Wang, Sivaraman Balakrishnan, Pradeep Ravikumar, Aarti Singh
2018	A	`conf`	Stochastic Zeroth-order Optimization in High Dimensions. AISTATS Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh
2018	J	`jnl`	Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. CoRR Yifan Wu, Barnabás Póczos, Aarti Singh
2017	J	`jnl`	A Thorough Insight into Theoretical and Practical Developments in MultiAgent Systems. Int. J. Ambient Comput. Intell. Dimple Juneja, Aarti Singh, Rashmi Singh, Saurabh Mukherjee
2017	J	`jnl`	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. Aarti Singh, Dimple Juneja, Manisha Malhotra
2017	J	`jnl`	Computationally Efficient Robust Estimation of Sparse Functionals. CoRR Simon S. Du, Sivaraman Balakrishnan, Aarti Singh
2017	A*	`conf`	Computationally Efficient Robust Sparse Estimation in High Dimensions. COLT Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh
2017	J	`jnl`	Detecting Localized Categorical Attributes on Graphs. IEEE Trans. Signal Process. Siheng Chen, Yaoqing Yang, Shi Zong, Aarti Singh, Jelena Kovacevic
2017	—	`conf`	Gradient Descent Can Take Exponential Time to Escape Saddle Points. NIPS Simon S. Du, Chi Jin, Jason D. Lee, Michael I. Jordan, Aarti Singh, Barnabás Póczos
2017	J	`jnl`	Gradient Descent Can Take Exponential Time to Escape Saddle Points. CoRR Simon S. Du, Chi Jin, Jason D. Lee, Michael I. Jordan, Barnabás Póczos, Aarti Singh
2017	J	`jnl`	Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. CoRR Simon S. Du, Jason D. Lee, Yuandong Tian, Barnabás Póczos, Aarti Singh
2017	—	`conf`	Hypothesis Transfer Learning via Transformation Functions. NIPS Simon S. Du, Jayanth Koushik, Aarti Singh, Barnabás Póczos
2017	A*	`conf`	Near-Optimal Design of Experiments via Regret Minimization. ICML Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang
2017	J	`jnl`	Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach. CoRR Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang
2017	—	`conf`	Noise-Tolerant Interactive Learning Using Pairwise Comparisons. NIPS Yichong Xu, Hongyang Zhang, Aarti Singh, Artur Dubrawski, Kyle Miller
2017	J	`jnl`	On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models. J. Mach. Learn. Res. Yining Wang, Adams Wei Yu, Aarti Singh
2017	—	`conf`	On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. NIPS Simon S. Du, Yining Wang, Aarti Singh
2017	J	`jnl`	On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. CoRR Simon S. Du, Yining Wang, Aarti Singh
2017	A	`ed.`	Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA AISTATS Aarti Singh, Xiaojin (Jerry) Zhu
2017	J	`jnl`	Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data. J. Mach. Learn. Res. Yining Wang, Aarti Singh
2017	J	`jnl`	Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates. CoRR Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh
2017	J	`jnl`	Stochastic Zeroth-order Optimization in High Dimensions. CoRR Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh
2017	A*	`conf`	Uncorrelation and Evenness: a New Diversity-Promoting Regularizer. ICML Pengtao Xie, Aarti Singh, Eric P. Xing
2016	J	`jnl`	A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. CoRR Yining Wang, Yu-Xiang Wang, Aarti Singh
2016	B	`conf`	A statistical perspective of sampling scores for linear regression. ISIT Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic
2016	A	`conf`	Active Learning Algorithms for Graphical Model Selection. AISTATS Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park
2016	J	`jnl`	Active Learning Algorithms for Graphical Model Selection. CoRR Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park
2016	J	`jnl`	Automatic builder of class diagram (ABCD): an application of UML generation from functional requirements. Softw. Pract. Exp. Wahiba Ben Abdessalem Karaa, Zeineb Ben Azzouz, Aarti Singh, Nilanjan Dey, Amira S. Ashour, Henda Ben Ghézala
2016	J	`jnl`	Classification Accuracy as a Proxy for Two Sample Testing. CoRR Aaditya Ramdas, Aarti Singh, Larry A. Wasserman
2016	—	`conf`	Data Poisoning Attacks on Factorization-Based Collaborative Filtering. NIPS Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik
2016	J	`jnl`	Data Poisoning Attacks on Factorization-Based Collaborative Filtering. CoRR Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik
2016	J	`jnl`	Detecting Anomalous Activity on Networks With the Graph Fourier Scan Statistic. IEEE Trans. Signal Process. James Sharpnack, Alessandro Rinaldo, Aarti Singh
2016	J	`jnl`	Detecting Structure-correlated Attributes on Graphs. CoRR Siheng Chen, Yaoqing Yang, Shi Zong, Aarti Singh, Jelena Kovacevic
2016	A	`conf`	Graph Connectivity in Noisy Sparse Subspace Clustering. AISTATS Yining Wang, Yu-Xiang Wang, Aarti Singh
2016	J	`jnl`	Minimax Lower Bounds for Linear Independence Testing. CoRR Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman
2016	J	`jnl`	Minimax Subsampling for Estimation and Prediction in Low-Dimensional Linear Regression. CoRR Yining Wang, Aarti Singh
2016	B	`conf`	Minimax lower bounds for linear independence testing. ISIT Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman
2016	A*	`conf`	Noise-Adaptive Margin-Based Active Learning and Lower Bounds under Tsybakov Noise Condition. AAAI Yining Wang, Aarti Singh
2016	—	`conf`	Optimal Cluster Head Election Algorithm for Mobile Wireless Sensor Networks. ICTCS Aarti Singh, Kavita Gupta
2016	J	`jnl`	Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints. PLoS Comput. Biol. Fang-Cheng Yeh, Jean M. Vettel, Aarti Singh, Barnabás Póczos, Scott T. Grafton, Kirk I. Erickson, Wen-Yih Isaac Tseng, Timothy D. Verstynen
2016	Misc	`conf`	Representations of piecewise smooth signals on graphs. ICASSP Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic
2016	J	`jnl`	Signal Recovery on Graphs: Fundamental Limits of Sampling Strategies. IEEE Trans. Signal Inf. Process. over Networks Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic
2016	—	`conf`	Signal detection on graphs: Bernoulli noise model. GlobalSIP Siheng Chen, Yaoqing Yang, Aarti Singh, Jelena Kovacevic
2016	J	`jnl`	Transformation Function Based Methods for Model Shift. CoRR Simon Shaolei Du, Jayanth Koushik, Aarti Singh, Barnabás Póczos
2015	A*	`conf`	A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data. ICML Yining Wang, Yu-Xiang Wang, Aarti Singh
2015	J	`jnl`	Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing. CoRR Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	J	`jnl`	Agent based Resource Allocation Mechanism Focusing Cost Optimization in Cloud Computing. Int. J. Cloud Appl. Comput. Aarti Singh, Manisha Malhotra
2015	J	`jnl`	Algorithmic Connections Between Active Learning and Stochastic Convex Optimization. CoRR Aaditya Ramdas, Aarti Singh
2015	J	`jnl`	An Analysis of Active Learning With Uniform Feature Noise. CoRR Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	—	`conf`	An empirical comparison of sampling techniques for matrix column subset selection. Allerton Yining Wang, Aarti Singh
2015	J	`jnl`	Clustering Consistent Sparse Subspace Clustering. CoRR Yining Wang, Yu-Xiang Wang, Aarti Singh
2015	A	`conf`	Column Subset Selection with Missing Data via Active Sampling. AISTATS Yining Wang, Aarti Singh
2015	—	`conf`	Differentially private subspace clustering. NIPS Yining Wang, Yu-Xiang Wang, Aarti Singh
2015	A	`conf`	Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures. AISTATS Martin Azizyan, Aarti Singh, Larry A. Wasserman
2015	J	`jnl`	Extreme Compressive Sampling for Covariance Estimation. CoRR Martin Azizyan, Akshay Krishnamurthy, Aarti Singh
2015	A*	`conf`	On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions. AAAI Aaditya Ramdas, Sashank Jakkam Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	A	`conf`	On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives. AISTATS Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2015	J	`jnl`	Provably Correct Active Sampling Algorithms for Matrix Column Subset Selection with Missing Data. CoRR Yining Wang, Aarti Singh
2015	J	`jnl`	Risk Bounds For Mode Clustering. CoRR Martin Azizyan, Yen-Chi Chen, Aarti Singh, Larry A. Wasserman
2015	J	`jnl`	Semantics and Agents Oriented Web Personalization: State of the Art. Int. J. Serv. Sci. Manag. Eng. Technol. Aarti Singh, Anu Sharma, Nilanjan Dey
2015	J	`jnl`	Signal Recovery on Graphs: Fundamental Limits of Sampling Strategies. CoRR Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic
2015	J	`jnl`	Signal Recovery on Graphs: Random versus Experimentally Designed Sampling. CoRR Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic
2015	J	`jnl`	Signal Representations on Graphs: Tools and Applications. CoRR Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic
2014	A	`conf`	An Analysis of Active Learning with Uniform Feature Noise. AISTATS Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014	A	`conf`	FuSSO: Functional Shrinkage and Selection Operator. AISTATS Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng
2014	J	`jnl`	Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions. CoRR Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014	J	`jnl`	Noise-adaptive Margin-based Active Learning for Multi-dimensional Data. CoRR Yining Wang, Aarti Singh
2014	J	`jnl`	On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives. CoRR Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman
2014	J	`jnl`	On the Power of Adaptivity in Matrix Completion and Approximation. CoRR Akshay Krishnamurthy, Aarti Singh
2014	J	`jnl`	Subspace Learning from Extremely Compressed Measurements. CoRR Akshay Krishnamurthy, Martin Azizyan, Aarti Singh
2014	Misc	`conf`	Subspace learning from extremely compressed measurements. ACSSC Martin Azizyan, Akshay Krishnamurthy, Aarti Singh
2013	B	`conf`	Algorithmic Connections between Active Learning and Stochastic Convex Optimization. ALT Aaditya Ramdas, Aarti Singh
2013	A	`conf`	Changepoint Detection over Graphs with the Spectral Scan Statistic. AISTATS James Sharpnack, Aarti Singh, Alessandro Rinaldo
2013	—	`conf`	Cluster Trees on Manifolds. NIPS Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Cluster Trees on Manifolds. CoRR Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	A	`conf`	Detecting Activations over Graphs using Spanning Tree Wavelet Bases. AISTATS James Sharpnack, Aarti Singh, Akshay Krishnamurthy
2013	J	`jnl`	Distribution-Free Distribution Regression CoRR Barnabás Póczos, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	A	`conf`	Distribution-Free Distribution Regression. AISTATS Barnabás Póczos, Aarti Singh, Alessandro Rinaldo, Larry A. Wasserman
2013	—	`conf`	Exploring the intersection of active learning and stochastic convex optimization. GlobalSIP Aaditya Ramdas, Aarti Singh
2013	J	`jnl`	FuSSO: Functional Shrinkage and Selection Operator. CoRR Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng
2013	—	`conf`	Low-Rank Matrix and Tensor Completion via Adaptive Sampling. NIPS Akshay Krishnamurthy, Aarti Singh
2013	—	`conf`	Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation. NIPS Martin Azizyan, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation. CoRR Martin Azizyan, Aarti Singh, Larry A. Wasserman
2013	—	`conf`	Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic. NIPS James Sharpnack, Akshay Krishnamurthy, Aarti Singh
2013	—	`conf`	Near-optimal and computationally efficient detectors for weak and sparse graph-structured patterns. GlobalSIP James Sharpnack, Aarti Singh
2013	J	`jnl`	On the Bootstrap for Persistence Diagrams and Landscapes. CoRR Frédéric Chazal, Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	—	`conf`	Optimal rates for stochastic convex optimization under Tsybakov noise condition. ICML (1) Aaditya Ramdas, Aarti Singh
2013	J	`jnl`	Recovering Graph-Structured Activations using Adaptive Compressive Measurements CoRR Akshay Krishnamurthy, James Sharpnack, Aarti Singh
2013	Misc	`conf`	Recovering graph-structured activations using adaptive compressive measurements. ACSSC Akshay Krishnamurthy, James Sharpnack, Aarti Singh
2013	J	`jnl`	Statistical Inference For Persistent Homology CoRR Sivaraman Balakrishnan, Brittany Terese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2013	J	`jnl`	Tight Lower Bounds for Homology Inference. CoRR Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman
2012	J	`jnl`	Changepoint Detection over Graphs with the Spectral Scan Statistic CoRR James Sharpnack, Alessandro Rinaldo, Aarti Singh
2012	J	`jnl`	Density-Sensitive Semisupervised Inference CoRR Martin Azizyan, Aarti Singh, Larry A. Wasserman
2012	J	`jnl`	Detecting Activations over Graphs using Spanning Tree Wavelet Bases CoRR Akshay Krishnamurthy, James Sharpnack, Aarti Singh
2012	J	`jnl`	Efficient Active Algorithms for Hierarchical Clustering CoRR Akshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu, Aarti Singh
2012	A*	`conf`	Efficient Active Algorithms for Hierarchical Clustering. ICML Akshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu, Aarti Singh
2012	A	`conf`	Minimax rates for homology inference. AISTATS Sivaraman Balakrishnan, Alessandro Rinaldo, Don Sheehy, Aarti Singh, Larry A. Wasserman
2012	J	`jnl`	Optimal Stochastic Convex Optimization Through The Lens Of Active Learning CoRR Aaditya Ramdas, Aarti Singh
2012	A*	`conf`	Robust multi-source network tomography using selective probes. INFOCOM Akshay Krishnamurthy, Aarti Singh
2012	A	`conf`	Sparsistency of the Edge Lasso over Graphs. AISTATS James Sharpnack, Aarti Singh, Alessandro Rinaldo
2012	J	`jnl`	Stability of density-based clustering. J. Mach. Learn. Res. Alessandro Rinaldo, Aarti Singh, Rebecca Nugent, Larry A. Wasserman
2012	—	`conf`	Subspace detection of high-dimensional vectors using compressive sampling. SSP Martin Azizyan, Aarti Singh
2011	J	`jnl`	Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities CoRR Brian Eriksson, Gautam Dasarathy, Aarti Singh, Robert D. Nowak
2011	A	`conf`	Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities. AISTATS Brian Eriksson, Gautam Dasarathy, Aarti Singh, Robert D. Nowak
2011	J	`jnl`	Agent Development Toolkits CoRR Aarti Singh, Dimple Juneja, A. K. Sharma
2011	—	`conf`	Design of an Intelligent and Adaptive Mapping Mechanism for Multiagent Interface. HPAGC Aarti Singh, Dimple Juneja, A. K. Sharma
2011	—	`conf`	Minimax Localization of Structural Information in Large Noisy Matrices. NIPS Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh
2011	J	`jnl`	Minimax Rates for Homology Inference CoRR Sivaraman Balakrishnan, Alessandro Rinaldo, Don Sheehy, Aarti Singh, Larry A. Wasserman
2011	—	`conf`	Noise Thresholds for Spectral Clustering. NIPS Sivaraman Balakrishnan, Min Xu, Akshay Krishnamurthy, Aarti Singh
2010	J	`jnl`	Detecting Weak but Hierarchically-Structured Patterns in Networks CoRR Aarti Singh, Robert D. Nowak, A. Robert Calderbank
2010	A	`conf`	Detecting Weak but Hierarchically-Structured Patterns in Networks. AISTATS Aarti Singh, Robert D. Nowak, A. Robert Calderbank
2010	—	`conf`	Identifying graph-structured activation patterns in networks. NIPS James Sharpnack, Aarti Singh
2009	A	`conf`	Multi-Manifold Semi-Supervised Learning. AISTATS Andrew B. Goldberg, Xiaojin Zhu, Aarti Singh, Zhiting Xu, Robert D. Nowak
2008	J	`jnl`	A Hybrid Computational Grid Architecture for Comparative Genomics. IEEE Trans. Inf. Technol. Biomed. Aarti Singh, Chen Chen, Weiguo Liu, Wayne P. Mitchell, Bertil Schmidt
2008	A*	`conf`	Adaptive Hausdorff Estimation of Density Level Sets. COLT Aarti Singh, Robert D. Nowak, Clayton D. Scott
2008	—	`conf`	Controlling the error in FMRI: Hypothesis testing or set estimation? ISBI Zachary T. Harmany, Rebecca Willett, Aarti Singh, Robert D. Nowak
2008	—	`conf`	Delay-Differentiated Gossiping in Delay Tolerant Networks. ICC Parameswaran Ramanathan, Aarti Singh
2008	—	`conf`	Unlabeled data: Now it helps, now it doesn't. NIPS Aarti Singh, Robert D. Nowak, Xiaojin Zhu
2006	—	`conf`	Active learning for adaptive mobile sensing networks. IPSN Aarti Singh, Robert D. Nowak, Parameswaran Ramanathan
2006	—	`conf`	Decentralized compression and predistribution via randomized gossiping. IPSN Michael G. Rabbat, Jarvis D. Haupt, Aarti Singh, Robert D. Nowak
2005	B	`conf`	Spatial reuse through adaptive interference cancellation in multi-antenna wireless networks. GLOBECOM Aarti Singh, Parmesh Ramanathan, Barry D. Van Veen