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2020 – today
- 2023
[j25]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): 1289-1300 (2023)- [i73]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 abs/2303.00694 (2023) - [i72]Vaibhav Jindal, Drew Jamieson, Albert Liang, Aarti Singh, Shirley Ho:
Predicting the Initial Conditions of the Universe using Deep Learning. CoRR abs/2303.13056 (2023) - [i71]Yusha Liu, Aarti Singh:
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. CoRR abs/2304.13830 (2023) - [i70]Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh:
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality. CoRR abs/2305.02955 (2023) - 2022
- [j24]Yusha Liu, Yichong Xu, Nihar B. Shah, Aarti Singh:
Integrating Rankings into Quantized Scores in Peer Review. Trans. Mach. Learn. Res. 2022 (2022) - [c80]Dhruv Malik, Yuanzhi Li, Aarti Singh:
Complete Policy Regret Bounds for Tallying Bandits. COLT 2022: 5146-5174 - [i69]Yusha Liu, Yichong Xu, Nihar B. Shah, Aarti Singh:
Integrating Rankings into Quantized Scores in Peer Review. CoRR abs/2204.03505 (2022) - [i68]Dhruv Malik, Yuanzhi Li, Aarti Singh:
Complete Policy Regret Bounds for Tallying Bandits. CoRR abs/2204.11174 (2022) - 2021
- [j23]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. J. Mach. Learn. Res. 22: 163:1-163:66 (2021) - [j22]Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang:
Near-optimal discrete optimization for experimental design: a regret minimization approach. Math. Program. 186(1): 439-478 (2021) - [j21]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): 75:1-75:17 (2021) - [c79]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: 4785-4793 - [c78]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. AAAI 2021: 4794-4802 - [c77]Ojash Neopane, Aaditya Ramdas, Aarti Singh:
Best Arm Identification under Additive Transfer Bandits. ACSCC 2021: 464-470 - [c76]Yusha Liu, Yining Wang, Aarti Singh:
Smooth Bandit Optimization: Generalization to Holder Space. AISTATS 2021: 2206-2214 - [c75]Aarti Singh, Neal Patwari:
Range-based Collision Prediction for Dynamic Motion. CCNC 2021: 1-6 - [c74]Stefani Karp, Ezra Winston, Yuanzhi Li, Aarti Singh:
Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels. NeurIPS 2021: 24883-24897 - [i67]Ojash Neopane, Aaditya Ramdas, Aarti Singh:
Best Arm Identification under Additive Transfer Bandits. CoRR abs/2112.04083 (2021) - 2020
- [j20]Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. J. Mach. Learn. Res. 21: 162:1-162:54 (2020) - [c73]Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski:
Thresholding Bandit Problem with Both Duels and Pulls. AISTATS 2020: 2591-2600 - [c72]Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh:
Two-Sample Testing on Pairwise Comparison Data and the Role of Modeling Assumptions. ISIT 2020: 1271-1276 - [c71]Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski:
Preference-based Reinforcement Learning with Finite-Time Guarantees. NeurIPS 2020 - [c70]Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski:
Zeroth Order Non-convex optimization with Dueling-Choice Bandits. UAI 2020: 899-908 - [i66]Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski:
Preference-based Reinforcement Learning with Finite-Time Guarantees. CoRR abs/2006.08910 (2020) - [i65]Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh:
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions. CoRR abs/2006.11909 (2020) - [i64]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment. CoRR abs/2010.04041 (2020) - [i63]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review. CoRR abs/2011.14646 (2020) - [i62]Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daumé III:
A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences. CoRR abs/2011.15050 (2020) - [i61]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 abs/2011.15083 (2020) - [i60]Yusha Liu, Yining Wang, Aarti Singh:
Smooth Bandit Optimization: Generalization to Hölder Space. CoRR abs/2012.06076 (2020)
2010 – 2019
- 2019
- [j19]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): 305-316 (2019) - [j18]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) - [j17]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): 685-706 (2019) - [j16]Yining Wang, Sivaraman Balakrishnan, Aarti Singh:
Optimization of Smooth Functions With Noisy Observations: Local Minimax Rates. IEEE Trans. Inf. Theory 65(11): 7350-7366 (2019) - [c69]Yifan Wu, Barnabás Póczos, Aarti Singh:
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. AISTATS 2019: 1070-1078 - [c68]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. ALT 2019: 827-855 - [c67]Simon S. Du, Xiyu Zhai, Barnabás Póczos, Aarti Singh:
Gradient Descent Provably Optimizes Over-parameterized Neural Networks. ICLR (Poster) 2019 - [c66]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
On Testing for Biases in Peer Review. NeurIPS 2019: 5287-5297 - [i59]Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski:
Thresholding Bandit Problem with Both Duels and Pulls. CoRR abs/1910.06368 (2019) - [i58]Yuexin Wu, Yichong Xu, Aarti Singh, Yiming Yang, Artur Dubrawski:
Active Learning for Graph Neural Networks via Node Feature Propagation. CoRR abs/1910.07567 (2019) - [i57]Yichong Xu, Aparna Joshi, Aarti Singh, Artur Dubrawski:
Zeroth Order Non-convex optimization with Dueling-Choice Bandits. CoRR abs/1911.00980 (2019) - 2018
- [j15]Aarti Singh, Anu Sharma:
A clustering-based recommendation engine for restaurants. Int. J. Adv. Intell. Paradigms 11(3/4): 272-283 (2018) - [j14]Martin Azizyan, Akshay Krishnamurthy, Aarti Singh:
Extreme Compressive Sampling for Covariance Estimation. IEEE Trans. Inf. Theory 64(12): 7613-7635 (2018) - [c65]Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Interactive Linear Regression with Pairwise Comparisons. ACSSC 2018: 636-640 - [c64]Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh:
Stochastic Zeroth-order Optimization in High Dimensions. AISTATS 2018: 1356-1365 - [c63]Yining Wang, Aarti Singh:
Linear Quantization by Effective-Resistance Sampling. ICASSP 2018: 6927-6930 - [c62]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: 1338-1347 - [c61]Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. ICML 2018: 5469-5478 - [c60]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: 371-381 - [c59]Yining Wang, Sivaraman Balakrishnan, Aarti Singh:
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. NeurIPS 2018: 4343-4354 - [c58]Sivaraman Balakrishnan, Yo Joong Choe, Aarti Singh, Jean M. Vettel, Timothy D. Verstynen:
Local White Matter Architecture Defines Functional Brain Dynamics. SMC 2018: 595-602 - [i56]Yifan Wu, Barnabás Póczos, Aarti Singh:
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent. CoRR abs/1802.04420 (2018) - [i55]Siheng Chen, Aarti Singh, Jelena Kovacevic:
Multiresolution Representations for Piecewise-Smooth Signals on Graphs. CoRR abs/1803.02944 (2018) - [i54]Yining Wang, Sivaraman Balakrishnan, Aarti Singh:
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates. CoRR abs/1803.08586 (2018) - [i53]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 abs/1805.07883 (2018) - [i52]Simon S. Du, Yining Wang, Sivaraman Balakrishnan, Pradeep Ravikumar, Aarti Singh:
Robust Nonparametric Regression under Huber's ε-contamination Model. CoRR abs/1805.10406 (2018) - [i51]Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski:
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information. CoRR abs/1806.03286 (2018) - [i50]Ivan Stelmakh, Nihar B. Shah, Aarti Singh:
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review. CoRR abs/1806.06237 (2018) - [i49]Simon S. Du, Xiyu Zhai, Barnabás Póczos, Aarti Singh:
Gradient Descent Provably Optimizes Over-parameterized Neural Networks. CoRR abs/1810.02054 (2018) - [i48]Yining Wang, Erva Ulu, Aarti Singh, Levent Burak Kara:
Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty. CoRR abs/1810.10977 (2018) - 2017
- [j13]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): 23-49 (2017) - [j12]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): 19-28 (2017) - [j11]Yining Wang, Adams Wei Yu, Aarti Singh:
On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models. J. Mach. Learn. Res. 18: 143:1-143:41 (2017) - [j10]Yining Wang, Aarti Singh:
Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data. J. Mach. Learn. Res. 18: 156:1-156:42 (2017) - [j9]Siheng Chen, Yaoqing Yang, Shi Zong, Aarti Singh, Jelena Kovacevic:
Detecting Localized Categorical Attributes on Graphs. IEEE Trans. Signal Process. 65(10): 2725-2740 (2017) - [c57]Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh:
Computationally Efficient Robust Sparse Estimation in High Dimensions. COLT 2017: 169-212 - [c56]Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang:
Near-Optimal Design of Experiments via Regret Minimization. ICML 2017: 126-135 - [c55]Pengtao Xie, Aarti Singh, Eric P. Xing:
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer. ICML 2017: 3811-3820 - [c54]Simon S. Du, Yining Wang, Aarti Singh:
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. NIPS 2017: 445-455 - [c53]Simon S. Du, Jayanth Koushik, Aarti Singh, Barnabás Póczos:
Hypothesis Transfer Learning via Transformation Functions. NIPS 2017: 574-584 - [c52]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: 1067-1077 - [c51]Yichong Xu, Hongyang Zhang, Aarti Singh, Artur Dubrawski, Kyle Miller:
Noise-Tolerant Interactive Learning Using Pairwise Comparisons. NIPS 2017: 2431-2440 - [e1]Aarti Singh, Xiaojin (Jerry) Zhu:
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA. Proceedings of Machine Learning Research 54, PMLR 2017 [contents] - [i47]Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh:
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates. CoRR abs/1702.02686 (2017) - [i46]Simon S. Du, Yining Wang, Aarti Singh:
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. CoRR abs/1702.06861 (2017) - [i45]Simon S. Du, Sivaraman Balakrishnan, Aarti Singh:
Computationally Efficient Robust Estimation of Sparse Functionals. CoRR abs/1702.07709 (2017) - [i44]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 abs/1705.10412 (2017) - [i43]Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh:
Stochastic Zeroth-order Optimization in High Dimensions. CoRR abs/1710.10551 (2017) - [i42]Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang:
Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach. CoRR abs/1711.05174 (2017) - [i41]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 abs/1712.00779 (2017) - 2016
- [j8]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) - [j7]Wahiba Ben Abdessalem Karaa, Zeineb Ben Azzouz, Aarti Singh, Nilanjan Dey, Amira S. Ashour, Henda Ben Ghézala:
Automatic builder of class diagram (ABCD): an application of UML generation from functional requirements. Softw. Pract. Exp. 46(11): 1443-1458 (2016) - [j6]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Signal Recovery on Graphs: Fundamental Limits of Sampling Strategies. IEEE Trans. Signal Inf. Process. over Networks 2(4): 539-554 (2016) - [j5]James Sharpnack, Alessandro Rinaldo, Aarti Singh:
Detecting Anomalous Activity on Networks With the Graph Fourier Scan Statistic. IEEE Trans. Signal Process. 64(2): 364-379 (2016) - [c50]Yining Wang, Aarti Singh:
Noise-Adaptive Margin-Based Active Learning and Lower Bounds under Tsybakov Noise Condition. AAAI 2016: 2180-2186 - [c49]Yining Wang, Yu-Xiang Wang, Aarti Singh:
Graph Connectivity in Noisy Sparse Subspace Clustering. AISTATS 2016: 538-546 - [c48]Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park:
Active Learning Algorithms for Graphical Model Selection. AISTATS 2016: 1356-1364 - [c47]Siheng Chen, Yaoqing Yang, Aarti Singh, Jelena Kovacevic:
Signal detection on graphs: Bernoulli noise model. GlobalSIP 2016: 395-399 - [c46]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Representations of piecewise smooth signals on graphs. ICASSP 2016: 6370-6374 - [c45]Aarti Singh, Kavita Gupta:
Optimal Cluster Head Election Algorithm for Mobile Wireless Sensor Networks. ICTCS 2016: 132:1-132:6 - [c44]Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman:
Minimax lower bounds for linear independence testing. ISIT 2016: 965-969 - [c43]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
A statistical perspective of sampling scores for linear regression. ISIT 2016: 1556-1560 - [c42]Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik:
Data Poisoning Attacks on Factorization-Based Collaborative Filtering. NIPS 2016: 1885-1893 - [i40]Yining Wang, Aarti Singh:
Minimax Subsampling for Estimation and Prediction in Low-Dimensional Linear Regression. CoRR abs/1601.02068 (2016) - [i39]Aaditya Ramdas, David Isenberg, Aarti Singh, Larry A. Wasserman:
Minimax Lower Bounds for Linear Independence Testing. CoRR abs/1601.06259 (2016) - [i38]Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park:
Active Learning Algorithms for Graphical Model Selection. CoRR abs/1602.00354 (2016) - [i37]Aaditya Ramdas, Aarti Singh, Larry A. Wasserman:
Classification Accuracy as a Proxy for Two Sample Testing. CoRR abs/1602.02210 (2016) - [i36]Siheng Chen, Yaoqing Yang, Shi Zong, Aarti Singh, Jelena Kovacevic:
Detecting Structure-correlated Attributes on Graphs. CoRR abs/1604.00657 (2016) - [i35]Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik:
Data Poisoning Attacks on Factorization-Based Collaborative Filtering. CoRR abs/1608.08182 (2016) - [i34]Yining Wang, Yu-Xiang Wang, Aarti Singh:
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data. CoRR abs/1610.07650 (2016) - [i33]Simon Shaolei Du, Jayanth Koushik, Aarti Singh, Barnabás Póczos:
Transformation Function Based Methods for Model Shift. CoRR abs/1612.01020 (2016) - 2015
- [j4]Aarti Singh, Manisha Malhotra:
Agent based Resource Allocation Mechanism Focusing Cost Optimization in Cloud Computing. Int. J. Cloud Appl. Comput. 5(3): 53-61 (2015) - [j3]Aarti Singh, Anu Sharma, Nilanjan Dey:
Semantics and Agents Oriented Web Personalization: State of the Art. Int. J. Serv. Sci. Manag. Eng. Technol. 6(2): 35-49 (2015) - [c41]Aaditya Ramdas, Sashank Jakkam Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions. AAAI 2015: 3571-3577 - [c40]Martin Azizyan, Aarti Singh, Larry A. Wasserman:
Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures. AISTATS 2015 - [c39]Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives. AISTATS 2015 - [c38]Yining Wang, Aarti Singh:
Column Subset Selection with Missing Data via Active Sampling. AISTATS 2015 - [c37]Yining Wang, Aarti Singh:
An empirical comparison of sampling techniques for matrix column subset selection. Allerton 2015: 1069-1074 - [c36]Yining Wang, Yu-Xiang Wang, Aarti Singh:
A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data. ICML 2015: 1422-1431 - [c35]Yining Wang, Yu-Xiang Wang, Aarti Singh:
Differentially private subspace clustering. NIPS 2015: 1000-1008 - [i32]Yining Wang, Yu-Xiang Wang, Aarti Singh:
Clustering Consistent Sparse Subspace Clustering. CoRR abs/1504.01046 (2015) - [i31]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Signal Recovery on Graphs: Random versus Experimentally Designed Sampling. CoRR abs/1504.05427 (2015) - [i30]Martin Azizyan, Yen-Chi Chen, Aarti Singh, Larry A. Wasserman:
Risk Bounds For Mode Clustering. CoRR abs/1505.00482 (2015) - [i29]Aaditya Ramdas, Aarti Singh:
Algorithmic Connections Between Active Learning and Stochastic Convex Optimization. CoRR abs/1505.04214 (2015) - [i28]Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
An Analysis of Active Learning With Uniform Feature Noise. CoRR abs/1505.04215 (2015) - [i27]Yining Wang, Aarti Singh:
Provably Correct Active Sampling Algorithms for Matrix Column Subset Selection with Missing Data. CoRR abs/1505.04343 (2015) - [i26]Martin Azizyan, Akshay Krishnamurthy, Aarti Singh:
Extreme Compressive Sampling for Covariance Estimation. CoRR abs/1506.00898 (2015) - [i25]Aaditya Ramdas, Sashank J. Reddi, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing. CoRR abs/1508.00655 (2015) - [i24]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Signal Recovery on Graphs: Fundamental Limits of Sampling Strategies. CoRR abs/1512.05405 (2015) - [i23]Siheng Chen, Rohan Varma, Aarti Singh, Jelena Kovacevic:
Signal Representations on Graphs: Tools and Applications. CoRR abs/1512.05406 (2015) - 2014
- [c34]Martin Azizyan, Akshay Krishnamurthy, Aarti Singh:
Subspace learning from extremely compressed measurements. ACSSC 2014: 311-315 - [c33]Junier B. Oliva, Barnabás Póczos, Timothy D. Verstynen, Aarti Singh, Jeff G. Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng:
FuSSO: Functional Shrinkage and Selection Operator. AISTATS 2014: 715-723 - [c32]Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
An Analysis of Active Learning with Uniform Feature Noise. AISTATS 2014: 805-813 - [i22]Akshay Krishnamurthy, Martin Azizyan, Aarti Singh:
Subspace Learning from Extremely Compressed Measurements. CoRR abs/1404.0751 (2014) - [i21]Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos, Aarti Singh, Larry A. Wasserman:
Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions. CoRR abs/1406.2083 (2014) - [i20]Yining Wang, Aarti Singh:
Noise-adaptive Margin-based Active Learning for Multi-dimensional Data. CoRR abs/1406.5383 (2014) - [i19]