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ORCIDAnanda Theertha Suresh
Person information
- affiliation: Google Research, New York, NY, USA
- affiliation (former): University of California San Diego, Department of Electrical and Computer Engineering, CA, USA
- affiliation (former): Indian Institute of Technology Madras, Chennai, India
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2020 – today
- 2024
[j7]Prathamesh Mayekar
, Shubham K. Jha, Ananda Theertha Suresh, Himanshu Tyagi:
Wyner-Ziv Estimators for Distributed Mean Estimation With Side Information and Optimization. IEEE Trans. Inf. Theory 70(4): 2779-2806 (2024)- [i71]Ahmad Beirami, Alekh Agarwal, Jonathan Berant, Alexander D'Amour, Jacob Eisenstein, Chirag Nagpal, Ananda Theertha Suresh:
Theoretical guarantees on the best-of-n alignment policy. CoRR abs/2401.01879 (2024) - [i70]Jae Hun Ro, Srinadh Bhojanapalli, Zheng Xu, Yanxiang Zhang, Ananda Theertha Suresh:
Efficient Language Model Architectures for Differentially Private Federated Learning. CoRR abs/2403.08100 (2024) - [i69]Ziteng Sun, Jae Hun Ro, Ahmad Beirami, Ananda Theertha Suresh:
Optimal Block-Level Draft Verification for Accelerating Speculative Decoding. CoRR abs/2403.10444 (2024) - [i68]Joy Qiping Yang, Salman Salamatian, Ziteng Sun, Ananda Theertha Suresh, Ahmad Beirami:
Asymptotics of Language Model Alignment. CoRR abs/2404.01730 (2024) - [i67]Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael Riley, Sanjiv Kumar, Adrian Benton:
Towards Fast Inference: Exploring and Improving Blockwise Parallel Drafts. CoRR abs/2404.09221 (2024) - [i66]Ziteng Sun, Peter Kairouz, Haicheng Sun, Adrià Gascón, Ananda Theertha Suresh:
Private federated discovery of out-of-vocabulary words for Gboard. CoRR abs/2404.11607 (2024) - 2023
- [c65]Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh:
Principled Approaches for Private Adaptation from a Public Source. AISTATS 2023: 8405-8432 - [c64]Travis Dick, Alex Kulesza, Ziteng Sun, Ananda Theertha Suresh:
Subset-Based Instance Optimality in Private Estimation. ICML 2023: 7992-8014 - [c63]Adrià Gascón, Peter Kairouz, Ziteng Sun, Ananda Theertha Suresh:
Federated Heavy Hitter Recovery under Linear Sketching. ICML 2023: 10997-11012 - [c62]Yuhan Liu, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser:
Algorithms for bounding contribution for histogram estimation under user-level privacy. ICML 2023: 21969-21996 - [c61]Clément L. Canonne, Ziteng Sun, Ananda Theertha Suresh:
Concentration Bounds for Discrete Distribution Estimation in KL Divergence. ISIT 2023: 2093-2098 - [c60]Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix X. Yu:
SpecTr: Fast Speculative Decoding via Optimal Transport. NeurIPS 2023 - [i65]Clément L. Canonne, Ziteng Sun, Ananda Theertha Suresh:
Concentration Bounds for Discrete Distribution Estimation in KL Divergence. CoRR abs/2302.06869 (2023) - [i64]Travis Dick, Alex Kulesza, Ziteng Sun, Ananda Theertha Suresh:
Subset-Based Instance Optimality in Private Estimation. CoRR abs/2303.01262 (2023) - [i63]Xuechen Zhang, Mingchen Li, Xiangyu Chang, Jiasi Chen, Amit K. Roy-Chowdhury, Ananda Theertha Suresh, Samet Oymak:
FedYolo: Augmenting Federated Learning with Pretrained Transformers. CoRR abs/2307.04905 (2023) - [i62]Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon:
The importance of feature preprocessing for differentially private linear optimization. CoRR abs/2307.11106 (2023) - [i61]Adrià Gascón, Peter Kairouz, Ziteng Sun, Ananda Theertha Suresh:
Federated Heavy Hitter Recovery under Linear Sketching. CoRR abs/2307.13347 (2023) - [i60]Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix X. Yu:
SpecTr: Fast Speculative Decoding via Optimal Transport. CoRR abs/2310.15141 (2023) - [i59]Lucas Monteiro Paes, Ananda Theertha Suresh, Alex Beutel, Flávio P. Calmon, Ahmad Beirami:
Multi-Group Fairness Evaluation via Conditional Value-at-Risk Testing. CoRR abs/2312.03867 (2023) - [i58]Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang:
Mean estimation in the add-remove model of differential privacy. CoRR abs/2312.06658 (2023) - 2022
- [c59]Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang:
Robust Estimation for Random Graphs. COLT 2022: 130-166 - [c58]Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh:
On the benefits of maximum likelihood estimation for Regression and Forecasting. ICLR 2022 - [c57]Wei-Ning Chen, Christopher A. Choquette-Choo, Peter Kairouz, Ananda Theertha Suresh:
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning. ICML 2022: 3056-3089 - [c56]Ananda Theertha Suresh, Ziteng Sun, Jae Ro, Felix X. Yu:
Correlated Quantization for Distributed Mean Estimation and Optimization. ICML 2022: 20856-20876 - [c55]Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh:
Differentially Private Learning with Margin Guarantees. NeurIPS 2022 - [i57]Wei-Ning Chen, Christopher A. Choquette-Choo, Peter Kairouz, Ananda Theertha Suresh:
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning. CoRR abs/2203.03761 (2022) - [i56]Ananda Theertha Suresh, Ziteng Sun, Jae Hun Ro, Felix X. Yu:
Correlated quantization for distributed mean estimation and optimization. CoRR abs/2203.04925 (2022) - [i55]Jae Hun Ro, Theresa Breiner, Lara McConnaughey, Mingqing Chen, Ananda Theertha Suresh, Shankar Kumar, Rajiv Mathews:
Scaling Language Model Size in Cross-Device Federated Learning. CoRR abs/2204.09715 (2022) - [i54]Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh:
Differentially Private Learning with Margin Guarantees. CoRR abs/2204.10376 (2022) - [i53]Yuhan Liu, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser:
Histogram Estimation under User-level Privacy with Heterogeneous Data. CoRR abs/2206.03008 (2022) - [i52]Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh:
Private Domain Adaptation from a Public Source. CoRR abs/2208.06135 (2022) - 2021
- [j6]Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol:
Approximating Probabilistic Models as Weighted Finite Automata. Comput. Linguistics 47(2): 221-254 (2021) - [j5]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [j4]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh:
Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs. IEEE J. Sel. Areas Inf. Theory 2(1): 464-478 (2021) - [c54]Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu:
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data. AISTATS 2021: 2332-2340 - [c53]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh:
Shuffled Model of Differential Privacy in Federated Learning. AISTATS 2021: 2521-2529 - [c52]Ananda Theertha Suresh:
Robust hypothesis testing and distribution estimation in Hellinger distance. AISTATS 2021: 2962-2970 - [c51]Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi:
Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information. AISTATS 2021: 3502-3510 - [c50]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz:
On the Rényi Differential Privacy of the Shuffle Model. CCS 2021: 2321-2341 - [c49]Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh:
Relative Deviation Margin Bounds. ICML 2021: 2122-2131 - [c48]Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang:
A Discriminative Technique for Multiple-Source Adaptation. ICML 2021: 2132-2143 - [c47]Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh:
Communication-Efficient Agnostic Federated Averaging. Interspeech 2021: 871-875 - [c46]Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh:
Learning with User-Level Privacy. NeurIPS 2021: 12466-12479 - [c45]Corinna Cortes, Mehryar Mohri, Dmitry Storcheus, Ananda Theertha Suresh:
Boosting with Multiple Sources. NeurIPS 2021: 17373-17387 - [c44]Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh:
Remember What You Want to Forget: Algorithms for Machine Unlearning. NeurIPS 2021: 18075-18086 - [c43]Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh:
Breaking the centralized barrier for cross-device federated learning. NeurIPS 2021: 28663-28676 - [i51]Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh:
Learning with User-Level Privacy. CoRR abs/2102.11845 (2021) - [i50]Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh:
Remember What You Want to Forget: Algorithms for Machine Unlearning. CoRR abs/2103.03279 (2021) - [i49]Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh:
Communication-Efficient Agnostic Federated Averaging. CoRR abs/2104.02748 (2021) - [i48]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz:
On the Renyi Differential Privacy of the Shuffle Model. CoRR abs/2105.05180 (2021) - [i47]Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh:
On the benefits of maximum likelihood estimation for Regression and Forecasting. CoRR abs/2106.10370 (2021) - [i46]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - [i45]Jae Hun Ro, Ananda Theertha Suresh, Ke Wu:
FedJAX: Federated learning simulation with JAX. CoRR abs/2108.02117 (2021) - [i44]Wittawat Jitkrittum, Michal Lukasik, Ananda Theertha Suresh, Felix X. Yu, Gang Wang:
HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation. CoRR abs/2110.15440 (2021) - [i43]Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang:
Robust Estimation for Random Graphs. CoRR abs/2111.05320 (2021) - 2020
- [c42]Jayadev Acharya, Ananda Theertha Suresh:
Optimal multiclass overfitting by sequence reconstruction from Hamming queries. ALT 2020: 3-21 - [c41]Jenny Hamer, Mehryar Mohri, Ananda Theertha Suresh:
FedBoost: A Communication-Efficient Algorithm for Federated Learning. ICML 2020: 3973-3983 - [c40]Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh:
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning. ICML 2020: 5132-5143 - [c39]Yuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley:
Learning discrete distributions: user vs item-level privacy. NeurIPS 2020 - [i42]Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh:
Three Approaches for Personalization with Applications to Federated Learning. CoRR abs/2002.10619 (2020) - [i41]Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh:
Relative Deviation Margin Bounds. CoRR abs/2006.14950 (2020) - [i40]Yishay Mansour, Mehryar Mohri, Ananda Theertha Suresh, Ke Wu:
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data. CoRR abs/2007.09762 (2020) - [i39]Yuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley:
Learning discrete distributions: user vs item-level privacy. CoRR abs/2007.13660 (2020) - [i38]Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh:
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning. CoRR abs/2008.03606 (2020) - [i37]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh:
Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs. CoRR abs/2008.07180 (2020) - [i36]Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang:
Multiple-Source Adaptation with Domain Classifiers. CoRR abs/2008.11036 (2020) - [i35]Ananda Theertha Suresh:
Robust hypothesis testing and distribution estimation in Hellinger distance. CoRR abs/2011.01848 (2020) - [i34]Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi:
Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side Information. CoRR abs/2011.12160 (2020)
2010 – 2019
- 2019
- [c38]Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley:
Federated Learning of N-Gram Language Models. CoNLL 2019: 121-130 - [c37]Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol:
Distilling weighted finite automata from arbitrary probabilistic models. FSMNLP 2019: 87-97 - [c36]Ehsan Variani, Ananda Theertha Suresh, Mitchel Weintraub:
West: Word Encoded Sequence Transducers. ICASSP 2019: 7340-7344 - [c35]Mehryar Mohri, Gary Sivek, Ananda Theertha Suresh:
Agnostic Federated Learning. ICML 2019: 4615-4625 - [c34]Nived Rajaraman, Prafulla Chandra, Andrew Thangaraj, Ananda Theertha Suresh:
Convergence of Chao Unseen Species Estimator. ISIT 2019: 46-50 - [c33]Ananda Theertha Suresh:
Differentially Private Anonymized Histograms. NeurIPS 2019: 7969-7979 - [c32]Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar:
Sampled Softmax with Random Fourier Features. NeurIPS 2019: 13834-13844 - [i33]Mehryar Mohri, Gary Sivek, Ananda Theertha Suresh:
Agnostic Federated Learning. CoRR abs/1902.00146 (2019) - [i32]Yi Hao, Alon Orlitsky, Ananda Theertha Suresh, Yihong Wu:
Data Amplification: A Unified and Competitive Approach to Property Estimation. CoRR abs/1904.00070 (2019) - [i31]Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol:
Approximating probabilistic models as weighted finite automata. CoRR abs/1905.08701 (2019) - [i30]Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar:
Sampled Softmax with Random Fourier Features. CoRR abs/1907.10747 (2019) - [i29]Jayadev Acharya, Ananda Theertha Suresh:
Optimal multiclass overfitting by sequence reconstruction from Hamming queries. CoRR abs/1908.03156 (2019) - [i28]Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar:
AdaCliP: Adaptive Clipping for Private SGD. CoRR abs/1908.07643 (2019) - [i27]Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley:
Federated Learning of N-gram Language Models. CoRR abs/1910.03432 (2019) - [i26]Ananda Theertha Suresh:
Differentially private anonymized histograms. CoRR abs/1910.03553 (2019) - [i25]Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh:
SCAFFOLD: Stochastic Controlled Averaging for On-Device Federated Learning. CoRR abs/1910.06378 (2019) - [i24]Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, H. Brendan McMahan:
Can You Really Backdoor Federated Learning? CoRR abs/1911.07963 (2019) - [i23]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. CoRR abs/1912.04977 (2019) - 2018
- [j3]Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Maximum Selection and Sorting with Adversarial Comparators. J. Mach. Learn. Res. 19: 59:1-59:31 (2018) - [c31]Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Brendan McMahan:
cpSGD: Communication-efficient and differentially-private distributed SGD. NeurIPS 2018: 7575-7586 - [c30]Yi Hao, Alon Orlitsky, Ananda Theertha Suresh, Yihong Wu:
Data Amplification: A Unified and Competitive Approach to Property Estimation. NeurIPS 2018: 8848-8857 - [i22]Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan:
cpSGD: Communication-efficient and differentially-private distributed SGD. CoRR abs/1805.10559 (2018) - [i21]Ehsan Variani, Ananda Theertha Suresh, Mitchel Weintraub:
WEST: Word Encoded Sequence Transducers. CoRR abs/1811.08417 (2018) - 2017
- [j2]Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi:
Estimating Renyi Entropy of Discrete Distributions. IEEE Trans. Inf. Theory 63(1): 38-56 (2017) - [c29]Shankar Kumar, Michael Nirschl, Daniel Niels Holtmann-Rice, Hank Liao, Ananda Theertha Suresh, Felix X. Yu:
Lattice rescoring strategies for long short term memory language models in speech recognition. ASRU 2017: 165-172 - [c28]Yury Polyanskiy, Ananda Theertha Suresh, Yihong Wu:
Sample complexity of population recovery. COLT 2017: 1589-1618 - [c27]Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh:
A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions. ICML 2017: 11-21 - [c26]Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh:
Maximum Selection and Ranking under Noisy Comparisons. ICML 2017: 1088-1096 - [c25]Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan:
Distributed Mean Estimation with Limited Communication. ICML 2017: 3329-3337 - [c24]Nikhilesh Rajaraman, Andrew Thangaraj, Ananda Theertha Suresh:
Minimax risk for missing mass estimation. ISIT 2017: 3025-3029 - [c23]Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Model-Powered Conditional Independence Test. NIPS 2017: 2951-2961 - [c22]Xiang Wu, Ruiqi Guo, Ananda Theertha Suresh, Sanjiv Kumar, Daniel N. Holtmann-Rice, David Simcha, Felix X. Yu:
Multiscale Quantization for Fast Similarity Search. NIPS 2017: 5745-5755 - [i20]Yury Polyanskiy, Ananda Theertha Suresh, Yihong Wu:
Sample complexity of population recovery. CoRR abs/1702.05574 (2017) - [i19]Nikhilesh Rajaraman, Andrew Thangaraj, Ananda Theertha Suresh:
Minimax Risk for Missing Mass Estimation. CoRR abs/1705.05006 (2017) - [i18]Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh:
Maximum Selection and Ranking under Noisy Comparisons. CoRR abs/1705.05366 (2017) - [i17]Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Model-Powered Conditional Independence Test. CoRR abs/1709.06138 (2017) - [i16]Shankar Kumar, Michael Nirschl, Daniel N. Holtmann-Rice, Hank Liao, Ananda Theertha Suresh, Felix X. Yu:
Lattice Rescoring Strategies for Long Short Term Memory Language Models in Speech Recognition. CoRR abs/1711.05448 (2017) - 2016
- [c21]Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh:
Estimating the number of defectives with group testing. ISIT 2016: 1376-1380 - [c20]Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh:
Learning Markov distributions: Does estimation trump compression? ISIT 2016: 2689-2693 - [c19]Felix X. Yu, Ananda Theertha Suresh, Krzysztof Marcin Choromanski, Daniel N. Holtmann-Rice, Sanjiv Kumar:
Orthogonal Random Features. NIPS 2016: 1975-1983 - [i15]Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Maximum Selection and Sorting with Adversarial Comparators and an Application to Density Estimation. CoRR abs/1606.02786 (2016) - [i14]Jakub Konecný, H. Brendan McMahan, Felix X. Yu, Peter Richtárik, Ananda Theertha Suresh, Dave Bacon:
Federated Learning: Strategies for Improving Communication Efficiency. CoRR abs/1610.05492 (2016) - [i13]Felix X. Yu, Ananda Theertha Suresh, Krzysztof Choromanski, Daniel N. Holtmann-Rice, Sanjiv Kumar:
Orthogonal Random Features. CoRR abs/1610.09072 (2016) - [i12]Ananda Theertha Suresh, Felix X. Yu, H. Brendan McMahan, Sanjiv Kumar:
Distributed Mean Estimation with Limited Communication. CoRR abs/1611.00429 (2016) - [i11]Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh:
A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation. CoRR abs/1611.02960 (2016) - [i10]Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh:
A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation. Electron. Colloquium Comput. Complex. TR16 (2016) - 2015
- [c18]Aditya Bhaskara, Ananda Theertha Suresh, Morteza Zadimoghaddam:
Sparse Solutions to Nonnegative Linear Systems and Applications. AISTATS 2015 - [c17]Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh:
Faster Algorithms for Testing under Conditional Sampling. COLT 2015: 607-636 - [c16]Sudeep Kamath, Alon Orlitsky, Dheeraj Pichapati, Ananda Theertha Suresh:
On Learning Distributions from their Samples. COLT 2015: 1066-1100 - [c15]Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh:
Universal compression of power-law distributions. ISIT 2015: 2001-2005 - [c14]Mehryar Mohri, Michael Riley, Ananda Theertha Suresh:
Automata and graph compression. ISIT 2015: 2989-2993 - [c13]Alon Orlitsky, Ananda Theertha Suresh:
Competitive Distribution Estimation: Why is Good-Turing Good. NIPS 2015: 2143-2151 - [c12]Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi:
The Complexity of Estimating Rényi Entropy. SODA 2015: 1855-1869 - [i9]Aditya Bhaskara, Ananda Theertha Suresh, Morteza Zadimoghaddam:
Sparse Solutions to Nonnegative Linear Systems and Applications. CoRR abs/1501.01689 (2015) - [i8]Mehryar Mohri, Michael Riley, Ananda Theertha Suresh:
Automata and Graph Compression. CoRR abs/1502.07288 (2015) - [i7]Alon Orlitsky, Ananda Theertha Suresh:
Competitive Distribution Estimation. CoRR abs/1503.07940 (2015) - [i6]Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapathi, Ananda Theertha Suresh:
Faster Algorithms for Testing under Conditional Sampling. CoRR abs/1504.04103 (2015) - [i5]Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh:
Universal Compression of Power-Law Distributions. CoRR abs/1504.08070 (2015) - 2014
- [c11]Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Sorting with adversarial comparators and application to density estimation. ISIT 2014: 1682-1686 - [c10]Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Efficient compression of monotone and m-modal distributions. ISIT 2014: 1867-1871 - [c9]Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Poissonization and universal compression of envelope classes. ISIT 2014: 1872-1876 - [c8]Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Sublinear algorithms for outlier detection and generalized closeness testing. ISIT 2014: 3200-3204 - [c7]Ananda Theertha Suresh, Alon Orlitsky, Jayadev Acharya, Ashkan Jafarpour:
Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures. NIPS 2014: 1395-1403 - [i4]Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Near-optimal-sample estimators for spherical Gaussian mixtures. CoRR abs/1402.4746 (2014) - [i3]Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Universal Compression of Envelope Classes: Tight Characterization via Poisson Sampling. CoRR abs/1405.7460 (2014) - [i2]Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi:
The Complexity of Estimating Rényi Entropy. CoRR abs/1408.1000 (2014) - 2013
- [j1]Neelesh B. Mehta, Rajat Talak, Ananda Theertha Suresh:
Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems. IEEE Trans. Commun. 61(7): 2735-2745 (2013) - [c6]Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
A Competitive Test for Uniformity of Monotone Distributions. AISTATS 2013: 57-65 - [c5]Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Optimal Probability Estimation with Applications to Prediction and Classification. COLT 2013: 764-796 - [c4]Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh:
Tight bounds for universal compression of large alphabets. ISIT 2013: 2875-2879 - 2012
- [c3]Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Theertha Suresh:
On the query computation and verification of functions. ISIT 2012: 2711-2715 - [c2]Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Theertha Suresh:
Competitive Classification and Closeness Testing. COLT 2012: 22.1-22.18 - 2010
- [c1]Ananda Theertha Suresh, Arunkumar Subramanian, Andrew Thangaraj, Matthieu R. Bloch, Steven W. McLaughlin:
Strong secrecy for erasure wiretap channels. ITW 2010: 1-5 - [i1]Ananda Theertha Suresh, Arunkumar Subramanian, Andrew Thangaraj, Matthieu R. Bloch, Steven W. McLaughlin:
Strong Secrecy for Erasure Wiretap Channels. CoRR abs/1004.5540 (2010)
Coauthor Index
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