Ananda Theertha Suresh

163 papers A* 39A 12B 18C 1Misc 2Journal 85Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Block Verification Accelerates Speculative Decoding. ICLR Ziteng Sun, Uri Mendlovic, Yaniv Leviathan, Asaf Aharoni, Jae Hun Ro, Ahmad Beirami, Ananda Theertha Suresh
2025	J	`jnl`	CafeQ: Calibration-free Quantization via Learned Transformations and Adaptive Rounding. CoRR Ziteng Sun, Adrian Benton, Samuel Kushnir, Asher Trockman, Vikas Singh, Suhas N. Diggavi, Ananda Theertha Suresh
2025	A	`conf`	Concept Forgetting via Label Annealing. UAI Subhodip Panda, Ananda Theertha Suresh, Atri Guha, Prathosh A. P.
2025	B	`conf`	Coupling Without Communication and Drafter-Invariant Speculative Decoding. ISIT Majid Daliri, Christopher Musco, Ananda Theertha Suresh
2025	A	`conf`	Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models. AISTATS Haotian Ye, Himanshu Jain, Chong You, Ananda Theertha Suresh, Haowei Lin, James Zou, Felix X. Yu
2025	J	`jnl`	Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models. CoRR Haotian Ye, Himanshu Jain, Chong You, Ananda Theertha Suresh, Haowei Lin, James Zou, Felix X. Yu
2025	A	`conf`	General Staircase Mechanisms for Optimal Differential Privacy. AISTATS Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang
2025	J	`jnl`	Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe. CoRR Chong You, Rajesh Jayaram, Ananda Theertha Suresh, Robin Nittka, Felix X. Yu, Sanjiv Kumar
2025	A*	`conf`	InfAlign: Inference-aware language model alignment. ICML Ananth Balashankar, Ziteng Sun, Jonathan Berant, Jacob Eisenstein, Michael Collins, Adrian Hutter, Jong Lee, Chirag Nagpal, Flavien Prost, Aradhana Sinha, Ananda Theertha Suresh, Ahmad Beirami
2025	A	`conf`	Rate of Model Collapse in Recursive Training. AISTATS Ananda Theertha Suresh, Andrew Thangaraj, Aditya Nanda Kishore Khandavally
2025	A*	`conf`	Theoretical guarantees on the best-of-n alignment policy. ICML Ahmad Beirami, Alekh Agarwal, Jonathan Berant, Alexander Nicholas D'Amour, Jacob Eisenstein, Chirag Nagpal, Ananda Theertha Suresh
2024	A*	`conf`	Accelerating Blockwise Parallel Language Models with Draft Refinement. NeurIPS Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael D. Riley, Sanjiv Kumar, Adrian Benton
2024	B	`conf`	Asymptotics of Language Model Alignment. ISIT Joy Qiping Yang, Salman Salamatian, Ziteng Sun, Ananda Theertha Suresh, Ahmad Beirami
2024	J	`jnl`	Asymptotics of Language Model Alignment. CoRR Joy Qiping Yang, Salman Salamatian, Ziteng Sun, Ananda Theertha Suresh, Ahmad Beirami
2024	J	`jnl`	Coupling without Communication and Drafter-Invariant Speculative Decoding. CoRR Majid Daliri, Christopher Musco, Ananda Theertha Suresh
2024	J	`jnl`	Efficient Language Model Architectures for Differentially Private Federated Learning. CoRR Jae Hun Ro, Srinadh Bhojanapalli, Zheng Xu, Yanxiang Zhang, Ananda Theertha Suresh
2024	Misc	`conf`	FedAQT: Accurate Quantized Training with Federated Learning. ICASSP Renkun Ni, Yonghui Xiao, Phoenix Meadowlark, Oleg Rybakov, Tom Goldstein, Ananda Theertha Suresh, Ignacio López-Moreno, Mingqing Chen, Rajiv Mathews
2024	J	`jnl`	InfAlign: Inference-aware language model alignment. CoRR Ananth Balashankar, Ziteng Sun, Jonathan Berant, Jacob Eisenstein, Michael Collins, Adrian Hutter, Jong Lee, Chirag Nagpal, Flavien Prost, Aradhana Sinha, Ananda Theertha Suresh, Ahmad Beirami
2024	A*	`conf`	Mean Estimation in the Add-Remove Model of Differential Privacy. ICML Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang
2024	J	`jnl`	Multi-Group Fairness Evaluation via Conditional Value-at-Risk Testing. IEEE J. Sel. Areas Inf. Theory Lucas Monteiro Paes, Ananda Theertha Suresh, Alex Beutel, Flávio P. Calmon, Ahmad Beirami
2024	J	`jnl`	Optimal Block-Level Draft Verification for Accelerating Speculative Decoding. CoRR Ziteng Sun, Jae Hun Ro, Ahmad Beirami, Ananda Theertha Suresh
2024	J	`jnl`	Private federated discovery of out-of-vocabulary words for Gboard. CoRR Ziteng Sun, Peter Kairouz, Haicheng Sun, Adrià Gascón, Ananda Theertha Suresh
2024	J	`jnl`	Rate of Model Collapse in Recursive Training. CoRR Ananda Theertha Suresh, Andrew Thangaraj, Aditya Nanda Kishore Khandavally
2024	A*	`conf`	The importance of feature preprocessing for differentially private linear optimization. ICLR Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
2024	J	`jnl`	Theoretical guarantees on the best-of-n alignment policy. CoRR Ahmad Beirami, Alekh Agarwal, Jonathan Berant, Alexander D'Amour, Jacob Eisenstein, Chirag Nagpal, Ananda Theertha Suresh
2024	J	`jnl`	Towards Fast Inference: Exploring and Improving Blockwise Parallel Drafts. CoRR Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael Riley, Sanjiv Kumar, Adrian Benton
2024	J	`jnl`	Wyner-Ziv Estimators for Distributed Mean Estimation With Side Information and Optimization. IEEE Trans. Inf. Theory Prathamesh Mayekar, Shubham K. Jha, Ananda Theertha Suresh, Himanshu Tyagi
2023	A*	`conf`	Algorithms for bounding contribution for histogram estimation under user-level privacy. ICML Yuhan Liu, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser
2023	B	`conf`	Concentration Bounds for Discrete Distribution Estimation in KL Divergence. ISIT Clément L. Canonne, Ziteng Sun, Ananda Theertha Suresh
2023	J	`jnl`	Concentration Bounds for Discrete Distribution Estimation in KL Divergence. CoRR Clément L. Canonne, Ziteng Sun, Ananda Theertha Suresh
2023	J	`jnl`	FedYolo: Augmenting Federated Learning with Pretrained Transformers. CoRR Xuechen Zhang, Mingchen Li, Xiangyu Chang, Jiasi Chen, Amit K. Roy-Chowdhury, Ananda Theertha Suresh, Samet Oymak
2023	A*	`conf`	Federated Heavy Hitter Recovery under Linear Sketching. ICML Adrià Gascón, Peter Kairouz, Ziteng Sun, Ananda Theertha Suresh
2023	J	`jnl`	Federated Heavy Hitter Recovery under Linear Sketching. CoRR Adrià Gascón, Peter Kairouz, Ziteng Sun, Ananda Theertha Suresh
2023	J	`jnl`	Mean estimation in the add-remove model of differential privacy. CoRR Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang
2023	J	`jnl`	Multi-Group Fairness Evaluation via Conditional Value-at-Risk Testing. CoRR Lucas Monteiro Paes, Ananda Theertha Suresh, Alex Beutel, Flávio P. Calmon, Ahmad Beirami
2023	A	`conf`	Principled Approaches for Private Adaptation from a Public Source. AISTATS Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
2023	A*	`conf`	SpecTr: Fast Speculative Decoding via Optimal Transport. NeurIPS Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix X. Yu
2023	J	`jnl`	SpecTr: Fast Speculative Decoding via Optimal Transport. CoRR Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix X. Yu
2023	A*	`conf`	Subset-Based Instance Optimality in Private Estimation. ICML Travis Dick, Alex Kulesza, Ziteng Sun, Ananda Theertha Suresh
2023	J	`jnl`	Subset-Based Instance Optimality in Private Estimation. CoRR Travis Dick, Alex Kulesza, Ziteng Sun, Ananda Theertha Suresh
2023	J	`jnl`	The importance of feature preprocessing for differentially private linear optimization. CoRR Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
2022	A*	`conf`	Correlated Quantization for Distributed Mean Estimation and Optimization. ICML Ananda Theertha Suresh, Ziteng Sun, Jae Ro, Felix X. Yu
2022	J	`jnl`	Correlated quantization for distributed mean estimation and optimization. CoRR Ananda Theertha Suresh, Ziteng Sun, Jae Hun Ro, Felix X. Yu
2022	A*	`conf`	Differentially Private Learning with Margin Guarantees. NeurIPS Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
2022	J	`jnl`	Differentially Private Learning with Margin Guarantees. CoRR Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
2022	J	`jnl`	Histogram Estimation under User-level Privacy with Heterogeneous Data. CoRR Yuhan Liu, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser
2022	A*	`conf`	On the benefits of maximum likelihood estimation for Regression and Forecasting. ICLR Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh
2022	J	`jnl`	Private Domain Adaptation from a Public Source. CoRR Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
2022	A*	`conf`	Robust Estimation for Random Graphs. COLT Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang
2022	J	`jnl`	Scaling Language Model Size in Cross-Device Federated Learning. CoRR Jae Hun Ro, Theresa Breiner, Lara McConnaughey, Mingqing Chen, Ananda Theertha Suresh, Shankar Kumar, Rajiv Mathews
2022	A*	`conf`	The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning. ICML Wei-Ning Chen, Christopher A. Choquette-Choo, Peter Kairouz, Ananda Theertha Suresh
2022	J	`jnl`	The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning. CoRR Wei-Ning Chen, Christopher A. Choquette-Choo, Peter Kairouz, Ananda Theertha Suresh
2021	A*	`conf`	A Discriminative Technique for Multiple-Source Adaptation. ICML Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang
2021	J	`jnl`	A Field Guide to Federated Optimization. CoRR 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
2021	A	`conf`	A Theory of Multiple-Source Adaptation with Limited Target Labeled Data. AISTATS Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu
2021	J	`jnl`	Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 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
2021	J	`jnl`	Approximating Probabilistic Models as Weighted Finite Automata. Comput. Linguistics Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol
2021	A*	`conf`	Boosting with Multiple Sources. NeurIPS Corinna Cortes, Mehryar Mohri, Dmitry Storcheus, Ananda Theertha Suresh
2021	A*	`conf`	Breaking the centralized barrier for cross-device federated learning. NeurIPS Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh
2021	A	`conf`	Communication-Efficient Agnostic Federated Averaging. Interspeech Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh
2021	J	`jnl`	Communication-Efficient Agnostic Federated Averaging. CoRR Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh
2021	J	`jnl`	FedJAX: Federated learning simulation with JAX. CoRR Jae Hun Ro, Ananda Theertha Suresh, Ke Wu
2021	J	`jnl`	HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation. CoRR Wittawat Jitkrittum, Michal Lukasik, Ananda Theertha Suresh, Felix X. Yu, Gang Wang
2021	A*	`conf`	Learning with User-Level Privacy. NeurIPS Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh
2021	J	`jnl`	Learning with User-Level Privacy. CoRR Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh
2021	J	`jnl`	On the Renyi Differential Privacy of the Shuffle Model. CoRR Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz
2021	A*	`conf`	On the Rényi Differential Privacy of the Shuffle Model. CCS Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz
2021	J	`jnl`	On the benefits of maximum likelihood estimation for Regression and Forecasting. CoRR Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh
2021	A*	`conf`	Relative Deviation Margin Bounds. ICML Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh
2021	A*	`conf`	Remember What You Want to Forget: Algorithms for Machine Unlearning. NeurIPS Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh
2021	J	`jnl`	Remember What You Want to Forget: Algorithms for Machine Unlearning. CoRR Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh
2021	J	`jnl`	Robust Estimation for Random Graphs. CoRR Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang
2021	A	`conf`	Robust hypothesis testing and distribution estimation in Hellinger distance. AISTATS Ananda Theertha Suresh
2021	A	`conf`	Shuffled Model of Differential Privacy in Federated Learning. AISTATS Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
2021	J	`jnl`	Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs. IEEE J. Sel. Areas Inf. Theory Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
2021	A	`conf`	Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information. AISTATS Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi
2020	J	`jnl`	A Theory of Multiple-Source Adaptation with Limited Target Labeled Data. CoRR Yishay Mansour, Mehryar Mohri, Ananda Theertha Suresh, Ke Wu
2020	A*	`conf`	FedBoost: A Communication-Efficient Algorithm for Federated Learning. ICML Jenny Hamer, Mehryar Mohri, Ananda Theertha Suresh
2020	A*	`conf`	Learning discrete distributions: user vs item-level privacy. NeurIPS Yuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley
2020	J	`jnl`	Learning discrete distributions: user vs item-level privacy. CoRR Yuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley
2020	J	`jnl`	Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning. CoRR Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh
2020	J	`jnl`	Multiple-Source Adaptation with Domain Classifiers. CoRR Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang
2020	B	`conf`	Optimal multiclass overfitting by sequence reconstruction from Hamming queries. ALT Jayadev Acharya, Ananda Theertha Suresh
2020	J	`jnl`	Relative Deviation Margin Bounds. CoRR Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh
2020	J	`jnl`	Robust hypothesis testing and distribution estimation in Hellinger distance. CoRR Ananda Theertha Suresh
2020	A*	`conf`	SCAFFOLD: Stochastic Controlled Averaging for Federated Learning. ICML Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh
2020	J	`jnl`	Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs. CoRR Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
2020	J	`jnl`	Three Approaches for Personalization with Applications to Federated Learning. CoRR Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh
2020	J	`jnl`	Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side Information. CoRR Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi
2019	J	`jnl`	AdaCliP: Adaptive Clipping for Private SGD. CoRR Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
2019	J	`jnl`	Advances and Open Problems in Federated Learning. CoRR 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
2019	A*	`conf`	Agnostic Federated Learning. ICML Mehryar Mohri, Gary Sivek, Ananda Theertha Suresh
2019	J	`jnl`	Agnostic Federated Learning. CoRR Mehryar Mohri, Gary Sivek, Ananda Theertha Suresh
2019	J	`jnl`	Approximating probabilistic models as weighted finite automata. CoRR Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol
2019	J	`jnl`	Can You Really Backdoor Federated Learning? CoRR Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, H. Brendan McMahan
2019	B	`conf`	Convergence of Chao Unseen Species Estimator. ISIT Nived Rajaraman, Prafulla Chandra, Andrew Thangaraj, Ananda Theertha Suresh
2019	J	`jnl`	Data Amplification: A Unified and Competitive Approach to Property Estimation. CoRR Yi Hao, Alon Orlitsky, Ananda Theertha Suresh, Yihong Wu
2019	A*	`conf`	Differentially Private Anonymized Histograms. NeurIPS Ananda Theertha Suresh
2019	J	`jnl`	Differentially private anonymized histograms. CoRR Ananda Theertha Suresh
2019	—	`conf`	Distilling weighted finite automata from arbitrary probabilistic models. FSMNLP Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol
2019	B	`conf`	Federated Learning of N-Gram Language Models. CoNLL Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley
2019	J	`jnl`	Federated Learning of N-gram Language Models. CoRR Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley
2019	J	`jnl`	Optimal multiclass overfitting by sequence reconstruction from Hamming queries. CoRR Jayadev Acharya, Ananda Theertha Suresh
2019	J	`jnl`	SCAFFOLD: Stochastic Controlled Averaging for On-Device Federated Learning. CoRR Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh
2019	A*	`conf`	Sampled Softmax with Random Fourier Features. NeurIPS Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar
2019	J	`jnl`	Sampled Softmax with Random Fourier Features. CoRR Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar
2019	Misc	`conf`	West: Word Encoded Sequence Transducers. ICASSP Ehsan Variani, Ananda Theertha Suresh, Mitchel Weintraub
2018	A*	`conf`	Data Amplification: A Unified and Competitive Approach to Property Estimation. NeurIPS Yi Hao, Alon Orlitsky, Ananda Theertha Suresh, Yihong Wu
2018	J	`jnl`	Maximum Selection and Sorting with Adversarial Comparators. J. Mach. Learn. Res. Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2018	J	`jnl`	WEST: Word Encoded Sequence Transducers. CoRR Ehsan Variani, Ananda Theertha Suresh, Mitchel Weintraub
2018	A*	`conf`	cpSGD: Communication-efficient and differentially-private distributed SGD. NeurIPS Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Brendan McMahan
2018	J	`jnl`	cpSGD: Communication-efficient and differentially-private distributed SGD. CoRR Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan
2017	A*	`conf`	A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions. ICML Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh
2017	A*	`conf`	Distributed Mean Estimation with Limited Communication. ICML Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan
2017	J	`jnl`	Estimating Renyi Entropy of Discrete Distributions. IEEE Trans. Inf. Theory Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi
2017	J	`jnl`	Lattice Rescoring Strategies for Long Short Term Memory Language Models in Speech Recognition. CoRR Shankar Kumar, Michael Nirschl, Daniel N. Holtmann-Rice, Hank Liao, Ananda Theertha Suresh, Felix X. Yu
2017	C	`conf`	Lattice rescoring strategies for long short term memory language models in speech recognition. ASRU Shankar Kumar, Michael Nirschl, Daniel Niels Holtmann-Rice, Hank Liao, Ananda Theertha Suresh, Felix X. Yu
2017	A*	`conf`	Maximum Selection and Ranking under Noisy Comparisons. ICML Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
2017	J	`jnl`	Maximum Selection and Ranking under Noisy Comparisons. CoRR Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
2017	J	`jnl`	Minimax Risk for Missing Mass Estimation. CoRR Nikhilesh Rajaraman, Andrew Thangaraj, Ananda Theertha Suresh
2017	B	`conf`	Minimax risk for missing mass estimation. ISIT Nikhilesh Rajaraman, Andrew Thangaraj, Ananda Theertha Suresh
2017	—	`conf`	Model-Powered Conditional Independence Test. NIPS Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai
2017	J	`jnl`	Model-Powered Conditional Independence Test. CoRR Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai
2017	—	`conf`	Multiscale Quantization for Fast Similarity Search. NIPS Xiang Wu, Ruiqi Guo, Ananda Theertha Suresh, Sanjiv Kumar, Daniel N. Holtmann-Rice, David Simcha, Felix X. Yu
2017	A*	`conf`	Sample complexity of population recovery. COLT Yury Polyanskiy, Ananda Theertha Suresh, Yihong Wu
2017	J	`jnl`	Sample complexity of population recovery. CoRR Yury Polyanskiy, Ananda Theertha Suresh, Yihong Wu
2016	J	`jnl`	A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation. CoRR Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh
2016	J	`jnl`	A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation. Electron. Colloquium Comput. Complex. Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh
2016	J	`jnl`	Distributed Mean Estimation with Limited Communication. CoRR Ananda Theertha Suresh, Felix X. Yu, H. Brendan McMahan, Sanjiv Kumar
2016	B	`conf`	Estimating the number of defectives with group testing. ISIT Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
2016	J	`jnl`	Federated Learning: Strategies for Improving Communication Efficiency. CoRR Jakub Konecný, H. Brendan McMahan, Felix X. Yu, Peter Richtárik, Ananda Theertha Suresh, Dave Bacon
2016	B	`conf`	Learning Markov distributions: Does estimation trump compression? ISIT Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
2016	J	`jnl`	Maximum Selection and Sorting with Adversarial Comparators and an Application to Density Estimation. CoRR Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2016	—	`conf`	Orthogonal Random Features. NIPS Felix X. Yu, Ananda Theertha Suresh, Krzysztof Marcin Choromanski, Daniel N. Holtmann-Rice, Sanjiv Kumar
2016	J	`jnl`	Orthogonal Random Features. CoRR Felix X. Yu, Ananda Theertha Suresh, Krzysztof Choromanski, Daniel N. Holtmann-Rice, Sanjiv Kumar
2015	J	`jnl`	Automata and Graph Compression. CoRR Mehryar Mohri, Michael Riley, Ananda Theertha Suresh
2015	B	`conf`	Automata and graph compression. ISIT Mehryar Mohri, Michael Riley, Ananda Theertha Suresh
2015	J	`jnl`	Competitive Distribution Estimation. CoRR Alon Orlitsky, Ananda Theertha Suresh
2015	—	`conf`	Competitive Distribution Estimation: Why is Good-Turing Good. NIPS Alon Orlitsky, Ananda Theertha Suresh
2015	A*	`conf`	Faster Algorithms for Testing under Conditional Sampling. COLT Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
2015	J	`jnl`	Faster Algorithms for Testing under Conditional Sampling. CoRR Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapathi, Ananda Theertha Suresh
2015	A*	`conf`	On Learning Distributions from their Samples. COLT Sudeep Kamath, Alon Orlitsky, Dheeraj Pichapati, Ananda Theertha Suresh
2015	A	`conf`	Sparse Solutions to Nonnegative Linear Systems and Applications. AISTATS Aditya Bhaskara, Ananda Theertha Suresh, Morteza Zadimoghaddam
2015	J	`jnl`	Sparse Solutions to Nonnegative Linear Systems and Applications. CoRR Aditya Bhaskara, Ananda Theertha Suresh, Morteza Zadimoghaddam
2015	A*	`conf`	The Complexity of Estimating Rényi Entropy. SODA Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi
2015	J	`jnl`	Universal Compression of Power-Law Distributions. CoRR Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
2015	B	`conf`	Universal compression of power-law distributions. ISIT Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh
2014	B	`conf`	Efficient compression of monotone and m-modal distributions. ISIT Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2014	—	`conf`	Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures. NIPS Ananda Theertha Suresh, Alon Orlitsky, Jayadev Acharya, Ashkan Jafarpour
2014	J	`jnl`	Near-optimal-sample estimators for spherical Gaussian mixtures. CoRR Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2014	B	`conf`	Poissonization and universal compression of envelope classes. ISIT Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2014	B	`conf`	Sorting with adversarial comparators and application to density estimation. ISIT Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2014	B	`conf`	Sublinear algorithms for outlier detection and generalized closeness testing. ISIT Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2014	J	`jnl`	The Complexity of Estimating Rényi Entropy. CoRR Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi
2014	J	`jnl`	Universal Compression of Envelope Classes: Tight Characterization via Poisson Sampling. CoRR Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2013	A	`conf`	A Competitive Test for Uniformity of Monotone Distributions. AISTATS Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2013	J	`jnl`	Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems. IEEE Trans. Commun. Neelesh B. Mehta, Rajat Talak, Ananda Theertha Suresh
2013	A*	`conf`	Optimal Probability Estimation with Applications to Prediction and Classification. COLT Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2013	B	`conf`	Tight bounds for universal compression of large alphabets. ISIT Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh
2012	A*	`conf`	Competitive Classification and Closeness Testing. COLT Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Theertha Suresh
2012	B	`conf`	On the query computation and verification of functions. ISIT Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Theertha Suresh
2010	J	`jnl`	Strong Secrecy for Erasure Wiretap Channels. CoRR Ananda Theertha Suresh, Arunkumar Subramanian, Andrew Thangaraj, Matthieu R. Bloch, Steven W. McLaughlin
2010	B	`conf`	Strong secrecy for erasure wiretap channels. ITW Ananda Theertha Suresh, Arunkumar Subramanian, Andrew Thangaraj, Matthieu R. Bloch, Steven W. McLaughlin