Ananda Theertha Suresh

According to our database, Ananda Theertha Suresh authored at least 104 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Wyner-Ziv Estimators for Distributed Mean Estimation With Side Information and Optimization.

Prathamesh Mayekar, Shubham K. Jha, Ananda Theertha Suresh, Himanshu Tyagi

IEEE Trans. Inf. Theory, April, 2024

Coupling without Communication and Drafter-Invariant Speculative Decoding.

Majid Daliri, Christopher Musco, Ananda Theertha Suresh

CoRR, 2024

Private federated discovery of out-of-vocabulary words for Gboard.

Ziteng Sun, Peter Kairouz, Haicheng Sun, Adrià Gascón, Ananda Theertha Suresh

CoRR, 2024

Towards Fast Inference: Exploring and Improving Blockwise Parallel Drafts.

Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael Riley, Sanjiv Kumar, Adrian Benton

CoRR, 2024

Optimal Block-Level Draft Verification for Accelerating Speculative Decoding.

Ziteng Sun, Jae Hun Ro, Ahmad Beirami, Ananda Theertha Suresh

CoRR, 2024

Efficient Language Model Architectures for Differentially Private Federated Learning.

Jae Hun Ro, Srinadh Bhojanapalli, Zheng Xu, Yanxiang Zhang, Ananda Theertha Suresh

CoRR, 2024

Theoretical guarantees on the best-of-n alignment policy.

Ahmad Beirami, Alekh Agarwal, Jonathan Berant, Alexander D'Amour, Jacob Eisenstein, Chirag Nagpal, Ananda Theertha Suresh

CoRR, 2024

Asymptotics of Language Model Alignment.

Joy Qiping Yang, Salman Salamatian, Ziteng Sun, Ananda Theertha Suresh, Ahmad Beirami

Proceedings of the IEEE International Symposium on Information Theory, 2024

Mean Estimation in the Add-Remove Model of Differential Privacy.

Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

The importance of feature preprocessing for differentially private linear optimization.

Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon

Proceedings of the Twelfth International Conference on Learning Representations, 2024

FedAQT: Accurate Quantized Training with Federated Learning.

Renkun Ni, Yonghui Xiao, Phoenix Meadowlark, Oleg Rybakov, Tom Goldstein, Ananda Theertha Suresh, Ignacio López-Moreno, Mingqing Chen, Rajiv Mathews

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Multi-Group Fairness Evaluation via Conditional Value-at-Risk Testing.

Lucas Monteiro Paes, Ananda Theertha Suresh, Alex Beutel, Flávio P. Calmon, Ahmad Beirami

CoRR, 2023

FedYolo: Augmenting Federated Learning with Pretrained Transformers.

Xuechen Zhang, Mingchen Li, Xiangyu Chang, Jiasi Chen, Amit K. Roy-Chowdhury, Ananda Theertha Suresh, Samet Oymak

CoRR, 2023

SpecTr: Fast Speculative Decoding via Optimal Transport.

Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix X. Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Concentration Bounds for Discrete Distribution Estimation in KL Divergence.

Clément L. Canonne, Ziteng Sun, Ananda Theertha Suresh

Proceedings of the IEEE International Symposium on Information Theory, 2023

Algorithms for bounding contribution for histogram estimation under user-level privacy.

Yuhan Liu, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser

Proceedings of the International Conference on Machine Learning, 2023

Federated Heavy Hitter Recovery under Linear Sketching.

Adrià Gascón, Peter Kairouz, Ziteng Sun, Ananda Theertha Suresh

Proceedings of the International Conference on Machine Learning, 2023

Subset-Based Instance Optimality in Private Estimation.

Travis Dick, Alex Kulesza, Ziteng Sun, Ananda Theertha Suresh

Proceedings of the International Conference on Machine Learning, 2023

Principled Approaches for Private Adaptation from a Public Source.

Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Private Domain Adaptation from a Public Source.

Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

CoRR, 2022

Histogram Estimation under User-level Privacy with Heterogeneous Data.

Yuhan Liu, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser

CoRR, 2022

Scaling Language Model Size in Cross-Device Federated Learning.

Jae Hun Ro, Theresa Breiner, Lara McConnaughey, Mingqing Chen, Ananda Theertha Suresh, Shankar Kumar, Rajiv Mathews

CoRR, 2022

Differentially Private Learning with Margin Guarantees.

Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Correlated Quantization for Distributed Mean Estimation and Optimization.

Ananda Theertha Suresh, Ziteng Sun, Jae Ro, Felix X. Yu

Proceedings of the International Conference on Machine Learning, 2022

The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning.

Wei-Ning Chen, Christopher A. Choquette-Choo, Peter Kairouz, Ananda Theertha Suresh

Proceedings of the International Conference on Machine Learning, 2022

On the benefits of maximum likelihood estimation for Regression and Forecasting.

Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh

Proceedings of the Tenth International Conference on Learning Representations, 2022

Robust Estimation for Random Graphs.

Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs.

Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh

IEEE J. Sel. Areas Inf. Theory, 2021

Advances and Open Problems in Federated Learning.

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

Found. Trends Mach. Learn., 2021

HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation.

Wittawat Jitkrittum, Michal Lukasik, Ananda Theertha Suresh, Felix X. Yu, Gang Wang

CoRR, 2021

FedJAX: Federated learning simulation with JAX.

Jae Hun Ro, Ananda Theertha Suresh, Ke Wu

CoRR, 2021

A Field Guide to Federated Optimization.

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

CoRR, 2021

Approximating Probabilistic Models as Weighted Finite Automata.

Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol

Comput. Linguistics, 2021

Remember What You Want to Forget: Algorithms for Machine Unlearning.

Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning with User-Level Privacy.

Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Breaking the centralized barrier for cross-device federated learning.

Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Boosting with Multiple Sources.

Corinna Cortes, Mehryar Mohri, Dmitry Storcheus, Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Communication-Efficient Agnostic Federated Averaging.

Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh

Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

A Discriminative Technique for Multiple-Source Adaptation.

Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang

Proceedings of the 38th International Conference on Machine Learning, 2021

Relative Deviation Margin Bounds.

Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh

Proceedings of the 38th International Conference on Machine Learning, 2021

On the Rényi Differential Privacy of the Shuffle Model.

Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Robust hypothesis testing and distribution estimation in Hellinger distance.

Ananda Theertha Suresh

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information.

Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

A Theory of Multiple-Source Adaptation with Limited Target Labeled Data.

Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Shuffled Model of Differential Privacy in Federated Learning.

Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Multiple-Source Adaptation with Domain Classifiers.

Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang

CoRR, 2020

Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs.

Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh

CoRR, 2020

Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning.

Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh

CoRR, 2020

A Theory of Multiple-Source Adaptation with Limited Target Labeled Data.

Yishay Mansour, Mehryar Mohri, Ananda Theertha Suresh, Ke Wu

CoRR, 2020

Three Approaches for Personalization with Applications to Federated Learning.

Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh

CoRR, 2020

Learning discrete distributions: user vs item-level privacy.

Yuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SCAFFOLD: Stochastic Controlled Averaging for Federated Learning.

Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh

Proceedings of the 37th International Conference on Machine Learning, 2020

FedBoost: A Communication-Efficient Algorithm for Federated Learning.

Jenny Hamer, Mehryar Mohri, Ananda Theertha Suresh

Proceedings of the 37th International Conference on Machine Learning, 2020

Optimal multiclass overfitting by sequence reconstruction from Hamming queries.

Jayadev Acharya, Ananda Theertha Suresh

Proceedings of the Algorithmic Learning Theory, 2020

2019

Advances and Open Problems in Federated Learning.

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

CoRR, 2019

Can You Really Backdoor Federated Learning?

Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, H. Brendan McMahan

CoRR, 2019

SCAFFOLD: Stochastic Controlled Averaging for On-Device Federated Learning.

Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh

CoRR, 2019

AdaCliP: Adaptive Clipping for Private SGD.

Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar

CoRR, 2019

Differentially Private Anonymized Histograms.

Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sampled Softmax with Random Fourier Features.

Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Convergence of Chao Unseen Species Estimator.

Nived Rajaraman, Prafulla Chandra, Andrew Thangaraj, Ananda Theertha Suresh

Proceedings of the IEEE International Symposium on Information Theory, 2019

Agnostic Federated Learning.

Mehryar Mohri, Gary Sivek, Ananda Theertha Suresh

Proceedings of the 36th International Conference on Machine Learning, 2019

West: Word Encoded Sequence Transducers.

Ehsan Variani, Ananda Theertha Suresh, Mitchel Weintraub

Proceedings of the IEEE International Conference on Acoustics, 2019

Distilling weighted finite automata from arbitrary probabilistic models.

Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol

Proceedings of the 14th International Conference on Finite-State Methods and Natural Language Processing, 2019

Federated Learning of N-Gram Language Models.

Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley

Proceedings of the 23rd Conference on Computational Natural Language Learning, 2019

2018

Maximum Selection and Sorting with Adversarial Comparators.

Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

J. Mach. Learn. Res., 2018

Data Amplification: A Unified and Competitive Approach to Property Estimation.

Yi Hao, Alon Orlitsky, Ananda Theertha Suresh, Yihong Wu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

cpSGD: Communication-efficient and differentially-private distributed SGD.

Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Brendan McMahan

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Estimating Renyi Entropy of Discrete Distributions.

Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi

IEEE Trans. Inf. Theory, 2017

Multiscale Quantization for Fast Similarity Search.

Xiang Wu, Ruiqi Guo, Ananda Theertha Suresh, Sanjiv Kumar, Daniel N. Holtmann-Rice, David Simcha, Felix X. Yu

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Model-Powered Conditional Independence Test.

Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Minimax risk for missing mass estimation.

Nikhilesh Rajaraman, Andrew Thangaraj, Ananda Theertha Suresh

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Distributed Mean Estimation with Limited Communication.

Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan

Proceedings of the 34th International Conference on Machine Learning, 2017

Maximum Selection and Ranking under Noisy Comparisons.

Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh

Proceedings of the 34th International Conference on Machine Learning, 2017

A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions.

Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 34th International Conference on Machine Learning, 2017

Sample complexity of population recovery.

Yury Polyanskiy, Ananda Theertha Suresh, Yihong Wu

Proceedings of the 30th Conference on Learning Theory, 2017

Lattice rescoring strategies for long short term memory language models in speech recognition.

Shankar Kumar, Michael Nirschl, Daniel Niels Holtmann-Rice, Hank Liao, Ananda Theertha Suresh, Felix X. Yu

Proceedings of the 2017 IEEE Automatic Speech Recognition and Understanding Workshop, 2017

2016

A Unified Maximum Likelihood Approach for Optimal Distribution Property Estimation.

Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh

Electron. Colloquium Comput. Complex., 2016

Federated Learning: Strategies for Improving Communication Efficiency.

Jakub Konecný, H. Brendan McMahan, Felix X. Yu, Peter Richtárik, Ananda Theertha Suresh, Dave Bacon

CoRR, 2016

Maximum Selection and Sorting with Adversarial Comparators and an Application to Density Estimation.

Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

CoRR, 2016

Orthogonal Random Features.

Felix X. Yu, Ananda Theertha Suresh, Krzysztof Marcin Choromanski, Daniel N. Holtmann-Rice, Sanjiv Kumar

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning Markov distributions: Does estimation trump compression?

Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh

Proceedings of the IEEE International Symposium on Information Theory, 2016

Estimating the number of defectives with group testing.

Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh

Proceedings of the IEEE International Symposium on Information Theory, 2016

2015

Competitive Distribution Estimation.

Alon Orlitsky, Ananda Theertha Suresh

CoRR, 2015

The Complexity of Estimating Rényi Entropy.

Jayadev Acharya, Alon Orlitsky, Ananda Theertha Suresh, Himanshu Tyagi

Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Competitive Distribution Estimation: Why is Good-Turing Good.

Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Automata and graph compression.

Mehryar Mohri, Michael Riley, Ananda Theertha Suresh

Proceedings of the IEEE International Symposium on Information Theory, 2015

Universal compression of power-law distributions.

Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh

Proceedings of the IEEE International Symposium on Information Theory, 2015

On Learning Distributions from their Samples.

Sudeep Kamath, Alon Orlitsky, Dheeraj Pichapati, Ananda Theertha Suresh

Proceedings of The 28th Conference on Learning Theory, 2015

Faster Algorithms for Testing under Conditional Sampling.

Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh

Proceedings of The 28th Conference on Learning Theory, 2015

Sparse Solutions to Nonnegative Linear Systems and Applications.

Aditya Bhaskara, Ananda Theertha Suresh, Morteza Zadimoghaddam

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Universal Compression of Envelope Classes: Tight Characterization via Poisson Sampling.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

CoRR, 2014

Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures.

Ananda Theertha Suresh, Alon Orlitsky, Jayadev Acharya, Ashkan Jafarpour

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Sublinear algorithms for outlier detection and generalized closeness testing.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Poissonization and universal compression of envelope classes.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Efficient compression of monotone and m-modal distributions.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Sorting with adversarial comparators and application to density estimation.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2013

Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems.

Neelesh B. Mehta, Rajat Talak, Ananda Theertha Suresh

IEEE Trans. Commun., 2013

Tight bounds for universal compression of large alphabets.

Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Optimal Probability Estimation with Applications to Prediction and Classification.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the COLT 2013, 2013

A Competitive Test for Uniformity of Monotone Distributions.

Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Competitive Classification and Closeness Testing.

Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Theertha Suresh

Proceedings of the COLT 2012, 2012

On the query computation and verification of functions.

Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Theertha Suresh

Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

2010

Strong secrecy for erasure wiretap channels.

Ananda Theertha Suresh, Arunkumar Subramanian, Andrew Thangaraj, Matthieu R. Bloch, Steven W. McLaughlin

Proceedings of the 2010 IEEE Information Theory Workshop, 2010