Anit Kumar Sahu

According to our database, Anit Kumar Sahu authored at least 56 papers between 2012 and 2024.

Collaborative distances:

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

2024

Hierarchical Preference Optimization: Learning to achieve goals via feasible subgoals prediction.

Utsav Singh, Souradip Chakraborty, Wesley A. Suttle, Brian M. Sadler, Anit Kumar Sahu, Mubarak Shah, Vinay P. Namboodiri, Amrit Singh Bedi

CoRR, 2024

Data-Centric Human Preference Optimization with Rationales.

Hoang Anh Just, Ming Jin, Anit Kumar Sahu, Huy Phan, Ruoxi Jia

CoRR, 2024

Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs.

Feiyang Kang, Hoang Anh Just, Yifan Sun, Himanshu Jahagirdar, Yuanzhi Zhang, Rongxing Du, Anit Kumar Sahu, Ruoxi Jia

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Partial model averaging in Federated Learning: Performance guarantees and benefits.

Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr

Neurocomputing, November, 2023

Distributed Recursive Estimation under Heavy-Tail Communication Noise.

Dusan Jakovetic, Manojlo Vukovic, Dragana Bajovic, Anit Kumar Sahu, Soummya Kar

SIAM J. Control. Optim., June, 2023

Large Deviations for Products of Non-Identically Distributed Network Matrices With Applications to Communication-Efficient Distributed Learning and Inference.

Nemanja Petrovic, Dragana Bajovic, Soummya Kar, Dusan Jakovetic, Anit Kumar Sahu

IEEE Trans. Signal Process., 2023

Nonlinear Gradient Mappings and Stochastic Optimization: A General Framework with Applications to Heavy-Tail Noise.

Dusan Jakovetic, Dragana Bajovic, Anit Kumar Sahu, Soummya Kar, Nemanja Milosevic, Dusan Stamenkovic

SIAM J. Optim., 2023

RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation.

Marco Bornstein, Amrit Singh Bedi, Anit Kumar Sahu, Furqan Khan, Furong Huang

CoRR, 2023

Federated Representation Learning for Automatic Speech Recognition.

Guruprasad V. Ramesh, Gopinath Chennupati, Milind Rao, Anit Kumar Sahu, Ariya Rastrow, Jasha Droppo

CoRR, 2023

Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources.

Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia

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

Learning When to Trust Which Teacher for Weakly Supervised ASR.

Aakriti Agrawal, Milind Rao, Anit Kumar Sahu, Gopinath Chennupati, Andreas Stolcke

Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Federated Self-Learning with Weak Supervision for Speech Recognition.

Milind Rao, Gopinath Chennupati, Gautam Tiwari, Anit Kumar Sahu, Anirudh Raju, Ariya Rastrow, Jasha Droppo

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Matcha: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization.

Jianyu Wang, Anit Kumar Sahu, Gauri Joshi, Soummya Kar

IEEE Trans. Signal Process., 2022

FedBC: Calibrating Global and Local Models via Federated Learning Beyond Consensus.

Amrit Singh Bedi, Chen Fan, Alec Koppel, Anit Kumar Sahu, Brian M. Sadler, Furong Huang, Dinesh Manocha

CoRR, 2022

Self-Aware Personalized Federated Learning.

Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang

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

ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale.

Gopinath Chennupati, Milind Rao, Gurpreet Chadha, Aaron Eakin, Anirudh Raju, Gautam Tiwari, Anit Kumar Sahu, Ariya Rastrow, Jasha Droppo, Andy Oberlin, Buddha Nandanoor, Prahalad Venkataramanan, Zheng Wu, Pankaj Sitpure

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Federated Learning Challenges and Opportunities: An Outlook.

Jie Ding, Eric W. Tramel, Anit Kumar Sahu, Shuang Wu, Salman Avestimehr, Tao Zhang

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

You Only Query Once: Effective Black Box Adversarial Attacks with Minimal Repeated Queries.

Devin Willmott, Anit Kumar Sahu, Fatemeh Sheikholeslami, Filipe Condessa, J. Zico Kolter

CoRR, 2021

Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes.

Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Multiplicative Filter Networks.

Rizal Fathony, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Federated Learning: Challenges, Methods, and Future Directions.

Tian Li, Anit Kumar Sahu, Ameet Talwalkar, Virginia Smith

IEEE Signal Process. Mag., 2020

Decentralized Zeroth-Order Constrained Stochastic Optimization Algorithms: Frank-Wolfe and Variants With Applications to Black-Box Adversarial Attacks.

Anit Kumar Sahu, Soummya Kar

Proc. IEEE, 2020

Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial Attacks.

Anit Kumar Sahu, Satya Narayan Shukla, J. Zico Kolter

CoRR, 2020

Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes.

Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter

CoRR, 2020

Federated Optimization in Heterogeneous Networks.

Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith

Proceedings of the Third Conference on Machine Learning and Systems, 2020

Exploring the Error-Runtime Trade-off in Decentralized Optimization.

Jianyu Wang, Anit Kumar Sahu, Gauri Joshi, Soummya Kar

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Black-box Adversarial Attacks with Bayesian Optimization.

Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter

CoRR, 2019

Learning in Confusion: Batch Active Learning with Noisy Oracle.

Gaurav Gupta, Anit Kumar Sahu, Wan-Yi Lin

CoRR, 2019

MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling.

Jianyu Wang, Anit Kumar Sahu, Zhouyi Yang, Gauri Joshi, Soummya Kar

CoRR, 2019

Communication Efficient Distributed Estimation Over Directed Random Graphs.

Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar

Proceedings of the IEEE EUROCON 2019, 2019

Distributed stochastic optimization with gradient tracking over strongly-connected networks.

Ran Xin, Anit Kumar Sahu, Usman A. Khan, Soummya Kar

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Towards Gradient Free and Projection Free Stochastic Optimization.

Anit Kumar Sahu, Manzil Zaheer, Soummya Kar

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Distributed empirical risk minimization over directed graphs.

Ran Xin, Anit Kumar Sahu, Soummya Kar, Usman A. Khan

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

FedDANE: A Federated Newton-Type Method.

Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

CIRFE: A Distributed Random Fields Estimator.

Anit Kumar Sahu, Dusan Jakovetic, Soummya Kar

IEEE Trans. Signal Process., 2018

Communication efficient distributed weighted non-linear least squares estimation.

Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar

EURASIP J. Adv. Signal Process., 2018

On the Convergence of Federated Optimization in Heterogeneous Networks.

Anit Kumar Sahu, Tian Li, Maziar Sanjabi, Manzil Zaheer, Ameet Talwalkar, Virginia Smith

CoRR, 2018

Managing App Install Ad Campaigns in RTB: A Q-Learning Approach.

Anit Kumar Sahu, Shaunak Mishra, Narayan Bhamidipati

CoRR, 2018

CREDO: A Communication-Efficient Distributed Estimation Algorithm.

Anit Kumar Sahu, Dusan Jakovetic, Soummya Kar

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Large Deviations for Products of Non-I.i.d. Stochastic Matrices with Application to Distributed Detection.

Dragana Bajovic, Dusan Jakovetic, Anit Kumar Sahu, Soummya Kar

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Non-Asymptotic Rates for Communication Efficient Distributed Zeroth Order Strongly Convex Optimization.

Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar

Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Distributed Zeroth Order Optimization Over Random Networks: A Kiefer-Wolfowitz Stochastic Approximation Approach.

Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Convergence Rates for Distributed Stochastic Optimization Over Random Networks.

Dusan Jakovetic, Dragana Bajovic, Anit Kumar Sahu, Soummya Kar

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Data-driven Thermal Model Inference with ARMAX, in Smart Environments, based on Normalized Mutual Information.

Zhanhong Jiang, Jonathan Francis, Anit Kumar Sahu, Sirajum Munir, Charles Shelton, Anthony Rowe, Mario Berges

Proceedings of the 2018 Annual American Control Conference, 2018

2017

Recursive Distributed Detection for Composite Hypothesis Testing: Nonlinear Observation Models in Additive Gaussian Noise.

Anit Kumar Sahu, Soummya Kar

IEEE Trans. Inf. Theory, 2017

Dist-Hedge: A partial information setting based distributed non-stochastic sequence prediction algorithm.

Anit Kumar Sahu, Soummya Kar

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016

Distributed Sequential Detection for Gaussian Shift-in-Mean Hypothesis Testing.

Anit Kumar Sahu, Soummya Kar

IEEE Trans. Signal Process., 2016

Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics.

Anit Kumar Sahu, Soummya Kar, José M. F. Moura, H. Vincent Poor

IEEE Trans. Signal Inf. Process. over Networks, 2016

Recursive Distributed Detection for Composite Hypothesis Testing: Algorithms and Asymptotics.

Anit Kumar Sahu, Soummya Kar

CoRR, 2016

Distributed recursive composite hypothesis testing: Imperfect communication.

Anit Kumar Sahu, Soummya Kar

Proceedings of the IEEE International Symposium on Information Theory, 2016

Distributed generalized likelihood ratio tests: Fundamental limits and tradeoffs.

Anit Kumar Sahu, Soummya Kar

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Distributed sequence prediction: A consensus+innovations approach.

Anit Kumar Sahu, Soummya Kar

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Queue-based broadcast gossip algorithm for consensus.

Soummya Kar, Rohit Negi, Majid Mahzoon, Anit Kumar Sahu

Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2014

Distributed Sequential Detection for Gaussian Binary Hypothesis Testing.

Anit Kumar Sahu, Soummya Kar

CoRR, 2014

Distributed sequential detection for Gaussian binary hypothesis testing: Heterogeneous networks.

Anit Kumar Sahu, Soummya Kar

Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2012

Fast and Accurate Frequency Estimation Using Sliding DFT

Anit Kumar Sahu, Mrityunjoy Chakraborty

CoRR, 2012