Anit Kumar Sahu
Orcid: 0000-0002-4083-0418
According to our database1,
Anit Kumar Sahu
authored at least 55 papers
between 2012 and 2024.
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Bibliography
2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Neurocomputing, November, 2023
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.
IEEE Trans. Signal Process., 2023
Nonlinear Gradient Mappings and Stochastic Optimization: A General Framework with Applications to Heavy-Tail Noise.
SIAM J. Optim., 2023
RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation.
CoRR, 2023
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
2022
Matcha: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization.
IEEE Trans. Signal Process., 2022
CoRR, 2022
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.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
2021
You Only Query Once: Effective Black Box Adversarial Attacks with Minimal Repeated Queries.
CoRR, 2021
Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
IEEE Signal Process. Mag., 2020
Decentralized Zeroth-Order Constrained Stochastic Optimization Algorithms: Frank-Wolfe and Variants With Applications to Black-Box Adversarial Attacks.
Proc. IEEE, 2020
CoRR, 2020
Proceedings of the Third Conference on Machine Learning and Systems, 2020
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020
2019
CoRR, 2019
Proceedings of the IEEE EUROCON 2019, 2019
Distributed stochastic optimization with gradient tracking over strongly-connected networks.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
2018
EURASIP J. Adv. Signal Process., 2018
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.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018
Non-Asymptotic Rates for Communication Efficient Distributed Zeroth Order Strongly Convex Optimization.
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.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
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.
Proceedings of the 2018 Annual American Control Conference, 2018
2017
Recursive Distributed Detection for Composite Hypothesis Testing: Nonlinear Observation Models in Additive Gaussian Noise.
IEEE Trans. Inf. Theory, 2017
Dist-Hedge: A partial information setting based distributed non-stochastic sequence prediction algorithm.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017
2016
IEEE Trans. Signal Process., 2016
Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics.
IEEE Trans. Signal Inf. Process. over Networks, 2016
Recursive Distributed Detection for Composite Hypothesis Testing: Algorithms and Asymptotics.
CoRR, 2016
Proceedings of the IEEE International Symposium on Information Theory, 2016
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016
Proceedings of the 54th Annual Allerton Conference on Communication, 2016
2014
Distributed sequential detection for Gaussian binary hypothesis testing: Heterogeneous networks.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014
2012