Anit Kumar Sahu

74 papers A* 6A 2B 3C 1Misc 7Journal 46Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	MIRA: Towards Mitigating Reward Hacking in Inference-Time Alignment of T2I Diffusion Models. CoRR Kevin Zhai, Utsav Singh, Anirudh Thatipelli, Souradip Chakraborty, Anit Kumar Sahu, Furong Huang, Amrit Singh Bedi, Mubarak Shah
2025	J	`jnl`	Test-Time Scaling in Diffusion LLMs via Hidden Semi-Autoregressive Experts. CoRR Jihoon Lee, Hoyeon Moon, Kevin Zhai, Arun Kumar Chithanar, Anit Kumar Sahu, Soummya Kar, Chul Lee, Souradip Chakraborty, Amrit Singh Bedi
2024	J	`jnl`	Data-Centric Human Preference Optimization with Rationales. CoRR Hoang Anh Just, Ming Jin, Anit Kumar Sahu, Huy Phan, Ruoxi Jia
2024	A*	`conf`	Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs. ICLR Feiyang Kang, Hoang Anh Just, Yifan Sun, Himanshu Jahagirdar, Yuanzhi Zhang, Rongxing Du, Anit Kumar Sahu, Ruoxi Jia
2024	J	`jnl`	Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs. CoRR Feiyang Kang, Hoang Anh Just, Yifan Sun, Himanshu Jahagirdar, Yuanzhi Zhang, Rongxing Du, Anit Kumar Sahu, Ruoxi Jia
2024	J	`jnl`	Hierarchical Preference Optimization: Learning to achieve goals via feasible subgoals prediction. CoRR Utsav Singh, Souradip Chakraborty, Wesley A. Suttle, Brian M. Sadler, Anit Kumar Sahu, Mubarak Shah, Vinay P. Namboodiri, Amrit Singh Bedi
2023	J	`jnl`	Distributed Recursive Estimation under Heavy-Tail Communication Noise. SIAM J. Control. Optim. Dusan Jakovetic, Manojlo Vukovic, Dragana Bajovic, Anit Kumar Sahu, Soummya Kar
2023	J	`jnl`	Federated Representation Learning for Automatic Speech Recognition. CoRR Guruprasad V. Ramesh, Gopinath Chennupati, Milind Rao, Anit Kumar Sahu, Ariya Rastrow, Jasha Droppo
2023	Misc	`conf`	Federated Self-Learning with Weak Supervision for Speech Recognition. ICASSP Milind Rao, Gopinath Chennupati, Gautam Tiwari, Anit Kumar Sahu, Anirudh Raju, Ariya Rastrow, Jasha Droppo
2023	J	`jnl`	Federated Self-Learning with Weak Supervision for Speech Recognition. CoRR Milind Rao, Gopinath Chennupati, Gautam Tiwari, Anit Kumar Sahu, Anirudh Raju, Ariya Rastrow, Jasha Droppo
2023	J	`jnl`	Large Deviations for Products of Non-Identically Distributed Network Matrices With Applications to Communication-Efficient Distributed Learning and Inference. IEEE Trans. Signal Process. Nemanja Petrovic, Dragana Bajovic, Soummya Kar, Dusan Jakovetic, Anit Kumar Sahu
2023	A	`conf`	Learning When to Trust Which Teacher for Weakly Supervised ASR. INTERSPEECH Aakriti Agrawal, Milind Rao, Anit Kumar Sahu, Gopinath Chennupati, Andreas Stolcke
2023	J	`jnl`	Learning When to Trust Which Teacher for Weakly Supervised ASR. CoRR Aakriti Agrawal, Milind Rao, Anit Kumar Sahu, Gopinath Chennupati, Andreas Stolcke
2023	J	`jnl`	Nonlinear Gradient Mappings and Stochastic Optimization: A General Framework with Applications to Heavy-Tail Noise. SIAM J. Optim. Dusan Jakovetic, Dragana Bajovic, Anit Kumar Sahu, Soummya Kar, Nemanja Milosevic, Dusan Stamenkovic
2023	J	`jnl`	Partial model averaging in Federated Learning: Performance guarantees and benefits. Neurocomputing Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr
2023	A*	`conf`	Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources. NeurIPS Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia
2023	J	`jnl`	Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources. CoRR Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia
2023	J	`jnl`	RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation. CoRR Marco Bornstein, Amrit Singh Bedi, Anit Kumar Sahu, Furqan Khan, Furong Huang
2022	J	`jnl`	FedBC: Calibrating Global and Local Models via Federated Learning Beyond Consensus. CoRR Amrit Singh Bedi, Chen Fan, Alec Koppel, Anit Kumar Sahu, Brian M. Sadler, Furong Huang, Dinesh Manocha
2022	Misc	`conf`	Federated Learning Challenges and Opportunities: An Outlook. ICASSP Jie Ding, Eric W. Tramel, Anit Kumar Sahu, Shuang Wu, Salman Avestimehr, Tao Zhang
2022	J	`jnl`	Federated Learning Challenges and Opportunities: An Outlook. CoRR Jie Ding, Eric W. Tramel, Anit Kumar Sahu, Shuang Wu, Salman Avestimehr, Tao Zhang
2022	A*	`conf`	ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale. KDD 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
2022	J	`jnl`	ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale. CoRR 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
2022	J	`jnl`	Matcha: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization. IEEE Trans. Signal Process. Jianyu Wang, Anit Kumar Sahu, Gauri Joshi, Soummya Kar
2022	J	`jnl`	Nonlinear gradient mappings and stochastic optimization: A general framework with applications to heavy-tail noise. CoRR Dusan Jakovetic, Dragana Bajovic, Anit Kumar Sahu, Soummya Kar, Nemanja Milosevic, Dusan Stamenkovic
2022	J	`jnl`	Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits. CoRR Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr
2022	A*	`conf`	Self-Aware Personalized Federated Learning. NeurIPS Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang
2022	J	`jnl`	Self-Aware Personalized Federated Learning. CoRR Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang
2021	A*	`conf`	Multiplicative Filter Networks. ICLR Rizal Fathony, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter
2021	A*	`conf`	Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes. KDD Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter
2021	J	`jnl`	You Only Query Once: Effective Black Box Adversarial Attacks with Minimal Repeated Queries. CoRR Devin Willmott, Anit Kumar Sahu, Fatemeh Sheikholeslami, Filipe Condessa, J. Zico Kolter
2020	J	`jnl`	Data-driven Thermal Model Inference with ARMAX, in Smart Environments, based on Normalized Mutual Information. CoRR Zhanhong Jiang, Jonathan Francis, Anit Kumar Sahu, Sirajum Munir, Charles Shelton, Anthony Rowe, Mario Bergés
2020	J	`jnl`	Decentralized Zeroth-Order Constrained Stochastic Optimization Algorithms: Frank-Wolfe and Variants With Applications to Black-Box Adversarial Attacks. Proc. IEEE Anit Kumar Sahu, Soummya Kar
2020	Misc	`conf`	Exploring the Error-Runtime Trade-off in Decentralized Optimization. ACSSC Jianyu Wang, Anit Kumar Sahu, Gauri Joshi, Soummya Kar
2020	J	`jnl`	FedDANE: A Federated Newton-Type Method. CoRR Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith
2020	J	`jnl`	Federated Learning: Challenges, Methods, and Future Directions. IEEE Signal Process. Mag. Tian Li, Anit Kumar Sahu, Ameet Talwalkar, Virginia Smith
2020	—	`conf`	Federated Optimization in Heterogeneous Networks. MLSys Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith
2020	J	`jnl`	Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial Attacks. CoRR Anit Kumar Sahu, Satya Narayan Shukla, J. Zico Kolter
2020	J	`jnl`	Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes. CoRR Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter
2019	J	`jnl`	Black-box Adversarial Attacks with Bayesian Optimization. CoRR Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter
2019	—	`conf`	Communication Efficient Distributed Estimation Over Directed Random Graphs. EUROCON Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar
2019	Misc	`conf`	Distributed empirical risk minimization over directed graphs. ACSSC Ran Xin, Anit Kumar Sahu, Soummya Kar, Usman A. Khan
2019	—	`conf`	Distributed stochastic optimization with gradient tracking over strongly-connected networks. CDC Ran Xin, Anit Kumar Sahu, Usman A. Khan, Soummya Kar
2019	J	`jnl`	Distributed stochastic optimization with gradient tracking over strongly-connected networks. CoRR Ran Xin, Anit Kumar Sahu, Usman A. Khan, Soummya Kar
2019	Misc	`conf`	FedDANE: A Federated Newton-Type Method. ACSSC Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith
2019	J	`jnl`	Federated Learning: Challenges, Methods, and Future Directions. CoRR Tian Li, Anit Kumar Sahu, Ameet Talwalkar, Virginia Smith
2019	J	`jnl`	Learning in Confusion: Batch Active Learning with Noisy Oracle. CoRR Gaurav Gupta, Anit Kumar Sahu, Wan-Yi Lin
2019	J	`jnl`	MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling. CoRR Jianyu Wang, Anit Kumar Sahu, Zhouyi Yang, Gauri Joshi, Soummya Kar
2019	A	`conf`	Towards Gradient Free and Projection Free Stochastic Optimization. AISTATS Anit Kumar Sahu, Manzil Zaheer, Soummya Kar
2018	J	`jnl`	CIRFE: A Distributed Random Fields Estimator. CoRR Anit Kumar Sahu, Dusan Jakovetic, Soummya Kar
2018	J	`jnl`	CIRFE: A Distributed Random Fields Estimator. IEEE Trans. Signal Process. Anit Kumar Sahu, Dusan Jakovetic, Soummya Kar
2018	B	`conf`	CREDO: A Communication-Efficient Distributed Estimation Algorithm. ISIT Anit Kumar Sahu, Dusan Jakovetic, Soummya Kar
2018	J	`jnl`	Communication efficient distributed weighted non-linear least squares estimation. EURASIP J. Adv. Signal Process. Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar
2018	—	`conf`	Convergence Rates for Distributed Stochastic Optimization Over Random Networks. CDC Dusan Jakovetic, Dragana Bajovic, Anit Kumar Sahu, Soummya Kar
2018	C	`conf`	Data-driven Thermal Model Inference with ARMAX, in Smart Environments, based on Normalized Mutual Information. ACC Zhanhong Jiang, Jonathan Francis, Anit Kumar Sahu, Sirajum Munir, Charles Shelton, Anthony Rowe, Mario Berges
2018	—	`conf`	Distributed Zeroth Order Optimization Over Random Networks: A Kiefer-Wolfowitz Stochastic Approximation Approach. CDC Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar
2018	B	`conf`	Large Deviations for Products of Non-I.i.d. Stochastic Matrices with Application to Distributed Detection. ISIT Dragana Bajovic, Dusan Jakovetic, Anit Kumar Sahu, Soummya Kar
2018	J	`jnl`	Managing App Install Ad Campaigns in RTB: A Q-Learning Approach. CoRR Anit Kumar Sahu, Shaunak Mishra, Narayan Bhamidipati
2018	—	`conf`	Non-Asymptotic Rates for Communication Efficient Distributed Zeroth Order Strongly Convex Optimization. GlobalSIP Anit Kumar Sahu, Dusan Jakovetic, Dragana Bajovic, Soummya Kar
2018	J	`jnl`	On the Convergence of Federated Optimization in Heterogeneous Networks. CoRR Anit Kumar Sahu, Tian Li, Maziar Sanjabi, Manzil Zaheer, Ameet Talwalkar, Virginia Smith
2018	J	`jnl`	Towards Gradient Free and Projection Free Stochastic Optimization. CoRR Anit Kumar Sahu, Manzil Zaheer, Soummya Kar
2017	—	`conf`	Dist-Hedge: A partial information setting based distributed non-stochastic sequence prediction algorithm. GlobalSIP Anit Kumar Sahu, Soummya Kar
2017	J	`jnl`	Recursive Distributed Detection for Composite Hypothesis Testing: Nonlinear Observation Models in Additive Gaussian Noise. IEEE Trans. Inf. Theory Anit Kumar Sahu, Soummya Kar
2016	J	`jnl`	Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics. CoRR Anit Kumar Sahu, Soummya Kar, José M. F. Moura, H. Vincent Poor
2016	J	`jnl`	Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics. IEEE Trans. Signal Inf. Process. over Networks Anit Kumar Sahu, Soummya Kar, José M. F. Moura, H. Vincent Poor
2016	J	`jnl`	Distributed Sequential Detection for Gaussian Shift-in-Mean Hypothesis Testing. IEEE Trans. Signal Process. Anit Kumar Sahu, Soummya Kar
2016	Misc	`conf`	Distributed generalized likelihood ratio tests: Fundamental limits and tradeoffs. ICASSP Anit Kumar Sahu, Soummya Kar
2016	B	`conf`	Distributed recursive composite hypothesis testing: Imperfect communication. ISIT Anit Kumar Sahu, Soummya Kar
2016	—	`conf`	Distributed sequence prediction: A consensus+innovations approach. GlobalSIP Anit Kumar Sahu, Soummya Kar
2016	—	`conf`	Queue-based broadcast gossip algorithm for consensus. Allerton Soummya Kar, Rohit Negi, Majid Mahzoon, Anit Kumar Sahu
2016	J	`jnl`	Recursive Distributed Detection for Composite Hypothesis Testing: Algorithms and Asymptotics. CoRR Anit Kumar Sahu, Soummya Kar
2014	J	`jnl`	Distributed Sequential Detection for Gaussian Binary Hypothesis Testing. CoRR Anit Kumar Sahu, Soummya Kar
2014	Misc	`conf`	Distributed sequential detection for Gaussian binary hypothesis testing: Heterogeneous networks. ACSSC Anit Kumar Sahu, Soummya Kar
2012	J	`jnl`	Fast and Accurate Frequency Estimation Using Sliding DFT CoRR Anit Kumar Sahu, Mrityunjoy Chakraborty