Sahu, Anit Kumar

9 publications

ICLR 2026 Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach Utsav Singh, Souradip Chakraborty, Wesley A. Suttle, Brian M. Sadler, Derrik E. Asher, Anit Kumar Sahu, Mubarak Shah, Vinay P. Namboodiri, Amrit Singh Bedi

ICLR 2026 Test-Time Scaling in Diffusion LLMs via Hidden Semi-Autoregressive Experts Jihoon Lee, Hoyeon Moon, Kevin Zhai, Arun Kumar Chithanar, Anit Kumar Sahu, Soummya Kar, Chul Lee, Souradip Chakraborty, Amrit Singh Bedi

ICLR 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

NeurIPS 2023 Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia

NeurIPSW 2023 RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation Marco Bornstein, Amrit Bedi, Anit Kumar Sahu, Furqan Khan, Furong Huang

NeurIPS 2022 Self-Aware Personalized Federated Learning Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang

ICLR 2021 Multiplicative Filter Networks Rizal Fathony, Anit Kumar Sahu, Devin Willmott, J Zico Kolter

ICMLW 2019 Federated Optimization for Heterogeneous Networks Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith

AISTATS 2019 Towards Gradient Free and Projection Free Stochastic Optimization Anit Kumar Sahu, Manzil Zaheer, Soummya Kar