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20242026
most citedTowards Fast Rates for Federated and Multi-Task Reinforcement Learning

1 citations · 1 across the 6 of their papers we have counts for

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cs.CL2025

LoLA: Low-Rank Linear Attention With Sparse Caching

Luke McDermott, Robert W. Heath, Rahul Parhi

The per-token cost of transformer inference scales with context length, preventing its application to lifelong in-context learning. Linear attention is an efficient alternative tha…

cs.LG2025

Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling

Feng Zhu, Aritra Mitra, Robert W. Heath

Motivated by collaborative reinforcement learning (RL) and optimization with time-correlated data, we study a generic federated stochastic approximation problem involving agent…