978 citations · 1.6k across the 24 of their papers we have counts for
3 papers · 1 filter
Hierarchy through Composition with Linearly Solvable Markov Decision Processes
Andrew M. Saxe, Adam Earle, Benjamin Rosman
Hierarchical architectures are critical to the scalability of reinforcement learning methods. Current hierarchical frameworks execute actions serially, with macro-actions comprisin…
Tensor Switching Networks
Chuan-Yung Tsai, Andrew Saxe, David Cox
We present a novel neural network algorithm, the Tensor Switching (TS) network, which generalizes the Rectified Linear Unit (ReLU) nonlinearity to tensor-valued hidden units. The T…
Active Long Term Memory Networks
Tommaso Furlanello, Jiaping Zhao, Andrew M. Saxe +2
Continual Learning in artificial neural networks suffers from interference and forgetting when different tasks are learned sequentially. This paper introduces the Active Long Term…