45 citations · 45 across the 3 of their papers we have counts for
3 papers
cs.LG2023
A Note on Noisy Reservoir Computation
Anthony M. Polloreno, Reuben R. W. Wang, Nikolas A. Tezak
In this note we extend the definition of the Information Processing Capacity (IPC) by Dambre et al [1] to include the effects of stochastic reservoir dynamics. We quantify the degr…
cs.CL2022★ 45 cited
Efficient Training of Language Models to Fill in the Middle
Mohammad Bavarian, Heewoo Jun, Nikolas Tezak +4
We show that autoregressive language models can learn to infill text after we apply a straightforward transformation to the dataset, which simply moves a span of text from the midd…
quant-ph2015
A Coherent Perceptron for All-Optical Learning
Nikolas Tezak, Hideo Mabuchi
We present nonlinear photonic circuit models for constructing programmable linear transformations and use these to realize a coherent Perceptron, i.e., an all-optical linear classi…