18 citations · 37 across the 7 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2023
Hierarchical Partitioning Forecaster
Christopher Mattern
In this work we consider a new family of algorithms for sequential prediction, Hierarchical Partitioning Forecasters (HPFs). Our goal is to provide appealing theoretical - regret g…
cs.LG2019
Gated Linear Networks
Joel Veness, Tor Lattimore, David Budden +8
This paper presents a new family of backpropagation-free neural architectures, Gated Linear Networks (GLNs). What distinguishes GLNs from contemporary neural networks is the distri…
cs.LG2017★ 18 cited
Online Learning with Gated Linear Networks
Joel Veness, Tor Lattimore, Avishkar Bhoopchand +3
This paper describes a family of probabilistic architectures designed for online learning under the logarithmic loss. Rather than relying on non-linear transfer functions, our meth…