4 citations · 7 across the 3 of their papers we have counts for
5 papers
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels
Michael K. Cohen, Samuel Daulton, Michael A. Osborne
Gaussian processes (GPs) produce good probabilistic models of functions, but most GP kernels require time, where is the number of data points and the number o…
Fully General Online Imitation Learning
Michael K. Cohen, Marcus Hutter, Neel Nanda
In imitation learning, imitators and demonstrators are policies for picking actions given past interactions with the environment. If we run an imitator, we probably want events to…
Pessimism About Unknown Unknowns Inspires Conservatism
Michael K. Cohen, Marcus Hutter
If we could define the set of all bad outcomes, we could hard-code an agent which avoids them; however, in sufficiently complex environments, this is infeasible. We do not know of…
Asymptotically Unambitious Artificial General Intelligence
Michael K Cohen, Badri Vellambi, Marcus Hutter
General intelligence, the ability to solve arbitrary solvable problems, is supposed by many to be artificially constructible. Narrow intelligence, the ability to solve a given part…
A Strongly Asymptotically Optimal Agent in General Environments
Michael K. Cohen, Elliot Catt, Marcus Hutter
Reinforcement Learning agents are expected to eventually perform well. Typically, this takes the form of a guarantee about the asymptotic behavior of an algorithm given some assump…