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Found 7 papers, 2 papers with code
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels
We present a new kernel that allows for Gaussian process regression in $O((n+m)\log(n+m))$ time.
Intelligence and Unambitiousness Using Algorithmic Information Theory
Algorithmic Information Theory has inspired intractable constructions of general intelligence (AGI), and undiscovered tractable approximations are likely feasible.
Fully General Online Imitation Learning
If we run an imitator, we probably want events to unfold similarly to the way they would have if the demonstrator had been acting the whole time.
Pessimism About Unknown Unknowns Inspires Conservatism
Our other main contribution is that the agent's policy's value approaches at least that of the mentor, while the probability of deferring to the mentor goes to 0.
Curiosity Killed or Incapacitated the Cat and the Asymptotically Optimal Agent
Much work in reinforcement learning uses an ergodicity assumption to avoid this problem.
Asymptotically Unambitious Artificial General Intelligence
General intelligence, the ability to solve arbitrary solvable problems, is supposed by many to be artificially constructible.
A Strongly Asymptotically Optimal Agent in General Environments
This is known as strong asymptotic optimality, and it was previously unknown whether it was possible for a policy to be strongly asymptotically optimal in the class of all computable probabilistic environments.
