Tootfinder

New pre-print! #ai
**Universal pre-training by iterated random computation.**
⌨️🐒 A monkey behind a typewriter will produce the collected works of Shakespeare eventually.
💻🐒 But what if we put a monkey behind a computer?
⌨️🐒 needs to be lucky enough to type all characters of all of Shakespeare correctly. 💻🐒 only needs to be lucky enough to type a program for Shakespeare.

Universal pre-training by iterated random computation
We investigate the use of randomly generated data for the sake of pre-training a model. We justify this approach theoretically from the perspective of algorithmic complexity, building on recent research that shows that sequence models can be trained to approximate Solomonoff induction. We derive similar, but complementary theoretical results. We show empirically that synthetically generated data can be used to pre-train a model before the data is seen. We replicate earlier results that models t…

Learning graphons from data: Random walks, transfer operators, and spectral clustering
Stefan Klus, Jason J. Bramburger
https://arxiv.org/abs/2507.18147 https://

Learning graphons from data: Random walks, transfer operators, and spectral clustering
Many signals evolve in time as a stochastic process, randomly switching between states over discretely sampled time points. Here we make an explicit link between the underlying stochastic process of a signal that can take on a bounded continuum of values and a random walk process on a graphon. Graphons are infinite-dimensional objects that represent the limit of convergent sequences of graphs whose size tends to infinity. We introduce transfer operators, such as the Koopman and Perron--Frobeniu…

🇺🇦 #NowPlaying on KEXP's #DriveTime
Kevin Morby:
🎵 A Random Act of Kindness
#KevinMorby
https://kevinmorby.bandcamp.com/track/a-random-act-of-kindness
https://open.spotify.com/track/5GepgBdAV6eI3RoijuHZua

Large-scale entity resolution via microclustering Ewens--Pitman random partitions
Mario Beraha, Stefano Favaro
https://arxiv.org/abs/2507.18101 https://arx…

Large-scale entity resolution via microclustering Ewens--Pitman random partitions
We introduce the microclustering Ewens--Pitman model for random partitions, obtained by scaling the strength parameter of the Ewens--Pitman model linearly with the sample size. The resulting random partition is shown to have the microclustering property, namely: the size of the largest cluster grows sub-linearly with the sample size, while the number of clusters grows linearly. By leveraging the interplay between the Ewens--Pitman random partition with the Pitman--Yor process, we develop effici…

#DavidHasselhoff
Season 2 Episode 5 "The Fabulous Buchannon Boys"
#RandomBaywatch #lvdlpx

Smooth linearization of contractive random dynamical systems in continuous time
Iryna Vasylieva
https://arxiv.org/abs/2506.19034 https://

Smooth linearization of contractive random dynamical systems in continuous time
We establish that uniformly exponentially stable random dynamical systems on the half line have equivalent dynamics through a $C^m-$ conjugacy. This result was obtained for random differential equations as well as for random dynamical systems with a uniformly exponentially stable linear part.

#KristaAllen is very beautiful
S11E12 "The Ex-Files"
#BaywatchHawaii #RandomBaywatch

#EddieCibrian #DavidHasselhoff
Baywatch Nights 2x01 - Terror of the Deep
#RandomBaywatch #lvdlpx

#BillyWarlock #ErikaEleniak

Season 2 Episode 15 "Sea of Flames"
#RandomBaywatch

*A lot* of talking in this episode. It's boring.
#BillyWarlock #ErikaEleniak
Season 2 Episode 22 "Summer of '85"
#RandomBaywatch