Tootfinder

An efficient construction of Raz's two-source randomness extractor with improved parameters
Cameron Foreman, Lewis Wooltorton, Kevin Milner, Florian J. Curchod
https://arxiv.org/abs/2506.15547

An efficient construction of Raz's two-source randomness extractor with improved parameters
Randomness extractors are algorithms that distill weak random sources into near-perfect random numbers. Two-source extractors enable this distillation process by combining two independent weak random sources. Raz's extractor (STOC '05) was the first to achieve this in a setting where one source has linear min-entropy (i.e., proportional to its length), while the other has only logarithmic min-entropy in its length. However, Raz's original construction is impractical due to a polynomial computat…

Just spotted a random @… post on Imgur...
https://imgur.com/gallery/random-stolen-meme-dump-sunday-july-20-part-1-oWCgiWL#kyB6Kl…

Was für ein unterirdischer Artikel zu #Renten in Deutschland!
Welche Jahrgänge bekommen die niedrigsten Renten?
Richtig: schwer zu bestimmen.
Dann erklären sie richtig das jährliche Rentenniveau nur um dieses dann irgendwie in Relation mit der Eingangsfrage zu insinuieren? Die detaillierte Tabelle der Regelaltersgrenze ist dann aus Wikipedia kopiert und völlig irrelevant ist.…

Rente: Manche Jahrgänge sichern kaum ihren Lebensstandard
Die Rente reicht oft nicht aus, um den Lebensstandard im Alter zu sichern. Einige Jahrgänge erhalten sogar so wenig, dass die Existenz gefährdet ist.

Randomised composite linear-combination-of-unitaries: its role in quantum simulation and observable estimation
Jinzhao Sun, Pei Zeng
https://arxiv.org/abs/2506.15658

Randomised composite linear-combination-of-unitaries: its role in quantum simulation and observable estimation
Randomisation is widely used in quantum algorithms to reduce the number of quantum gates and ancillary qubits required. A range of randomised algorithms, including eigenstate property estimation by spectral filters, Hamiltonian simulation, and perturbative quantum simulation, though motivated and designed for different applications, share common features in the use of unitary decomposition and Hadamard-test-based implementation. In this work, we start by analysing the role of randomised linear-…

The speed of biased random walks among dynamical random conductances
Eszter Couillard
https://arxiv.org/abs/2508.13664 https://arxiv.org/pdf/2508.13664

The speed of biased random walks among dynamical random conductances
We study biased random walks on dynamical random conductances on $\mathbb{Z}^d$. We analyze three models: the Variable Speed Biased Random Walk (VBRW), the Normalized VBRW (NVBRW), and the Constant Speed Biased Random Walk (CBRW). We prove positivity of the linear speed for all models and investigate how the speed depends on the bias $λ$. Notably, while the CBRW speed increases for large $λ$, the NVBRW speed can asymptotically decrease even in uniformly elliptic conductances. The results for …

Revisiting Randomization in Greedy Model Search
Xin Chen, Jason M. Klusowski, Yan Shuo Tan, Chang Yu
https://arxiv.org/abs/2506.15643 https://

Revisiting Randomization in Greedy Model Search
Combining randomized estimators in an ensemble, such as via random forests, has become a fundamental technique in modern data science, but can be computationally expensive. Furthermore, the mechanism by which this improves predictive performance is poorly understood. We address these issues in the context of sparse linear regression by proposing and analyzing an ensemble of greedy forward selection estimators that are randomized by feature subsampling -- at each iteration, the best feature is s…

AI at the World’s Biggest Games Event Booked Random Meetings for Attendees https://www.404media.co/ai-at-the-worlds-biggest-games-event-booked-random-meetings-for-attendees/

The Search
Season 4 Episode 1 "Race Against Time: part 1"
#RandomBaywatch #lvdlpx #Baywatch

Generalisation and benign over-fitting for linear regression onto random functional covariates
Andrew Jones, Nick Whiteley
https://arxiv.org/abs/2508.13895 https://

Generalisation and benign over-fitting for linear regression onto random functional covariates
We study theoretical predictive performance of ridge and ridge-less least-squares regression when covariate vectors arise from evaluating $p$ random, means-square continuous functions over a latent metric space at $n$ random and unobserved locations, subject to additive noise. This leads us away from the standard assumption of i.i.d. data to a setting in which the $n$ covariate vectors are exchangeable but not independent in general. Under an assumption of independence across dimensions, $4$-th…

DC National Guard Is Being Trained to Carry Pistols Known to Fire at Random https://www.404media.co/dc-national-guard-is-being-trained-to-carrying-pistols-known-to-fire-at-random/