Tootfinder

Seit Jahren erklären mir Menschen, warum sie nicht Linke wählen können. Manche sind schlicht rechts, manche eher mittig, die (sich?) das aber nicht recht eingestehen wollen, und manche hätten sehr gern eine *andere* Linke.
Ich persönlich glaube, dass Parteien nicht glücklich machen. Die sind immer ein großer Kompromiss, da stimmt immer viel nicht. Es hilft, das zu verstehen.
Wählen ist *immer* die Frage nach dem geringsten Übel.
Und für den Rest: Engagiert Euch. Für das, wa…

Ich höre gerade den @…
#Dresden: 5 Straßen, 5 Ideen
Thema u.a. die #AugsburgerStraße.
Da ic…

5 Straßen, 5 Ideen - Piratencast #61 - Piraten Dresden
Anne, Steve, Manu und Stephanie sprechen über Verkehrspolitik und verschiedene Straßen im Dresdner Stadtgebiet.

Es ist eines der größten Gebäude der Stadt: Die [ehemalige] „Agentur für Arbeit“, unterhalb des in einen Kulturstandort umgewandelten Hauptbahnhofs an der Joseph-Beuys-Str., benannt nach dem völkisch und anthroposophisch orientierten Künstler. Von Westen wirkt das massive mehrgeschossige Gebäude wie hinter einem kleinen mysteriösen Wald versteckt. Der Blick geht über die Brache, die [nun] vom Fraunhofer-Institut bebaut [ist]? Seit der „Agenda 2010“,

Im #Saarland will das #BSW auf kommunaler Ebene mit den Nazis zusammenarbeiten. Im #Bundestag hat man das ja heute schon mal geprobt.
Nach der Wahl fallen die Masken. Das Bündnis Sahra

Practical Boolean Decomposition for Delay-driven LUT Mapping
Alessandro Tempia Calvino, Alan Mishchenko, Giovanni De Micheli, Robert Brayton
https://arxiv.org/abs/2406.06241

Practical Boolean Decomposition for Delay-driven LUT Mapping
Ashenhurst-Curtis decomposition (ACD) is a decomposition technique used, in particular, to map combinational logic into lookup tables (LUTs) structures when synthesizing hardware designs. However, available implementations of ACD suffer from excessive complexity, search-space restrictions, and slow run time, which limit their applicability and scalability. This paper presents a novel fast and versatile technique of ACD suitable for delay optimization. We use this new formulation to compute two-…

This https://arxiv.org/abs/2405.13653 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Downlink Power Control based UE-Sided Initial Access for Tactical 5G NR
Communication technologies play a crucial role in battlefields. They are an inalienable part of any tactical response, whether at the battlefront or inland. Such scenarios require that the communication technologies be versatile, scalable, cost-effective, and stealthy. While multiple studies and past products have tried to address these requirements, none of them have been able to solve all the four challenges simultaneously. Hence, in this paper, we propose a tactical solution that is based on…

Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints
T. Tony Cai, Abhinav Chakraborty, Lasse Vuursteen
https://arxiv.org/abs/2406.06755

Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints
This paper studies federated learning for nonparametric regression in the context of distributed samples across different servers, each adhering to distinct differential privacy constraints. The setting we consider is heterogeneous, encompassing both varying sample sizes and differential privacy constraints across servers. Within this framework, both global and pointwise estimation are considered, and optimal rates of convergence over the Besov spaces are established. Distributed privacy-pres…

Practical Boolean Decomposition for Delay-driven LUT Mapping
Alessandro Tempia Calvino, Alan Mishchenko, Giovanni De Micheli, Robert Brayton
https://arxiv.org/abs/2406.06241

Practical Boolean Decomposition for Delay-driven LUT Mapping
Ashenhurst-Curtis decomposition (ACD) is a decomposition technique used, in particular, to map combinational logic into lookup tables (LUTs) structures when synthesizing hardware designs. However, available implementations of ACD suffer from excessive complexity, search-space restrictions, and slow run time, which limit their applicability and scalability. This paper presents a novel fast and versatile technique of ACD suitable for delay optimization. We use this new formulation to compute two-…

Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests
T. Tony Cai, Abhinav Chakraborty, Lasse Vuursteen
https://arxiv.org/abs/2406.06749

Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests
Federated learning has attracted significant recent attention due to its applicability across a wide range of settings where data is collected and analyzed across disparate locations. In this paper, we study federated nonparametric goodness-of-fit testing in the white-noise-with-drift model under distributed differential privacy (DP) constraints. We first establish matching lower and upper bounds, up to a logarithmic factor, on the minimax separation rate. This optimal rate serves as a benchm…

Another successful rave at the... toilet?
Last night's Club Toilet rave was amazing, as always! I woke up specifically for it, danced for a bit, and then went back to bed. Could've been a dream if I didn't have any pics of it :neofox_think_googly:
I wasn't expecting about 40 people inside the damn toilet, but I especially wasn't expecting Valant as the DJ! The set was full of bangers.