Language, Usage and Cognition - April 2010

Eher zufällig hütete Rainer Groß in den 70ern für eine Woche das VfL-Tor. Für Volkswagen schaute er unter die Motorhauben der Konkurrenz.

Learn how to create an asynchronous web app using warp and tokio-postgres and build a database-backed CRUD service with error handling in Rust.

The ability to follow gaze (i.e. head and eye direction) has recently been shown for social mammals, particularly primates. In most studies, individuals could use gaze direction as a behavioural cue without understanding that the view of others may be ...

DUV Ultramarathon-Statistik

DUV Ultramarathon-Statistik

The ability of machines to make truly independent and autonomous decisions is a goal of many, not least of military leaders who wish to take the human out of the loop as much as possible, claiming ...

Background— A role for myeloperoxidase (MPO) as a mediator of coronary artery disease and acute coronary syndromes has recently received considerable attention. Although active MPO and hypochlorite-m

65 votes and 40 comments so far on Reddit

Workshop in advances and future research in secure federated machine learning for the application in the health inforamatics domain

ERCIM News, the quarterly magazine of the European Research Consortium for Informatics and Mathematics

The Security Forum of the Hagenberger Kreis 2017 at the FH Hagenberg is again a great success. More than 200 participants inform themselves about the latest trends, threats and dangers of IT security during the two days. SEC4YOU is represented at the Security Forum 2017 with an

Important text examines most significant algorithms for optimizing large systems and clarifying relations between optimization procedures. Much data appear as charts and graphs and will be highly valuable to readers in selecting a method and estimating computer time and cost in problem-solving. Initial chapter on linear and nonlinear programming presents all necessary background for subjects covered in rest of book. Second chapter illustrates how large-scale mathematical programs arise from real-world problems. Appendixes. List of Symbols.

11/02/22 - Data augmentation is a critical contributing factor to the success of deep learning but heavily relies on prior domain knowledge w...

Elon Musk explains that we need a (revenue-neural) carbon tax in order to avoid a climate crisis. To see the full speech klick here: https://www.youtube.com/watch?v=iavquu6PP9g

This paper presents a comparison study between native code and different browser-based implementations: JavaScript, ASM.js as well as WebAssembly on a representative mix of algorithms, showing that current efforts in runtime optimization push the boundaries well towards (and even beyond) native binary performance. AI applications pose increasing demands on performance, so it is not surprising that the era of client-side distributed software is becoming important. On top of many AI applications already using mobile hardware, and even browsers for computationally demanding AI applications, we are already witnessing the emergence of client-side (federated) machine learning algorithms, driven by the interests of large corporations and startups alike. Apart from mathematical and algorithmic concerns, this trend especially demands new levels of computational efficiency from client environments. Consequently, this paper deals with the question of state-of-the-art performance by presenting a comparison study between native code and different browser-based implementations: JavaScript, ASM.js as well as WebAssembly on a representative mix of algorithms. Our results show that current efforts in runtime optimization push the boundaries well towards (and even beyond) native binary performance. We analyze the results obtained and speculate on the reasons behind some surprises, rounding the paper off by outlining future possibilities as well as some of our own research efforts.

This paper presents a comparison study between native code and different browser-based implementations: JavaScript, ASM.js as well as WebAssembly on a representative mix of algorithms, showing that current efforts in runtime optimization push the boundaries well towards (and even beyond) native binary performance. AI applications pose increasing demands on performance, so it is not surprising that the era of client-side distributed software is becoming important. On top of many AI applications already using mobile hardware, and even browsers for computationally demanding AI applications, we are already witnessing the emergence of client-side (federated) machine learning algorithms, driven by the interests of large corporations and startups alike. Apart from mathematical and algorithmic concerns, this trend especially demands new levels of computational efficiency from client environments. Consequently, this paper deals with the question of state-of-the-art performance by presenting a comparison study between native code and different browser-based implementations: JavaScript, ASM.js as well as WebAssembly on a representative mix of algorithms. Our results show that current efforts in runtime optimization push the boundaries well towards (and even beyond) native binary performance. We analyze the results obtained and speculate on the reasons behind some surprises, rounding the paper off by outlining future possibilities as well as some of our own research efforts.

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