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#algorithm

11 posts9 participants0 posts today

The program no longer crashes and the fix was simpler than I thought.

Instead of comparing rounded doubles (what a silly idea) I did the proper thing, which is abs(a - b) < epsilon. A lot of times 🙂 Takes maybe half second to generate the design. Then I can pan, zoom and rotate to find a screenshot I like.

I'm thinking that the lines that end in lonely places should end with a tiny knot. I may try that next.

New paper, just out.

Often, in real-world situations, one does not know the full structure of a network. However, at the same time, one can often observe some interactions that take place on it, and may be interested in knowing its full structure. For example, one may be detecting some partial criminal activity and may want to determine the whole organization. We consider higher-order networks, which are structures with many-body interactions, and specifically simplicial complexes, and show that one can reconstruct a whole network almost perfectly simply by observing the transient of the dynamics that takes place on it. In fact, we give 3 different algorithms to do it, with different complexities and accuracies, so you can choose which one suits you best.

Exclusive: how the Atlantic’s Jeffrey Goldberg got added to the White House Signal group chat

"According to the White House, the number was erroneously saved during a “contact #suggestion update” by Waltz’s iPhone, which one person described as the function where an iPhone #algorithm adds a previously unknown number to an existing contact that it detects may be related." 😂

theguardian.com/us-news/2025/a

The Guardian · Exclusive: how the Atlantic’s Jeffrey Goldberg got added to the White House Signal group chatBy Hugo Lowell

I 'boost' stuff I find interesting, or think needs more awareness, or is just damn funny.

I 'like' stuff to let the poster know I read it and appreciate/acknowledge/see the effort required to make the post. I may not agree with the sentiment but if it's in my locus of topics du jour I make an effort to acknowledge if relevant as an outlier.

Mastodon has no algorithms and I'm on a single user instance (i.e. just me!) so it is what it is - I guess. If you are offended by anything I post or respond to then let me know and we can talk about the topic.

#SocialNetworks that are fed by an #algorithm are causing much harm to you. Just one example of many: karl-voit.at/2024/07/13/social

Please do convince your friends and relatives to try out a healthy alternative like the #Fediverse here: karl-voit.at/2024/06/18/Fedive

When you visit your friends and family, tell them about not having #endlessscrolling or #doomscrolling. Tell them about being able to read unfiltered comments and articles. Tell them about not destroying your mental health all the time, following some #influencers that show a wrong picture of the world and the people.

Accounts on servers like graz.social are for free. (Donations welcomed: info.graz.social/spenden/ )

Have a happy weekend!

public voit - Web-page of Karl Voit · Social Networks Are Lying to Manipulate YouSocial Networks Are Lying to Manipulate You

I wrote a brief piece on how the Fediverse helped me discover new and unusual concepts that reignited my enthusiasm for writing through tech minimalism.

Kudos to @HailsandAles and @denis; without you, this could happen, but not this fast

arnel.bearblog.dev/writing-for

SharanWriting for HumansHow Fediverse made me discover strange new concepts that reignited my excitement for writing through tech minimalism
Replied to Killian Mangan🇮🇪

On top of banning all Recommender Systems on social media, we must change from being powerless users of Tech giant services into having democratic collective control of algorithms on all services we use!

Tech platform co-ops creating apps and services which users can democratically and collectively control 🙌

'Algorithms have the character of a sticky jelly that seeps into every nook and cranny, and once it hardens, it’s hard to peel off.

Learning to control algorithms will ensure that they do not end up controlling us: our clicks, our tastes, our individual and collective thoughts and imagination. “We want to democratize knowledge of these tools and open them up to the public.”'

english.elpais.com/society/202

EL PAÍS English · Why everything looks the same everywhereClosed online communities and platforms offer us an accessible, aspirational, and increasingly cloned universe. And, following the dictates of ‘likes,’ algorithms erase differences and identities and transform us into passive users. Are we losing our personality?

Karatsuba Matrix Multiplication and Its Efficient Hardware Implementations

arxiv.org/abs/2501.08889

arXiv logo
arXiv.orgKaratsuba Matrix Multiplication and its Efficient Custom Hardware ImplementationsWhile the Karatsuba algorithm reduces the complexity of large integer multiplication, the extra additions required minimize its benefits for smaller integers of more commonly-used bitwidths. In this work, we propose the extension of the scalar Karatsuba multiplication algorithm to matrix multiplication, showing how this maintains the reduction in multiplication complexity of the original Karatsuba algorithm while reducing the complexity of the extra additions. Furthermore, we propose new matrix multiplication hardware architectures for efficiently exploiting this extension of the Karatsuba algorithm in custom hardware. We show that the proposed algorithm and hardware architectures can provide real area or execution time improvements for integer matrix multiplication compared to scalar Karatsuba or conventional matrix multiplication algorithms, while also supporting implementation through proven systolic array and conventional multiplier architectures at the core. We provide a complexity analysis of the algorithm and architectures and evaluate the proposed designs both in isolation and in an end-to-end deep learning accelerator system compared to baseline designs and prior state-of-the-art works implemented on the same type of compute platform, demonstrating their ability to increase the performance-per-area of matrix multiplication hardware.

Researchers at Kaiser Permanente developed algorithm to reduce #bias in #multiplesclerosis treatment decisions, ensuring more equitable access to highly effective therapies. A study tracking over 6,000 #MS patients in Southern California found that after #algorithm was implemented, the use of highly effective therapies increased by 90 percent among Hispanic patients, 87 percent among Black patients, and 80 percent among white patients. #healthcare #bias #discrimination multiplesclerosisnewstoday.com

Multiple Sclerosis News Today · Algorithm may reduce racial, ethnic inequalities in MS treatmentA simple algorithm to recommend disease-modifying therapies may help reduce racial and ethnic inequalities in MS treatment, per a study.