No exact results. Similar results found.

@arXiv_eessSP_bot@mastoxiv.page

2024-04-18 06:54:21

2024-04-18 06:54:21

Robust and tractable multidimensional exponential analysis

H. N. Mhaskar, S. Kitimoon, Raghu G. Raj

https://arxiv.org/abs/2404.11004 https://

A square root algorithm faster than Newton's method for multiprecision numbers, using floating-point arithmetic

Fabio Romano

https://arxiv.org/abs/2406.07751

@arXiv_csRO_bot@mastoxiv.page

2024-06-12 07:28:22

2024-06-12 07:28:22

Developing, Analyzing, and Evaluating Vehicular Lane Keeping Algorithms Under Dynamic Lighting and Weather Conditions Using Electric Vehicles

Michael Khalfin, Jack Volgren, Matthew Jones, Luke LeGoullon, Joshua Siegel, Chan-Jin Chung

https://arxiv.org/abs/2406.06899

@cheeaun@mastodon.social

2024-06-07 15:53:07

2024-06-07 15:53:07

The "Catch up on this thread" notifications on #Threads are pretty annoying.

It seems trying to notify you a post from a following that you missed, buried under the chronological Following timeline but not going to be resurfaced by the algorithm in the 'For You' timeline 🤔

@kernellogger@fosstodon.org

2024-04-27 06:08:10

2024-04-27 06:08:10

How Allegro reduced latency outliers by 82% by switching to #XFS:

https://blog.allegro.tech/2024/03/kafka-performance-analysis.html

"'Using a com…

@arXiv_csCV_bot@mastoxiv.page

2024-05-10 08:29:58

2024-05-10 08:29:58

This https://arxiv.org/abs/2405.03352 has been replaced.

initial toot: https://mastoxiv.page/@arXiv_csCV_…

@j12t@social.coop

2024-05-03 22:21:46

2024-05-03 22:21:46

Opaque algorithms are a funny thing.

Over on #Threads, my "Following" feed does consistently have more things in it that are interesting to me than my "For you" feed.

I've been observing this for a few weeks now, and it's consistent.

Seem the cost function might be optimizing for something other than what I like? Or is the signal not good enough because …

@arXiv_csDC_bot@mastoxiv.page

2024-05-09 06:52:34

2024-05-09 06:52:34

Probabilistic Byzantine Fault Tolerance (Extended Version)

Diogo Avel\~as, Hasan Heydari, Eduardo Alchieri, Tobias Distler, Alysson Bessani

https://arxiv.org/abs/2405.04606

@arXiv_csDS_bot@mastoxiv.page

2024-04-30 07:20:33

2024-04-30 07:20:33

Private graph colouring with limited defectiveness

Aleksander B. G. Christiansen, Eva Rotenberg, Teresa Anna Steiner, Juliette Vlieghe

https://arxiv.org/abs/2404.18692 https://arxiv.org/pdf/2404.18692

arXiv:2404.18692v1 Announce Type: new

Abstract: Differential privacy is the gold standard in the problem of privacy preserving data analysis, which is crucial in a wide range of disciplines. Vertex colouring is one of the most fundamental questions about a graph. In this paper, we study the vertex colouring problem in the differentially private setting.

To be edge-differentially private, a colouring algorithm needs to be defective: a colouring is d-defective if a vertex can share a colour with at most d of its neighbours. Without defectiveness, the only differentially private colouring algorithm needs to assign n different colours to the n different vertices. We show the following lower bound for the defectiveness: a differentially private c-edge colouring algorithm of a graph of maximum degree {\Delta} > 0 has defectiveness at least d = {\Omega} (log n / (log c log {\Delta})).

We also present an {\epsilon}-differentially private algorithm to {\Theta} ( {\Delta} / log n 1 / {\epsilon})-colour a graph with defectiveness at most {\Theta}(log n).

@j12t@social.coop

2024-04-30 03:14:53

2024-04-30 03:14:53

Whittled down the list of people I’m following. With no algorithm in the fediverse that shows me what it thinks I should be interested in, I better pick myself how I fill my feed.