#averaging — Public Fediverse posts

NCAA men’s basketball transfer tracker: Players from Indiana in portal https://www.rawchili.com/nba/683134/ #averaging #Basketball #CollegeBasketball #IdahoState #Indiana #IuIndy #JaxonEdwards #LukeAlmodovar #MicahDavis #MissouriValleyConference #MurrayState #ncaa #NCAABasketball #ncaab #SoutheastMissouriState #TransferPortal #ValleyConference

#NotNews24 | #UnbreaklingMichaelFassbenderFlightSimulatorNotNews; #IT's #DefinitelyNotNews... #IT's #FunTimeFriday...!

#MichaelFassbenderFlightSimulator is #Running #ALittleBitWarm... #Averaging around #60 - #80 #FramesPerSecond, with #TheOccassionalSpike at #420+ #FPS...

But, #IT's #StillVerySmooth...

We can #AlsoPlay: #SquirrelSimulator with #FancyHats...

#IT should #LookQuiteNice on #MyLittleBigBuddy's #NewToyJoy #Once #IT's #Installed in #AllITs #UltraHD #4KFormat #Gorgeousness...

#BTW: #TheOmen is #Still: #SuperCool; there was a #Prophecy... 🔮

🧙🛫🤖:wolfparty:🤖🛬🧙 | :fediverse:​🦹🚁🦄🚁🦹:fediverse:

#BeingEuropean #StayingEuropean #BeingLegal #TotallyLegal #CyborgOrangeJesusLovesYou

📚🤖 Ah, the fine art of #averaging in Prolog! Because why use a calculator when you can write a dissertation just to sum a list? 🎓🧠 Prolog: the language for those who enjoy torturing themselves with recursive gymnastics instead of solving real problems. 🚀💥
https://storytotell.org/how-to-average-in-prolog #Prolog #RecursiveGymnastics #TechHumor #ProgrammingDissertation #CodingChallenges #HackerNews #ngated

'Stability and L2-penalty in Model Averaging', by Hengkun Zhu, Guohua Zou.

http://jmlr.org/papers/v25/23-0853.html

#averaging #estimators #models

'Stability and L2-penalty in Model Averaging', by Hengkun Zhu, Guohua Zou.

http://jmlr.org/papers/v25/23-0853.html

#averaging #estimators #models

'Stability and L2-penalty in Model Averaging', by Hengkun Zhu, Guohua Zou.

http://jmlr.org/papers/v25/23-0853.html

#averaging #estimators #models

'Stability and L2-penalty in Model Averaging', by Hengkun Zhu, Guohua Zou.

http://jmlr.org/papers/v25/23-0853.html

#averaging #estimators #models

'Stability and L2-penalty in Model Averaging', by Hengkun Zhu, Guohua Zou.

http://jmlr.org/papers/v25/23-0853.html

#averaging #estimators #models

'Iterate Averaging in the Quest for Best Test Error', by Diego Granziol, Nicholas P. Baskerville, Xingchen Wan, Samuel Albanie, Stephen Roberts.

http://jmlr.org/papers/v25/21-1125.html

#iterate #iterates #averaging

In our second session of the day, we heard from Jørn Hafver who trained an AI in audio recognition right in front of us - so it could tell how loud we were clapping at the end. Ben Ashforth spoke about a journey he went on, inspired by a talk from the last gathering, to visit roads named after every day of the year (details at http://benguin.co.uk/roads). @alisonkiddle talked about the maths behind the games Guess Who and Which One Doesn't Belong, and has a pleasing binary chop device made from card with pins and holes. Phil Ramsen followed up on his talk from three years ago and discussed slide rules and Kolmogorov. Daniel Johnson explored the possibly surprising link between Numberblocks and Polyominoes (https://youtu.be/htnZGHjX8p4?si=YzAXxPP7lT2-_Do5&t=522)- and @Tarim said what we've all been thinking and pointed out some illogical song lyrics - lions don't really live in the mighty jungle, and Kilimanjaro is nowhere near the Serengeti! #mathsjam #maths #ai #travelling #guesswho #wwdb #sliderules #means #averaging #kolmogorov #numberblocks #polyominoes #songs #logic #lyrics

In our second session of the day, we heard from Jørn Hafver who trained an AI in audio recognition right in front of us - so it could tell how loud we were clapping at the end. Ben Ashforth spoke about a journey he went on, inspired by a talk from the last gathering, to visit roads named after every day of the year (details at http://benguin.co.uk/roads). @alisonkiddle talked about the maths behind the games Guess Who and Which One Doesn't Belong, and has a pleasing binary chop device made from card with pins and holes. Phil Ramsen followed up on his talk from three years ago and discussed slide rules and Kolmogorov. Daniel Johnson explored the possibly surprising link between Numberblocks and Polyominoes (https://youtu.be/htnZGHjX8p4?si=YzAXxPP7lT2-_Do5&t=522)- and @Tarim said what we've all been thinking and pointed out some illogical song lyrics - lions don't really live in the mighty jungle, and Kilimanjaro is nowhere near the Serengeti! #mathsjam #maths #ai #travelling #guesswho #wwdb #sliderules #means #averaging #kolmogorov #numberblocks #polyominoes #songs #logic #lyrics

In our second session of the day, we heard from Jørn Hafver who trained an AI in audio recognition right in front of us - so it could tell how loud we were clapping at the end. Ben Ashforth spoke about a journey he went on, inspired by a talk from the last gathering, to visit roads named after every day of the year (details at http://benguin.co.uk/roads). @alisonkiddle talked about the maths behind the games Guess Who and Which One Doesn't Belong, and has a pleasing binary chop device made from card with pins and holes. Phil Ramsen followed up on his talk from three years ago and discussed slide rules and Kolmogorov. Daniel Johnson explored the possibly surprising link between Numberblocks and Polyominoes (https://youtu.be/htnZGHjX8p4?si=YzAXxPP7lT2-_Do5&t=522)- and @Tarim said what we've all been thinking and pointed out some illogical song lyrics - lions don't really live in the mighty jungle, and Kilimanjaro is nowhere near the Serengeti! #mathsjam #maths #ai #travelling #guesswho #wwdb #sliderules #means #averaging #kolmogorov #numberblocks #polyominoes #songs #logic #lyrics

In our second session of the day, we heard from Jørn Hafver who trained an AI in audio recognition right in front of us - so it could tell how loud we were clapping at the end. Ben Ashforth spoke about a journey he went on, inspired by a talk from the last gathering, to visit roads named after every day of the year (details at http://benguin.co.uk/roads). @alisonkiddle talked about the maths behind the games Guess Who and Which One Doesn't Belong, and has a pleasing binary chop device made from card with pins and holes. Phil Ramsen followed up on his talk from three years ago and discussed slide rules and Kolmogorov. Daniel Johnson explored the possibly surprising link between Numberblocks and Polyominoes (https://youtu.be/htnZGHjX8p4?si=YzAXxPP7lT2-_Do5&t=522)- and @Tarim said what we've all been thinking and pointed out some illogical song lyrics - lions don't really live in the mighty jungle, and Kilimanjaro is nowhere near the Serengeti! #mathsjam #maths #ai #travelling #guesswho #wwdb #sliderules #means #averaging #kolmogorov #numberblocks #polyominoes #songs #logic #lyrics

In our second session of the day, we heard from Jørn Hafver who trained an AI in audio recognition right in front of us - so it could tell how loud we were clapping at the end. Ben Ashforth spoke about a journey he went on, inspired by a talk from the last gathering, to visit roads named after every day of the year (details at http://benguin.co.uk/roads). @alisonkiddle talked about the maths behind the games Guess Who and Which One Doesn't Belong, and has a pleasing binary chop device made from card with pins and holes. Phil Ramsen followed up on his talk from three years ago and discussed slide rules and Kolmogorov. Daniel Johnson explored the possibly surprising link between Numberblocks and Polyominoes (https://youtu.be/htnZGHjX8p4?si=YzAXxPP7lT2-_Do5&t=522)- and @Tarim said what we've all been thinking and pointed out some illogical song lyrics - lions don't really live in the mighty jungle, and Kilimanjaro is nowhere near the Serengeti! #mathsjam #maths #ai #travelling #guesswho #wwdb #sliderules #means #averaging #kolmogorov #numberblocks #polyominoes #songs #logic #lyrics

'Least Squares Model Averaging for Distributed Data', by Haili Zhang, Zhaobo Liu, Guohua Zou.

http://jmlr.org/papers/v24/22-0511.html

#averaging #models #distributed

'Online Mirror Descent and Dual Averaging: Keeping Pace in the Dynamic Case', by Huang Fang, Nicholas J. A. Harvey, Victor S. Portella, Michael P. Friedlander.

http://jmlr.org/papers/v23/21-1027.html

#optimization #convex #averaging

#Kurtosis was an important #parameter differentiating #size distributions, with #platykurtic distributions in #marls and #leptokurtic distributions in #limestones, suggesting that this parameter may reflect different degrees of #time #averaging. Most size #distributions were positively #skewed, but most strongly in marls. Complete #sampling led to #skewness values close to zero (#symmetrical distributions) and high kurtosis.

https://doi.org/10.2110/palo.2021.063

#Kurtosis was an important #parameter differentiating #size distributions, with #platykurtic distributions in #marls and #leptokurtic distributions in #limestones, suggesting that this parameter may reflect different degrees of #time #averaging. Most size #distributions were positively #skewed, but most strongly in marls. Complete #sampling led to #skewness values close to zero (#symmetrical distributions) and high kurtosis.

https://doi.org/10.2110/palo.2021.063

#Kurtosis was an important #parameter differentiating #size distributions, with #platykurtic distributions in #marls and #leptokurtic distributions in #limestones, suggesting that this parameter may reflect different degrees of #time #averaging. Most size #distributions were positively #skewed, but most strongly in marls. Complete #sampling led to #skewness values close to zero (#symmetrical distributions) and high kurtosis.

https://doi.org/10.2110/palo.2021.063

#Kurtosis was an important #parameter differentiating #size distributions, with #platykurtic distributions in #marls and #leptokurtic distributions in #limestones, suggesting that this parameter may reflect different degrees of #time #averaging. Most size #distributions were positively #skewed, but most strongly in marls. Complete #sampling led to #skewness values close to zero (#symmetrical distributions) and high kurtosis.

https://doi.org/10.2110/palo.2021.063

#Kurtosis was an important #parameter differentiating #size distributions, with #platykurtic distributions in #marls and #leptokurtic distributions in #limestones, suggesting that this parameter may reflect different degrees of #time #averaging. Most size #distributions were positively #skewed, but most strongly in marls. Complete #sampling led to #skewness values close to zero (#symmetrical distributions) and high kurtosis.

https://doi.org/10.2110/palo.2021.063