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Prikvačeni tweet
Hey look!
@cmoon6's and my post, "Decisions are First Class Citizens", is up on the@GrubhubTech blog!#ormshttps://bytes.grubhub.com/decisions-are-first-class-citizens-9994fd8fe802 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Yup. Because all other languages.https://twitter.com/hspter/status/1221901764972175360 …
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Yeah, that was ridiculous too. Somehow the TSP stuff seems worse to me.https://twitter.com/AustinLBuchanan/status/1221634028585078785 …
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Is the same attention to detail paid to stories on climate change? What about coronavirus? I don't know much about these things, and I'd like to have faith that what I read has been researched. This is as far as anyone has to go to find the state of the art in TSP solving. https://twitter.com/ryanjoneil/status/1221592366357729280 …pic.twitter.com/Lrq6OkyN1c
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What bugs me in these TSP articles: They're not just a little bit wrong. They're light years off from decades-old reality. Lots of MS students study TSP solving. These aren't the dark arts. If the news is so wrong about this, how can I believe articles about anything technical?
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And on and on. I forgot that
@washingtonpost and@nytimes got on the bandwagon for that one too. http://www.math.uwaterloo.ca/tsp/usa50/index.html … Surely someone at one of these establishments would like to correct the record?Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Any journos out there want to write a story correcting this rubbish?
@washingtonpost published an article just as bad a couple years back.@NPR did the same thing. It's gotten pretty shameful.https://twitter.com/JFPuget/status/1221402530623696901 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ryan J. O'Neil proslijedio/la je Tweet
2. Maybe better tooling for to reach more people without heavy experience on discrete algorithms. The solvers we use are always comparing each other in terms of constraints implemented and performance. How about usage? Time to setup a project? Documentation?
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Long live Integer Science! If I weren't too busy right now, I would totally apply.https://twitter.com/mluebbecke/status/1220289421834059781 …
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It gets worse when you consider online shoppers who don't own cars, request delivery, and purchase large boxes. "No, thanks, I just ordered 40 lbs of cat litter."
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From a consumer perspective, the state of recommendation systems often seems to be "you bought cat litter, would you like to buy more cat litter? Here are 15 other brands of cat litter."https://twitter.com/alexiskold/status/1218338211078033409 …
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To all the developers who struggle with naming things... You are not alone.
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I thought it was when you switched to fitness proportionate search, but neglected to hit the gym.https://twitter.com/marinaepelman/status/1216463659792326656 …
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Stumbling into the abyss, essentially.
https://twitter.com/JFPuget/status/1216446748828340226 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ryan J. O'Neil proslijedio/la je Tweet
I wonder if it is true that myopic is more used when talking about stochastic optimization. For instance, a myopic policy ignores future rewards and optimizes direct rewards. On the other hand, greedy is more used in classic combinatorial optimization (like Dijkstra) Not sure...
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Ryan J. O'Neil proslijedio/la je Tweet
that does contradict my def. If you check a textbook def, greedy needs the "local optimal" while myopic is just the opposite of "far sighted", well literally, or "not global", it is weaker than greedy. If both were the same, why would one proof properties for greedy algos?
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Interesting alternative view re: greedy vs myopic.https://twitter.com/claud10contardo/status/1216428696975835136 …
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Ryan J. O'Neil proslijedio/la je Tweet
That being said, to asnwer the question, I'd say that I use both terms interchangeably
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I hereby endorse this answer.https://twitter.com/mluebbecke/status/1216372158387118081 …
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Ryan J. O'Neil proslijedio/la je Tweet
I would use “greedy” when referring to a choice that neglects existing data (eg nearest neighbor tsp heuristic) and “myopic” for choices made before new information is released over time (eg maximizes today’s profit before seeing tomorrow’s demand data). Time aspect is key
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