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sigopt
sigopt-examples
Jupyter Notebook2015–2017
sigopt / sigopt-examples · Archived

sigopt-examples

Optimization Examples with SigOpt

Science & Engineering
Explore on GitHubRead Hacker News discussions
3Distinct people
13Mentions
0Explicit recommenders
199GitHub stars
REPOSITORY AT A GLANCE

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What it is

Optimization Examples with SigOpt

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 2:59:53 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month13 dated mentions

Observed mentions: 2015-12-31 19:25:04 UTC to 2017-08-09 01:07:47 UTC.

01232015-12-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 commentsDec 20152016-01-01 00:00:00 UTC to 2016-02-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2016-02-01 00:00:00 UTC to 2016-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-03-01 00:00:00 UTC to 2016-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-04-01 00:00:00 UTC to 2016-05-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2016-05-01 00:00:00 UTC to 2016-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-06-01 00:00:00 UTC to 2016-07-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-07-01 00:00:00 UTC to 2016-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-01 00:00:00 UTC to 2016-09-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2016-09-01 00:00:00 UTC to 2016-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-10-01 00:00:00 UTC to 2016-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsOct 20162016-11-01 00:00:00 UTC to 2016-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-12-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2017-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-02-01 00:00:00 UTC to 2017-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-03-01 00:00:00 UTC to 2017-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-04-01 00:00:00 UTC to 2017-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-05-01 00:00:00 UTC to 2017-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2017-06-01 00:00:00 UTC to 2017-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-07-01 00:00:00 UTC to 2017-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-08-01 00:00:00 UTC to 2017-09-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsAug 2017

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Dec 20152015-12-01 00:00:00 UTC2016-01-01 00:00:00 UTC202
Jan 20162016-01-01 00:00:00 UTC2016-02-01 00:00:00 UTC303
Feb 20162016-02-01 00:00:00 UTC2016-03-01 00:00:00 UTC000
Mar 20162016-03-01 00:00:00 UTC2016-04-01 00:00:00 UTC101
Apr 20162016-04-01 00:00:00 UTC2016-05-01 00:00:00 UTC110
May 20162016-05-01 00:00:00 UTC2016-06-01 00:00:00 UTC000
Jun 20162016-06-01 00:00:00 UTC2016-07-01 00:00:00 UTC101
Jul 20162016-07-01 00:00:00 UTC2016-08-01 00:00:00 UTC000
Aug 20162016-08-01 00:00:00 UTC2016-09-01 00:00:00 UTC303
Sep 20162016-09-01 00:00:00 UTC2016-10-01 00:00:00 UTC000
Oct 20162016-10-01 00:00:00 UTC2016-11-01 00:00:00 UTC000
Nov 20162016-11-01 00:00:00 UTC2016-12-01 00:00:00 UTC000
Dec 20162016-12-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
Jan 20172017-01-01 00:00:00 UTC2017-02-01 00:00:00 UTC000
Feb 20172017-02-01 00:00:00 UTC2017-03-01 00:00:00 UTC000
Mar 20172017-03-01 00:00:00 UTC2017-04-01 00:00:00 UTC000
Apr 20172017-04-01 00:00:00 UTC2017-05-01 00:00:00 UTC000
May 20172017-05-01 00:00:00 UTC2017-06-01 00:00:00 UTC101
Jun 20172017-06-01 00:00:00 UTC2017-07-01 00:00:00 UTC000
Jul 20172017-07-01 00:00:00 UTC2017-08-01 00:00:00 UTC000
Aug 20172017-08-01 00:00:00 UTC2017-09-01 00:00:00 UTC101

What Hacker News says

2 sources
Zephyr314·Dec 31, 2015
Thanks! Great question. There is a huge variance in the cumulative gains as you pointed out. Because of the 100 win/110 loss edge that Vegas has you need to win over 52.5% of the time to register a profit. Even with a model that can win 52.5% + e of the time you are effectively flipping a (biased) coin. Over the 131 games in the holdout dataset this random walk will tend upward, but can vary widely (especially at the start). As the season continues on this should start to wash out (in the cumulative profit). We plan to write a followup post at the end of the season to see how it performs. You could also fork the code [1] and train/tune on '00-'13/'13-'14 and use the entire '14-'15 set as the holdout (or a similar combination). The features can be found here [2], we don't use individual player stats or temporal stats, but it should be rela
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tively easy to add if you wanted to try it out. [1]: https://github.com/sigopt/sigopt-examples [2]: https://github.com/sigopt/sigopt-examples/blob/master/sigopt...
In Using Model Tuning to Beat Vegas

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