Date: Thu, 14 May 2020 15:18:03 -0400
On Thu, May 14, 2020 at 9:51 AM Michael Wong <fraggamuffin_at_[hidden]> wrote:
> SG19 Machine Learning 2 hours
> Hi,
>
> Michael Wong is inviting you to a scheduled Zoom meeting.
>
> Hi,
>
> Michael Wong is inviting you to a scheduled Zoom meeting.
>
> Topic: SG19 monthly Apr 2020-Oct 2020
> Time: Apr 9, 2020 02:00 PM Eastern Time (US and Canada) 18:00 UTC
> Every month on the Second Thu, until Oct 8, 2020, 7 occurrence(s)
> Apr 9, 2020 02:00 PM 18:00 UTC
> May 14, 2020 02:00 PM 18:00 UTC
> Jun 11, 2020 02:00 PM 18:00 UTC
> Jul 9, 2020 02:00 PM 18:00 UTC
> Aug 13, 2020 02:00 PM 18:00 UTC
> Sep 10, 2020 02:00 PM 18:00 UTC
> Oct 8, 2020 02:00 PM 18:00 UTC
> Please download and import the following iCalendar (.ics) files to your
> calendar system.
> Monthly:
>
> https://iso.zoom.us/meeting/v50sceqopj4pyLdu5Mx1orYgnZZUj0RNqw/ics?icsToken=98tyKuuhrz0pGtyQs1-CArUqE53ibvG1kmhirrYIsQe0DDJqZQ3MDNdIYoBRAc-B
>
> Join from PC, Mac, Linux, iOS or Android:
> https://iso.zoom.us/j/291630853?pwd=WUlKbS9SNFNRa0QyWXRWenlGSDhaQT09
> Password: 339768
>
> Or iPhone one-tap :
> US: +14086380968,,291630853# or +16468769923,,291630853#
> Or Telephone:
> Dial(for higher quality, dial a number based on your current location):
> US: +1 408 638 0968 or +1 646 876 9923 or +1 669 900 6833 or +1
> 253 215 8782 or +1 301 715 8592 or +1 312 626 6799 or +1 346 248 7799
> or 877 853 5247 (Toll Free)
> Meeting ID: 291 630 853
> Password: 339768
> International numbers available: https://iso.zoom.us/u/abhaIjFKLZ
>
> Or Skype for Business (Lync):
> https://iso.zoom.us/skype/291630853
>
> Agenda:
>
> 1. Opening and introductions
>
> 1.1 Roll call of participants
>
Andrew Lumsdaine, Phil Ratzloff, luke D'alessandro, Marco Foco, Richard
Dosselmann, Scott McMillan, Michael Wong, Michael Chiu, Kevin Deweese
1.2 Adopt agenda
>
Approve
> 1.3 Approve minutes from previous meeting, and approve publishing
> previously approved minutes to ISOCPP.org
>
> 1.4 Action items from previous meetings
>
> 2. Main issues (125 min)
>
> 2.1 General logistics
>
> Meeting plan, focus on one paper per meeting but does not preclude other
> paper updates:
>
> Apr 9, 2020 02:00 PM: stats paper- DONE
> May 14, 2020 02:00 PM: Stats paper replaces Differential calculus
> Jun 11, 2020 02:00 PM: Graph paper
> Jul 9, 2020 02:00 PM: Stats paper
> Aug 13, 2020 02:00 PM: Differential calculus
> Sep 10, 2020 02:00 PM: Graph paper
> Oct 8, 2020 02:00 PM: stats paper
>
>
>
> all ISO meetings online untilend of Aug
>
monthly 15th is a deadline
2.2 Paper reviews
>
> 2.2.1: ML topics
>
> Richard Dosselman et al
>
> P1708R1: Math proposal for Machine Learning
>
> https://docs.google.com/document/d/1VAgcyvL1riMdGz7tQIT9eTtSSfV3CoCEMWKk8GvVuFY/edit
>
> > std.org/jtc1/sc22/wg21/docs/papers/2020/p1708r2
> > above is the stats paper that was reviewed in Prague
> > http://wiki.edg.com/bin/view/Wg21prague/P1708R2SG19
> >
> > Revie Jolanta Polish feedback.
> > http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2020/p2119r0.html
>
Freestanding, or accumulator object? Have done both
series of weight suggested by Michael C
moved to ranges projection as suggested by Jens M
this now looks more compact
latest versoin of python has geometric + harmonic mean following geometric
mean
now we can compact all calculation of avg down to 6 , now we are on par
with with python has
Yolanta's paper pointed out notion of trimmed mean, implies it is sorted
nice compromise so we don't have to take on the trimmed stats
Luke A: have you considered less strenous restriction of input range as
long as you already have forward range?
yes I can change that as I thought foward range was more restricted, I will
change that
PR: selection between population and sample, better to use enumeration
population vs sample? OK
MF: or do both for when you need to switch to a projection? OK so switch
order of projection and population
Quantile as a replacement for median, so you can ask for 0.25 instead of
strictly median
have a random_access_range for the sorted case to find the middle position
for mode we can customize with your own allocator, customize what it means
to be equal, makes use of output iterator so you can return multiple mode
LA: may want to commit all into ranges, so return mode as a range vs output
iterator (view, allowing take_n), so return all of them and not just first
strange that python decided to only return one
PhilR: i was advised too to use output iterator
LA: range's model is composability
PhilR: Also Macro to implementation
accumulator object was more difficult to get right
liek a vehicle that stops every mile, and accumulate it at every mile, user
just say they want mean or variance, then pass the mean to this function
then you can pull the stats out of these objects; idea is to fuse multipel
operations into a single path
so in the end you can do it all in one pass
also have sig variance for a weighted mean
LA: use forwardign references && vs & aggressively when dealing with ranges
Invite Yolanta, Walter, Eric, and Lisa for July meeting.
>
> Phil Ratsloff et al
>
> P1709R1: Graph Proposal for Machine Learning
>
>
> P1709R3:
>
> https://docs.google.com/document/d/1kLHhbSTX7j0tPeTYECQFSNx3R35Mu3xO5_dyYdRy4dM/edit?usp=sharing
>
>
>
> https://docs.google.com/document/d/1QkfDzGyfNQKs86y053M0YHOLP6frzhTJqzg1Ug_vkkE/edit?usp=sharing
> <
>
> https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdocs.google.com%2Fdocument%2Fd%2F1QkfDzGyfNQKs86y053M0YHOLP6frzhTJqzg1Ug_vkkE%2Fedit%3Fusp%3Dsharing&data=02%7C01%7CPhil.Ratzloff%40sas.com%7C729b2cf8502641e4ae5e08d749064578%7Cb1c14d5c362545b3a430
> 9552373a0c2f%7C0%7C0%7C637058163592253027&sdata=4UQm8tqrcUbiZsr200UMrOaEModJYGNgP1oNot9PbAg%3D&reserved=0>
>
> Differentiable Programing by Marco Foco
>
> P1416R1: SG19 - Linear Algebra for Data Science and Machine Learning
>
> https://docs.google.com/document/d/1IKUNiUhBgRURW-UkspK7fAAyIhfXuMxjk7xKikK4Yp8/edit#heading=h.tj9hitg7dbtr
>
> P1415: Machine Learning Layered list
>
> https://docs.google.com/document/d/1elNFdIXWoetbxjO1OKol_Wj8fyi4Z4hogfj5tLVSj64/edit#heading=h.tj9hitg7dbtr
>
> 2.2.2 SG14 Linear Algebra progress:
> Different layers of proposal
>
> https://docs.google.com/document/d/1poXfr7mUPovJC9ZQ5SDVM_1Nb6oYAXlK_d0ljdUAtSQ/edit
>
> 2.2.3 any other proposal for reviews?
>
> 2.3 Other Papers and proposals
>
> 2.5 Future F2F meetings:
>
> 2.6 future C++ Standard meetings:
> https://isocpp.org/std/meetings-and-participation/upcoming-meetings
>
> -2020-02-10 to 15: Prague, Czech Republic
>
> - 2020-06-01 to 06: Bulgaria
> - 2020-11: (New York, tentative)
> - 2021-02-22 to 27: Kona, HI, USA
>
> 3. Any other business
>
> New reflector
>
> http://lists.isocpp.org/mailman/listinfo.cgi/sg19
>
> Old Reflector
> https://groups.google.com/a/isocpp.org/forum/#!newtopic/sg19
> <https://groups.google.com/a/isocpp.org/forum/?fromgroups=#!forum/sg14>
>
> Code and proposal Staging area
>
> 4. Review
>
> 4.1 Review and approve resolutions and issues [e.g., changes to SG's
> working draft]
>
> 4.2 Review action items (5 min)
>
> 5. Closing process
>
> 5.1 Establish next agenda
>
> TBD
>
> 5.2 Future meeting
>
>
> Jun 11, 2020 02:00 PM
> Jul 9, 2020 02:00 PM
> Aug 13, 2020 02:00 PM
> Sep 10, 2020 02:00 PM
> Oct 8, 2020 02:00 PM
>
> SG19 Machine Learning 2 hours
> Hi,
>
> Michael Wong is inviting you to a scheduled Zoom meeting.
>
> Hi,
>
> Michael Wong is inviting you to a scheduled Zoom meeting.
>
> Topic: SG19 monthly Apr 2020-Oct 2020
> Time: Apr 9, 2020 02:00 PM Eastern Time (US and Canada) 18:00 UTC
> Every month on the Second Thu, until Oct 8, 2020, 7 occurrence(s)
> Apr 9, 2020 02:00 PM 18:00 UTC
> May 14, 2020 02:00 PM 18:00 UTC
> Jun 11, 2020 02:00 PM 18:00 UTC
> Jul 9, 2020 02:00 PM 18:00 UTC
> Aug 13, 2020 02:00 PM 18:00 UTC
> Sep 10, 2020 02:00 PM 18:00 UTC
> Oct 8, 2020 02:00 PM 18:00 UTC
> Please download and import the following iCalendar (.ics) files to your
> calendar system.
> Monthly:
>
> https://iso.zoom.us/meeting/v50sceqopj4pyLdu5Mx1orYgnZZUj0RNqw/ics?icsToken=98tyKuuhrz0pGtyQs1-CArUqE53ibvG1kmhirrYIsQe0DDJqZQ3MDNdIYoBRAc-B
>
> Join from PC, Mac, Linux, iOS or Android:
> https://iso.zoom.us/j/291630853?pwd=WUlKbS9SNFNRa0QyWXRWenlGSDhaQT09
> Password: 339768
>
> Or iPhone one-tap :
> US: +14086380968,,291630853# or +16468769923,,291630853#
> Or Telephone:
> Dial(for higher quality, dial a number based on your current location):
> US: +1 408 638 0968 or +1 646 876 9923 or +1 669 900 6833 or +1
> 253 215 8782 or +1 301 715 8592 or +1 312 626 6799 or +1 346 248 7799
> or 877 853 5247 (Toll Free)
> Meeting ID: 291 630 853
> Password: 339768
> International numbers available: https://iso.zoom.us/u/abhaIjFKLZ
>
> Or Skype for Business (Lync):
> https://iso.zoom.us/skype/291630853
>
> Agenda:
>
> 1. Opening and introductions
>
> 1.1 Roll call of participants
>
Andrew Lumsdaine, Phil Ratzloff, luke D'alessandro, Marco Foco, Richard
Dosselmann, Scott McMillan, Michael Wong, Michael Chiu, Kevin Deweese
1.2 Adopt agenda
>
Approve
> 1.3 Approve minutes from previous meeting, and approve publishing
> previously approved minutes to ISOCPP.org
>
> 1.4 Action items from previous meetings
>
> 2. Main issues (125 min)
>
> 2.1 General logistics
>
> Meeting plan, focus on one paper per meeting but does not preclude other
> paper updates:
>
> Apr 9, 2020 02:00 PM: stats paper- DONE
> May 14, 2020 02:00 PM: Stats paper replaces Differential calculus
> Jun 11, 2020 02:00 PM: Graph paper
> Jul 9, 2020 02:00 PM: Stats paper
> Aug 13, 2020 02:00 PM: Differential calculus
> Sep 10, 2020 02:00 PM: Graph paper
> Oct 8, 2020 02:00 PM: stats paper
>
>
>
> all ISO meetings online untilend of Aug
>
monthly 15th is a deadline
2.2 Paper reviews
>
> 2.2.1: ML topics
>
> Richard Dosselman et al
>
> P1708R1: Math proposal for Machine Learning
>
> https://docs.google.com/document/d/1VAgcyvL1riMdGz7tQIT9eTtSSfV3CoCEMWKk8GvVuFY/edit
>
> > std.org/jtc1/sc22/wg21/docs/papers/2020/p1708r2
> > above is the stats paper that was reviewed in Prague
> > http://wiki.edg.com/bin/view/Wg21prague/P1708R2SG19
> >
> > Revie Jolanta Polish feedback.
> > http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2020/p2119r0.html
>
Freestanding, or accumulator object? Have done both
series of weight suggested by Michael C
moved to ranges projection as suggested by Jens M
this now looks more compact
latest versoin of python has geometric + harmonic mean following geometric
mean
now we can compact all calculation of avg down to 6 , now we are on par
with with python has
Yolanta's paper pointed out notion of trimmed mean, implies it is sorted
nice compromise so we don't have to take on the trimmed stats
Luke A: have you considered less strenous restriction of input range as
long as you already have forward range?
yes I can change that as I thought foward range was more restricted, I will
change that
PR: selection between population and sample, better to use enumeration
population vs sample? OK
MF: or do both for when you need to switch to a projection? OK so switch
order of projection and population
Quantile as a replacement for median, so you can ask for 0.25 instead of
strictly median
have a random_access_range for the sorted case to find the middle position
for mode we can customize with your own allocator, customize what it means
to be equal, makes use of output iterator so you can return multiple mode
LA: may want to commit all into ranges, so return mode as a range vs output
iterator (view, allowing take_n), so return all of them and not just first
strange that python decided to only return one
PhilR: i was advised too to use output iterator
LA: range's model is composability
PhilR: Also Macro to implementation
accumulator object was more difficult to get right
liek a vehicle that stops every mile, and accumulate it at every mile, user
just say they want mean or variance, then pass the mean to this function
then you can pull the stats out of these objects; idea is to fuse multipel
operations into a single path
so in the end you can do it all in one pass
also have sig variance for a weighted mean
LA: use forwardign references && vs & aggressively when dealing with ranges
Invite Yolanta, Walter, Eric, and Lisa for July meeting.
>
> Phil Ratsloff et al
>
> P1709R1: Graph Proposal for Machine Learning
>
>
> P1709R3:
>
> https://docs.google.com/document/d/1kLHhbSTX7j0tPeTYECQFSNx3R35Mu3xO5_dyYdRy4dM/edit?usp=sharing
>
>
>
> https://docs.google.com/document/d/1QkfDzGyfNQKs86y053M0YHOLP6frzhTJqzg1Ug_vkkE/edit?usp=sharing
> <
>
> https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdocs.google.com%2Fdocument%2Fd%2F1QkfDzGyfNQKs86y053M0YHOLP6frzhTJqzg1Ug_vkkE%2Fedit%3Fusp%3Dsharing&data=02%7C01%7CPhil.Ratzloff%40sas.com%7C729b2cf8502641e4ae5e08d749064578%7Cb1c14d5c362545b3a430
> 9552373a0c2f%7C0%7C0%7C637058163592253027&sdata=4UQm8tqrcUbiZsr200UMrOaEModJYGNgP1oNot9PbAg%3D&reserved=0>
>
> Differentiable Programing by Marco Foco
>
> P1416R1: SG19 - Linear Algebra for Data Science and Machine Learning
>
> https://docs.google.com/document/d/1IKUNiUhBgRURW-UkspK7fAAyIhfXuMxjk7xKikK4Yp8/edit#heading=h.tj9hitg7dbtr
>
> P1415: Machine Learning Layered list
>
> https://docs.google.com/document/d/1elNFdIXWoetbxjO1OKol_Wj8fyi4Z4hogfj5tLVSj64/edit#heading=h.tj9hitg7dbtr
>
> 2.2.2 SG14 Linear Algebra progress:
> Different layers of proposal
>
> https://docs.google.com/document/d/1poXfr7mUPovJC9ZQ5SDVM_1Nb6oYAXlK_d0ljdUAtSQ/edit
>
> 2.2.3 any other proposal for reviews?
>
> 2.3 Other Papers and proposals
>
> 2.5 Future F2F meetings:
>
> 2.6 future C++ Standard meetings:
> https://isocpp.org/std/meetings-and-participation/upcoming-meetings
>
> -2020-02-10 to 15: Prague, Czech Republic
>
> - 2020-06-01 to 06: Bulgaria
> - 2020-11: (New York, tentative)
> - 2021-02-22 to 27: Kona, HI, USA
>
> 3. Any other business
>
> New reflector
>
> http://lists.isocpp.org/mailman/listinfo.cgi/sg19
>
> Old Reflector
> https://groups.google.com/a/isocpp.org/forum/#!newtopic/sg19
> <https://groups.google.com/a/isocpp.org/forum/?fromgroups=#!forum/sg14>
>
> Code and proposal Staging area
>
> 4. Review
>
> 4.1 Review and approve resolutions and issues [e.g., changes to SG's
> working draft]
>
> 4.2 Review action items (5 min)
>
> 5. Closing process
>
> 5.1 Establish next agenda
>
> TBD
>
> 5.2 Future meeting
>
>
> Jun 11, 2020 02:00 PM
> Jul 9, 2020 02:00 PM
> Aug 13, 2020 02:00 PM
> Sep 10, 2020 02:00 PM
> Oct 8, 2020 02:00 PM
>
Received on 2020-05-14 14:22:14