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Jamie Brandon jamii

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View gist:c98fa795359a0af66de7f3ee2b96e5c4
(lldb) bt all
* thread #1, name = 'sqllogictest', stop reason = signal SIGSTOP
* frame #0: 0x00007ffff7cc82dd libpthread.so.0`__GI___pthread_timedjoin_ex + 445
frame #1: 0x0000555555b43e7d sqllogictest`join at thread.rs:168
frame #2: 0x00005555555d5618 sqllogictest`_$LT$std..thread..JoinHandle$LT$T$GT$$GT$::join::hab0e5b34b5aa2c78 + 72
frame #3: 0x00005555555e1066 sqllogictest`_$LT$timely_communication..initialize..WorkerGuards$LT$T$GT$$u20$as$u20$core..ops..drop..Drop$GT$::drop::h03f32e10376100ef + 166
frame #4: 0x00005555555c884c sqllogictest`core::ptr::real_drop_in_place::hdcc67cf3c2194a39 + 12
frame #5: 0x00005555555cc04b sqllogictest`sqllogictest::run::h0ee1d73416c26295 + 2379
frame #6: 0x00005555555c66d5 sqllogictest`sqllogictest::main::h8e18555117711ce2 + 1781
frame #7: 0x00005555555c22c3 sqllogictest`std::rt::lang_start::_$u7b$$u7b$closure$u7d$$u7d$::h3a8b47154c70f142 + 3
View gist:fd97dbed48f5acf7c82b99ff012748ec
(lldb) bt all
* thread #1, name = 'sqllogictest', stop reason = signal SIGSTOP
* frame #0: 0x00007ffff7cc82dd libpthread.so.0`__GI___pthread_timedjoin_ex + 445
frame #1: 0x0000555555b43e7d sqllogictest`join at thread.rs:168
frame #2: 0x00005555555d5618 sqllogictest`_$LT$std..thread..JoinHandle$LT$T$GT$$GT$::join::hab0e5b34b5aa2c78 + 72
frame #3: 0x00005555555e1066 sqllogictest`_$LT$timely_communication..initialize..WorkerGuards$LT$T$GT$$u20$as$u20$core..ops..drop..Drop$GT$::drop::h03f32e10376100ef + 166
frame #4: 0x00005555555c884c sqllogictest`core::ptr::real_drop_in_place::hdcc67cf3c2194a39 + 12
frame #5: 0x00005555555cc04b sqllogictest`sqllogictest::run::h0ee1d73416c26295 + 2379
frame #6: 0x00005555555c66d5 sqllogictest`sqllogictest::main::h8e18555117711ce2 + 1781
frame #7: 0x00005555555c22c3 sqllogictest`std::rt::lang_start::_$u7b$$u7b$closure$u7d$$u7d$::h3a8b47154c70f142 + 3
View codegen.jl
julia> abstract type Expr end
julia> struct Apply <: Expr
f::Expr
arg::Expr
end
julia> struct Var <: Expr
name::Symbol
end
View gist:060b49f02609d0813fcf5f0593339fb8
mdp example? https://www.nature.com/articles/s41598-017-15249-0
foraging? http://rsif.royalsocietypublishing.org/content/14/136/20170376
something better about policies? https://www.mitpressjournals.org/doi/full/10.1162/neco_a_00999
overview of papers. http://www.sciencedirect.com/science/article/pii/S0149763416307096
working software for reading model. http://www.sciencedirect.com/science/article/pii/S0149763416307096
possible alternative formulations. http://www.mdpi.com/1099-4300/19/6/266/htm
meta-bayes. http://www.ipsi.utoronto.ca/sdis/Friston-Paper.pdf
habits? http://www.sciencedirect.com/science/article/pii/S0149763416301336
hierarchical? http://rstb.royalsocietypublishing.org/content/364/1521/1211?ijkey=22b2ec7c7ee727c55840251984a7e9803922b453&keytype2=tf_ipsecsha
View gist:acc43478f933b8533a6863493bccd543
doesn't include actions
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0006421
mountain car in detail
policies are functions of sensory input
state entropy bounded by sensory entropy + transfer term
ergodic assumption
sensory entropy = integrate equilibrum density over time ie min sensory entropy = min surprise
minimizing surprise in dynamic environment requires controlling environment - cant just wait it out
but cant compute surprise directly, so need to bound it
View .md

doesn't include actions

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0006421 mountain car in detail policies are functions of sensory input state entropy bounded by sensory entropy + transfer term ergodic assumption sensory entropy = integrate equilibrum density over time ie min sensory entropy = min surprise minimizing surprise in dynamic environment requires controlling environment - cant just wait it out but cant compute surprise directly, so need to bound it

View gist:e3a96a0dcdb739c4c2104a1e6e216348
trialNo,type,title,content,trialText,stimFormat,target,stim1,stim2,stim3,stim4,stim5,stim6,mask,ITI,ISI,presTime,presTime2,button1,button2,button3,keyboard,counterTrial,counterBlock
,instructions,This is your title,"This is your content. <br><br>This screen will be presented for 5 seconds, after which the experiment advances to the next trial.",,,,,,,,,,,,,5000,,,,,,,
1,test,,,image for 10ms followed by mask until response (1 or 2),.png,,image1,,,,,,mask,50,,10,,,,,1 2,1,
2,test,,,image for 20ms followed by mask until response (1 or 2),.png,,image1,,,,,,mask,50,,20,,,,,1 2,1,
3,test,,,image for 30ms followed by mask until response (1 or 2),.png,,image1,,,,,,mask,50,,30,,,,,1 2,1,
4,test,,,image for 40ms followed by mask until response (1 or 2),.png,,image1,,,,,,mask,50,,40,,,,,1 2,1,
5,test,,,image for 50ms followed by mask until response (1 or 2),.png,,image1,,,,,,mask,50,,50,,,,,1 2,1,
6,test,,,image for 60ms followed by mask until response (1 or 2),.png,,image1,,,,,,mask,50,,60,,,,,1 2,1,
7,test,,,image fo
View p.diff
<div>
- <button>
+ <span>
</div>
View gist:fe5d210f12a6a56a175aa040a03c950f
I finally got around to doing this. Goodreads has an import tool but it requires manually adding and re-rating each book.
Amazon really doesn't seem to want to show you your old ratings, but I finally found a page in Recommendations -> Improve your recommendations -> Items you've rated.
Then run this once:
``` js
localStorage.setItem("ratings", JSON.stringify({}))
```
View backup.sh
#!/bin/bash
/usr/local/bin/tarsnap -c \
--cachedir /home/jamie/tarsnap \
--keyfile /home/jamie/tarsnap.key \
-f machine-`date +%Y-%m-%d_%H-%M-%S` \
/home/jamie/tarsnap.key \
/home/jamie/.ssh \
/home/jamie/bin \
/home/jamie/scratch \
/home/jamie/.bashrc \
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