@deanmalmgren
@DsAtweet
2014 august
nyc algorithmic trading
quant skillz beyond wall st
deriving value from large, non-fina...
@deanmalmgren | bit.ly/design-data
data scientists thrive with ambiguity
solve for x
x = 5 + 2
projectevolution
@deanmalmgren | bit.ly/design-data
data scientists thrive with ambiguity
solve for x
x = 5 + 2
projectevolution
A x = b
@deanmalmgren | bit.ly/design-data
data scientists thrive with ambiguity
solve for x
x = 5 + 2
projectevolution
A x = b
op...
@deanmalmgren | bit.ly/design-data
data scientists thrive with ambiguity
solve for x
x = 5 + 2
projectevolution
A x = b op...
@deanmalmgren | bit.ly/design-data
data scientists thrive with ambiguity
solve for x
x = 5 + 2
projectevolution
A x = b op...
@deanmalmgren | bit.ly/design-data
origins of ambiguity
many feasible approaches
@deanmalmgren | bit.ly/design-data
origins of ambiguity
unclear problems
identify the best locations to plant new trees
@deanmalmgren | bit.ly/design-data
origins of ambiguity
unclear problems
@deanmalmgren | bit.ly/design-data
identify the b...
@deanmalmgren | bit.ly/design-data
origins of ambiguity
unclear problems
identify the best locations to plant new trees
ho...
@deanmalmgren | bit.ly/design-data
generate
hypotheses
build
prototype
evaluate
feedback
“design process” is used everywhe...
@deanmalmgren | bit.ly/design-data
generate
hypotheses
build
prototype
evaluate
feedback
surveys, interviews, focus groups...
@deanmalmgren | bit.ly/design-data
generate
hypotheses
build
prototype
evaluate
feedback
design and data science
challenge...
@deanmalmgren | bit.ly/design-data
generate
hypotheses
build
prototype
evaluate
feedback
problem lost in translation
desig...
@deanmalmgren | bit.ly/design-data
generate
hypotheses
build
prototype
evaluate
feedback
problem lost in translation
takes...
@deanmalmgren | bit.ly/design-data
generate
hypotheses
build
prototype
evaluate
feedback
proof is in the pudding
problem l...
@deanmalmgren | bit.ly/design-data
how do projects start?
@deanmalmgren | bit.ly/design-data
how do projects start?
@deanmalmgren | bit.ly/design-data
how do projects start?
@deanmalmgren | bit.ly/design-data
how do projects start?
@deanmalmgren | bit.ly/design-data
how do projects start?
@deanmalmgren | bit.ly/design-data
informal conversation to stated goals
mostly bad ideas, but a few good ones
@deanmalmgren | bit.ly/design-data@deanmalmgren | bit.ly/design-data
mostly bad ideas, but a few good ones
informal conver...
@deanmalmgren | bit.ly/design-data@deanmalmgren | bit.ly/design-data
mostly bad ideas, but a few good ones
Lorem Ipsum: a ...
@deanmalmgren | bit.ly/design-data@deanmalmgren | bit.ly/design-data
mostly bad ideas, but a few good ones
Lorem Ipsum: a ...
@deanmalmgren | bit.ly/design-data@deanmalmgren | bit.ly/design-data
mostly bad ideas, but a few good ones
informal conver...
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing
search engine
with relevance metrics...
@deanmalmgren | bit.ly/design-data
from sketch to blue print to prototype
add detail to get feedback (while building)
@deanmalmgren | bit.ly/design-data
from sketch to blue print to prototype
add detail to get feedback (while building)
@deanmalmgren | bit.ly/design-data
from sketch to blue print to prototype
add detail to get feedback (while building)
@deanmalmgren | bit.ly/design-data
from sketch to blue print to prototype
add detail to get feedback (while building)
@deanmalmgren | bit.ly/design-data
motorola
data-driven consumer feedback
@deanmalmgren | bit.ly/design-data
motorola
new product
announcement
data-driven consumer feedback
@deanmalmgren | bit.ly/design-data
motorola
new product
announcement
first versions
from manufacturer
data-driven consumer ...
@deanmalmgren | bit.ly/design-data
motorola
new product
announcement
first versions
from manufacturer
available
in stores
d...
@deanmalmgren | bit.ly/design-data
motorola
new product
announcement
first versions
from manufacturer
available
in stores
n...
@deanmalmgren | bit.ly/design-data
motorola
new product
announcement
first versions
from manufacturer
available
in stores
n...
@deanmalmgren | bit.ly/design-data
motorola
data-driven consumer feedback
@deanmalmgren | bit.ly/design-data
motorola
data-driven consumer feedback
@deanmalmgren | bit.ly/design-data
motorola
data-driven consumer feedback
@deanmalmgren | bit.ly/design-data
motorola
data-driven consumer feedback
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
aboutpatent
not
aboutpatent
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
aboutpatent
not
aboutpatent
turn over to plaintiff
don’t...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
aboutpatent
not
aboutpatent
turn over to plaintiff
don’t...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
aboutpatent
not
aboutpatent
turn over to plaintiff
don’t...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
turn over to plaintiff
don’t
turn over to plaintiff
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
algorithm design
patents
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
algorithm design
patents
fantasy football
lunch
coffee
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
algorithm design
patents
marketing
finances
fantasy footb...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
algorithm design
patents
marketi...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
fantasy football
algorithm desig...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
fantasy football
algorithm desig...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
fantasy football
algorithm desig...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
fantasy football
algorithm desig...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
fantasy football
algorithm desig...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
fantasy football
algorithm desig...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
fantasy football
algorithm desig...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
fantasy football
algorithm desig...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
create a “document map”
fantasy football
algorithm desig...
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
awesome!
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
who cares?
awesome!
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
who cares?
awesome!
<lots of iteration/>
@deanmalmgren | bit.ly/design-data
data-driven e-discovery
daegis
@deanmalmgren | bit.ly/design-data
quant skillz to data science?
bit.ly/metis-ds
generate
hypotheses
build
prototype
evalu...
@deanmalmgren | bit.ly/design-data
quant skillz to data science?
bit.ly/metis-ds
http://bit.ly/design-data
http://bit.ly/metis-ds
!
@deanmalmgren
dean.malmgren@datascopeanalytics.com
solve ambiguous prob...
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quant skillz beyond wall st: deriving value from large, non-financial datasets

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This presentation was prepared for a talk on 2014.08.06 at the NYC Algorithmic Trading meetup (http://www.meetup.com/NYC-Algorithmic-Trading/events/197749772/)

Regardless of whether you call it "data science", "business intelligence", "analytics", "statistics" or just plain old "math", we have many tried and true techniques for dealing with uncertainty (particularly in quantitative finance). But ambiguity—what problem do we need to solve in the first place?—is a separate matter and, at least in my experience, is the hardest part of creating value from data. During this talk, I'll discuss how we address ambiguity by giving a guided tour of some of our client projects, such as how to reduce legal e-discovery costs by 99% (hint: supervised binary classification of text documents) or how to assemble project teams on emerging R&D opportunities in a multinational organization (hint: unsupervised classification of employee expertise).

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quant skillz beyond wall st: deriving value from large, non-financial datasets

  1. 1. @deanmalmgren @DsAtweet 2014 august nyc algorithmic trading quant skillz beyond wall st deriving value from large, non-financial datasets
  2. 2. @deanmalmgren | bit.ly/design-data data scientists thrive with ambiguity solve for x x = 5 + 2 projectevolution
  3. 3. @deanmalmgren | bit.ly/design-data data scientists thrive with ambiguity solve for x x = 5 + 2 projectevolution A x = b
  4. 4. @deanmalmgren | bit.ly/design-data data scientists thrive with ambiguity solve for x x = 5 + 2 projectevolution A x = b optimize A x = b subject to f(x) > 0
  5. 5. @deanmalmgren | bit.ly/design-data data scientists thrive with ambiguity solve for x x = 5 + 2 projectevolution A x = b optimize f(x) optimize A x = b subject to f(x) > 0
  6. 6. @deanmalmgren | bit.ly/design-data data scientists thrive with ambiguity solve for x x = 5 + 2 projectevolution A x = b optimize f(x) optimize A x = b subject to f(x) > 0 optimize “our profitability”
  7. 7. @deanmalmgren | bit.ly/design-data origins of ambiguity many feasible approaches
  8. 8. @deanmalmgren | bit.ly/design-data origins of ambiguity unclear problems identify the best locations to plant new trees
  9. 9. @deanmalmgren | bit.ly/design-data origins of ambiguity unclear problems @deanmalmgren | bit.ly/design-data identify the best locations to plant new trees how many? what kinds of trees? move old trees? replace old trees?
  10. 10. @deanmalmgren | bit.ly/design-data origins of ambiguity unclear problems identify the best locations to plant new trees how many? what kinds of trees? move old trees? replace old trees? aesthetically pleasing? maximize growth? increase foliage? offset CO2 emissions? @deanmalmgren | bit.ly/design-data
  11. 11. @deanmalmgren | bit.ly/design-data generate hypotheses build prototype evaluate feedback “design process” is used everywhere anticipate failure 1-4 week iterations
  12. 12. @deanmalmgren | bit.ly/design-data generate hypotheses build prototype evaluate feedback surveys, interviews, focus groups split testing, A/B testing QA; requirements churn personas, scenarios, use cases business/product requirements story/user cards build device prototypes minimum viable product write code human-centered design lean startup agile programming “design process” is used everywhere anticipate failure 1-4 week iterations
  13. 13. @deanmalmgren | bit.ly/design-data generate hypotheses build prototype evaluate feedback design and data science challenges in practice 1-4 week iterations
  14. 14. @deanmalmgren | bit.ly/design-data generate hypotheses build prototype evaluate feedback problem lost in translation design and data science challenges in practice 1-4 week iterations
  15. 15. @deanmalmgren | bit.ly/design-data generate hypotheses build prototype evaluate feedback problem lost in translation takes a long time to collect data, analyze, and build visualization design and data science challenges in practice 1-4 week iterations
  16. 16. @deanmalmgren | bit.ly/design-data generate hypotheses build prototype evaluate feedback proof is in the pudding problem lost in translation takes a long time to collect data, analyze, and build visualization design and data science challenges in practice 1-4 week iterations
  17. 17. @deanmalmgren | bit.ly/design-data how do projects start?
  18. 18. @deanmalmgren | bit.ly/design-data how do projects start?
  19. 19. @deanmalmgren | bit.ly/design-data how do projects start?
  20. 20. @deanmalmgren | bit.ly/design-data how do projects start?
  21. 21. @deanmalmgren | bit.ly/design-data how do projects start?
  22. 22. @deanmalmgren | bit.ly/design-data informal conversation to stated goals mostly bad ideas, but a few good ones
  23. 23. @deanmalmgren | bit.ly/design-data@deanmalmgren | bit.ly/design-data mostly bad ideas, but a few good ones informal conversation to stated goals
  24. 24. @deanmalmgren | bit.ly/design-data@deanmalmgren | bit.ly/design-data mostly bad ideas, but a few good ones Lorem Ipsum: a narrative about blankets. Author: Charlie Brown Date: 31 Jan 2012 ! Lorem Ipsum is a dummy text used when typesetting or marking up documents. It has a long history starting from the 1500s and is still used in digital millennium for typesetting electronic documents, page designs, etc. ! In itself, the original text of Lorem Ipsum might have been taken from an ancient Latin book that was written about 50 BC. Nevertheless, Lorem Ipsum’s words have been changed so they don’t read as a proper text. ! Naturally, page designs that are made for text documents must contain some text rather than placeholder dots or something else. However, should they contain proper English words and sentences almost every reader will deliberately try to interpret it eventually, missing the design itself. ! However, a placeholder text must have a natural distribution of letters and punctuation or otherwise the markup will look strange and unnatural. That’s what Lorem Ipsum helps to achieve. ! I would like to thank Peppermint Pattyfor her support on studying Lorem Ipsum as well as the infinite wisdom of Linus van Peltand his willingness to use his blanket in my experiments. informal conversation to stated goals
  25. 25. @deanmalmgren | bit.ly/design-data@deanmalmgren | bit.ly/design-data mostly bad ideas, but a few good ones Lorem Ipsum: a narrative about blankets. Author: Charlie Brown Date: 31 Jan 2012 ! Lorem Ipsum is a dummy text used when typesetting or marking up documents. It has a long history starting from the 1500s and is still used in digital millennium for typesetting electronic documents, page designs, etc. ! In itself, the original text of Lorem Ipsum might have been taken from an ancient Latin book that was written about 50 BC. Nevertheless, Lorem Ipsum’s words have been changed so they don’t read as a proper text. ! Naturally, page designs that are made for text documents must contain some text rather than placeholder dots or something else. However, should they contain proper English words and sentences almost every reader will deliberately try to interpret it eventually, missing the design itself. ! However, a placeholder text must have a natural distribution of letters and punctuation or otherwise the markup will look strange and unnatural. That’s what Lorem Ipsum helps to achieve. ! I would like to thank Peppermint Pattyfor her support on studying Lorem Ipsum as well as the infinite wisdom of Linus van Peltand his willingness to use his blanket in my experiments. informal conversation to stated goals
  26. 26. @deanmalmgren | bit.ly/design-data@deanmalmgren | bit.ly/design-data mostly bad ideas, but a few good ones informal conversation to stated goals
  27. 27. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  28. 28. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  29. 29. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  30. 30. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  31. 31. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  32. 32. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  33. 33. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  34. 34. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  35. 35. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  36. 36. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  37. 37. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  38. 38. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  39. 39. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  40. 40. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  41. 41. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing
  42. 42. @deanmalmgren | bit.ly/design-data concept sketch comparisons qualitative a/b testing search engine with relevance metrics demographics human readable expertise summary
  43. 43. @deanmalmgren | bit.ly/design-data from sketch to blue print to prototype add detail to get feedback (while building)
  44. 44. @deanmalmgren | bit.ly/design-data from sketch to blue print to prototype add detail to get feedback (while building)
  45. 45. @deanmalmgren | bit.ly/design-data from sketch to blue print to prototype add detail to get feedback (while building)
  46. 46. @deanmalmgren | bit.ly/design-data from sketch to blue print to prototype add detail to get feedback (while building)
  47. 47. @deanmalmgren | bit.ly/design-data motorola data-driven consumer feedback
  48. 48. @deanmalmgren | bit.ly/design-data motorola new product announcement data-driven consumer feedback
  49. 49. @deanmalmgren | bit.ly/design-data motorola new product announcement first versions from manufacturer data-driven consumer feedback
  50. 50. @deanmalmgren | bit.ly/design-data motorola new product announcement first versions from manufacturer available in stores data-driven consumer feedback
  51. 51. @deanmalmgren | bit.ly/design-data motorola new product announcement first versions from manufacturer available in stores next generation to manufacturer data-driven consumer feedback
  52. 52. @deanmalmgren | bit.ly/design-data motorola new product announcement first versions from manufacturer available in stores next generation to manufacturer product defects from consumers data-driven consumer feedback
  53. 53. @deanmalmgren | bit.ly/design-data motorola data-driven consumer feedback
  54. 54. @deanmalmgren | bit.ly/design-data motorola data-driven consumer feedback
  55. 55. @deanmalmgren | bit.ly/design-data motorola data-driven consumer feedback
  56. 56. @deanmalmgren | bit.ly/design-data motorola data-driven consumer feedback
  57. 57. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis
  58. 58. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis
  59. 59. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis
  60. 60. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis aboutpatent not aboutpatent
  61. 61. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis aboutpatent not aboutpatent turn over to plaintiff don’t turn over to plaintiff adverse inference
  62. 62. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis aboutpatent not aboutpatent turn over to plaintiff don’t turn over to plaintiff adverse inference give away trade secrets
  63. 63. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis aboutpatent not aboutpatent turn over to plaintiff don’t turn over to plaintiff adverse inference give away trade secrets
  64. 64. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis turn over to plaintiff don’t turn over to plaintiff
  65. 65. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis
  66. 66. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis
  67. 67. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis algorithm design patents
  68. 68. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis algorithm design patents fantasy football lunch coffee
  69. 69. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis algorithm design patents marketing finances fantasy football lunch coffee
  70. 70. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” algorithm design patents marketing finances fantasy football lunch coffee
  71. 71. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” fantasy football algorithm design patents lunch marketing finances coffee
  72. 72. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” fantasy football algorithm design patents lunch marketing finances coffee
  73. 73. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” fantasy football algorithm design patents lunch marketing finances coffee
  74. 74. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” fantasy football algorithm design patents lunch marketing finances coffee
  75. 75. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” fantasy football algorithm design patents lunch marketing finances coffee
  76. 76. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” fantasy football algorithm design patents lunch marketing finances coffee
  77. 77. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” fantasy football algorithm design patents lunch marketing finances coffee
  78. 78. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” fantasy football algorithm design patents lunch marketing finances coffee review away shades of grey
  79. 79. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis create a “document map” fantasy football algorithm design patents lunch marketing finances coffee review away shades of grey reduce reviews by 90-99%
  80. 80. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis
  81. 81. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis awesome!
  82. 82. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis who cares? awesome!
  83. 83. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis who cares? awesome! <lots of iteration/>
  84. 84. @deanmalmgren | bit.ly/design-data data-driven e-discovery daegis
  85. 85. @deanmalmgren | bit.ly/design-data quant skillz to data science? bit.ly/metis-ds generate hypotheses build prototype evaluate feedback 1-4 week iterations
  86. 86. @deanmalmgren | bit.ly/design-data quant skillz to data science? bit.ly/metis-ds
  87. 87. http://bit.ly/design-data http://bit.ly/metis-ds ! @deanmalmgren dean.malmgren@datascopeanalytics.com solve ambiguous problems with quantitative, iterative approach
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