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| This is in user space because it's not really about machine learning.
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| {| class="sortable wikitable" | | {| class="sortable wikitable" |
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| ! Term !! Notation !! Type !! Definition !! Notes | | ! Term !! Notation !! Type !! Definition !! Notes |
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| | <math>\mathcal F</math>-combination || <math>A</math> || <math>\mathcal S \cup \{0,1\} \to \mathcal F_n</math> || || Function application of an <math>\mathcal F</math>-combination uses square brackets instead of parentheses. Why? As far as I can tell, this is because each coefficient is in <math>\mathcal F</math> so is itself a function. This means we have two senses of "application": we can pick out the specific coefficient we want (square brackets), or we can apply each coefficient to return something (parentheses). | | | <math>\mathcal F</math>-combination || <math>A</math> || <math>\mathcal S \cup \{1\} \to \mathcal F_n</math> || || Function application of an <math>\mathcal F</math>-combination uses square brackets instead of parentheses. Why? As far as I can tell, this is because each coefficient is in <math>\mathcal F</math> so is itself a function. This means we have two senses of "application": we can pick out the specific coefficient we want (square brackets), or we can apply each coefficient to return something (parentheses). |
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| | Holdings from <math>T</math> against <math>\overline{\mathbb P}</math> (a <math>\mathbb Q</math>-combination)|| <math>T(\overline{\mathbb P})</math> || <math>\mathcal S \cup \{0,1\} \to \mathbb Q</math> || || | | | Holdings from <math>T</math> against <math>\overline{\mathbb P}</math> (a <math>\mathbb Q</math>-combination)|| <math>T(\overline{\mathbb P})</math> || <math>\mathcal S \cup \{1\} \to \mathbb Q</math> || || |
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| | Trading strategy || <math>T</math> || <math>\mathcal S \cup \{1\} \to \mathcal{E\!F}</math> || || | | | Trading strategy || <math>T</math> || <math>\mathcal S \cup \{1\} \to \mathcal{E\!F}</math> || || |
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| :<math>\mathbb W(T(\overline{\mathbb V})) = c(\overline{\mathbb V})+ \xi_1(\overline{\mathbb V})\mathbb W(\phi_1) + \cdots + \xi_k(\overline{\mathbb V})\mathbb W(\phi_k) \in \mathbb R</math> | | :<math>\mathbb W(T(\overline{\mathbb V})) = c(\overline{\mathbb V})+ \xi_1(\overline{\mathbb V})\mathbb W(\phi_1) + \cdots + \xi_k(\overline{\mathbb V})\mathbb W(\phi_k) \in \mathbb R</math> |
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| I think <math>\mathbb W(T(\overline{\mathbb V})) = (\mathbb W(T))(\overline{\mathbb V})</math>. | | I think <math>\mathbb W(T(\overline{\mathbb V})) = (\mathbb W(T))(\overline{\mathbb V})</math> but the former notation seems to be preferred in the paper. |
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| The following is used in the Fixed Point Lemma (5.1.1):
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| Writing the <math>n</math>-strategy as
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| :<math>T_n = \sum_{j=1}^k \xi_j \phi_j - \sum_{j=1}^k \xi_j\phi_j^{*n}</math>
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| we have
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| :<math>\mathbb V(T_n(\mathbb P_{\leq n-1}, \mathbb V)) = \sum_{j=1}^k \xi_j(\mathbb P_{\leq n-1}, \mathbb V)\cdot \mathbb V(\phi_j) - \sum_{j=1}^k \xi_j(\mathbb P_{\leq n-1}, \mathbb V) \cdot \phi_j^{*n}(\mathbb P_{\leq n-1}, \mathbb V)</math>
| | ==See also== |
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| But <math>\phi^{*n}(\mathbb P_{\leq n-1}, \mathbb V) = \mathbb V(\phi_j)</math> so the two sums cancel to obtain <math>0</math>.
| | * https://machinelearning.subwiki.org/wiki/User:IssaRice/Logical_inductor_construction |
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| ==External links== | | ==External links== |
Term |
Notation |
Type |
Definition |
Notes
|
-combination |
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 |
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Function application of an -combination uses square brackets instead of parentheses. Why? As far as I can tell, this is because each coefficient is in so is itself a function. This means we have two senses of "application": we can pick out the specific coefficient we want (square brackets), or we can apply each coefficient to return something (parentheses).
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Holdings from against (a -combination) |
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Trading strategy |
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Feature |
 |
or equivalently or equivalently  |
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Example of a 5-strategy given on p. 18 of the paper:
![{\displaystyle \underbrace {\left[(\neg \neg \phi )^{*5}-\phi ^{*5}\right]} _{\xi _{1}}\cdot (\phi -\phi ^{*5})+\underbrace {\left[\phi ^{*5}-(\neg \neg \phi )^{*5}\right]} _{\xi _{2}}\cdot \left(\neg \neg \phi -(\neg \neg \phi )^{*5}\right)}](https://wikimedia.org/api/rest_v1/media/math/render/svg/7431a4d14ca4f3c336b8bbfbe7e0cfa191843a40)
Since the coefficients (
and
) are in
, this is an
-combination. Let's call this 5-strategy
. We can pick out the coefficient for the
term like
. But since each coefficient is a feature (which is a function), we can also apply each coefficient to some valuation sequence
, like this:
![{\displaystyle T_{5}({\overline {\mathbb {V} }})=\left[(\neg \neg \phi )^{*5}({\overline {\mathbb {V} }})-\phi ^{*5}({\overline {\mathbb {V} }})\right]\cdot (\phi -\phi ^{*5}({\overline {\mathbb {V} }}))+\left[\phi ^{*5}({\overline {\mathbb {V} }})-(\neg \neg \phi )^{*5}({\overline {\mathbb {V} }})\right]\cdot \left(\neg \neg \phi -(\neg \neg \phi )^{*5}({\overline {\mathbb {V} }})\right)}](https://wikimedia.org/api/rest_v1/media/math/render/svg/3d594f8de75b2faf3b3386495415c7f234eeccd7)
Now each coefficient is a real number, so
is an
-combination. Note that since
is a function that takes a sentence or the number
and
is a valuation sequence (not a sentence or number), there appears to be a type error in writing
. What is going on is that we aren't evaluating
at
; rather, we are evaluating each coefficient of
, to convert the range of
from
to
.
To summarize the types:

in other words ![{\displaystyle T_{5}[\phi ]\colon [0,1]^{{\mathcal {S}}\times \mathbb {N} ^{+}}\to \mathbb {R} }](https://wikimedia.org/api/rest_v1/media/math/render/svg/ebfe5b7ecb197d0c9ff3bfdc1114c8dc980ba632)

If
, then

and

and

I think
but the former notation seems to be preferred in the paper.
See also
External links