\( \newcommand{\matr}[1] {\mathbf{#1}} \newcommand{\vertbar} {\rule[-1ex]{0.5pt}{2.5ex}} \newcommand{\horzbar} {\rule[.5ex]{2.5ex}{0.5pt}} \newcommand{\E} {\mathrm{E}} \)
deepdream of
          a sidewalk

Kevin Doran

Lebesgue Measure. Definition

\( \newcommand{\cat}[1] {\mathrm{#1}} \newcommand{\catobj}[1] {\operatorname{Obj}(\mathrm{#1})} \newcommand{\cathom}[1] {\operatorname{Hom}_{\cat{#1}}} \newcommand{\multiBetaReduction}[0] {\twoheadrightarrow_{\beta}} \newcommand{\betaReduction}[0] {\rightarrow_{\beta}} \newcommand{\betaEq}[0] {=_{\beta}} \newcommand{\string}[1] {\texttt{"}\mathtt{#1}\texttt{"}} \newcommand{\symbolq}[1] {\texttt{`}\mathtt{#1}\texttt{'}} \newcommand{\groupMul}[1] { \cdot_{\small{#1}}} \newcommand{\groupAdd}[1] { +_{\small{#1}}} \newcommand{\inv}[1] {#1^{-1} } \newcommand{\bm}[1] { \boldsymbol{#1} } \require{physics} \require{ams} \require{mathtools} \) Math and science::Analysis::Tao, measure::02. Lebesgue measure Lebesgue Measure. Definition The Jordan measure has limitations. Tweak the Jordan measure to arrive at the Lebesgue measure. Jordan measure on \( \mathbb{R}^d \) Recap. The development of Jordan measure proceeded as follows: Read more...

Lebesgue Measure. Definition (answer)

\( \newcommand{\cat}[1] {\mathrm{#1}} \newcommand{\catobj}[1] {\operatorname{Obj}(\mathrm{#1})} \newcommand{\cathom}[1] {\operatorname{Hom}_{\cat{#1}}} \newcommand{\multiBetaReduction}[0] {\twoheadrightarrow_{\beta}} \newcommand{\betaReduction}[0] {\rightarrow_{\beta}} \newcommand{\betaEq}[0] {=_{\beta}} \newcommand{\string}[1] {\texttt{"}\mathtt{#1}\texttt{"}} \newcommand{\symbolq}[1] {\texttt{`}\mathtt{#1}\texttt{'}} \newcommand{\groupMul}[1] { \cdot_{\small{#1}}} \newcommand{\groupAdd}[1] { +_{\small{#1}}} \newcommand{\inv}[1] {#1^{-1} } \newcommand{\bm}[1] { \boldsymbol{#1} } \require{physics} \require{ams} \require{mathtools} \) Math and science::Analysis::Tao, measure::02. Lebesgue measure Lebesgue Measure. Definition The Jordan measure has limitations. Tweak the Jordan measure to arrive at the Lebesgue measure. Jordan measure on \( \mathbb{R}^d \) Recap. The development of Jordan measure proceeded as follows: Read more...

The 3 basic properties of Lebesgue outer measure 

\( \newcommand{\cat}[1] {\mathrm{#1}} \newcommand{\catobj}[1] {\operatorname{Obj}(\mathrm{#1})} \newcommand{\cathom}[1] {\operatorname{Hom}_{\cat{#1}}} \newcommand{\multiBetaReduction}[0] {\twoheadrightarrow_{\beta}} \newcommand{\betaReduction}[0] {\rightarrow_{\beta}} \newcommand{\betaEq}[0] {=_{\beta}} \newcommand{\string}[1] {\texttt{"}\mathtt{#1}\texttt{"}} \newcommand{\symbolq}[1] {\texttt{`}\mathtt{#1}\texttt{'}} \newcommand{\groupMul}[1] { \cdot_{\small{#1}}} \newcommand{\groupAdd}[1] { +_{\small{#1}}} \newcommand{\inv}[1] {#1^{-1} } \newcommand{\bm}[1] { \boldsymbol{#1} } \require{physics} \require{ams} \require{mathtools} \) Math and science::Analysis::Tao, measure::02. Lebesgue measure The 3 basic properties of Lebesgue outer measure  Reminder that the Lebesgue outer measure is denoted as \( m^{*} \). The 3 basic propositions of Lebesgue outer measure Empty set [. Read more...

The 3 basic properties of Lebesgue outer measure  (answer)

\( \newcommand{\cat}[1] {\mathrm{#1}} \newcommand{\catobj}[1] {\operatorname{Obj}(\mathrm{#1})} \newcommand{\cathom}[1] {\operatorname{Hom}_{\cat{#1}}} \newcommand{\multiBetaReduction}[0] {\twoheadrightarrow_{\beta}} \newcommand{\betaReduction}[0] {\rightarrow_{\beta}} \newcommand{\betaEq}[0] {=_{\beta}} \newcommand{\string}[1] {\texttt{"}\mathtt{#1}\texttt{"}} \newcommand{\symbolq}[1] {\texttt{`}\mathtt{#1}\texttt{'}} \newcommand{\groupMul}[1] { \cdot_{\small{#1}}} \newcommand{\groupAdd}[1] { +_{\small{#1}}} \newcommand{\inv}[1] {#1^{-1} } \newcommand{\bm}[1] { \boldsymbol{#1} } \require{physics} \require{ams} \require{mathtools} \) Math and science::Analysis::Tao, measure::02. Lebesgue measure The 3 basic properties of Lebesgue outer measure  Reminder that the Lebesgue outer measure is denoted as \( m^{*} \). The 3 basic propositions of Lebesgue outer measure Empty set \( m^{*}(\emptyset) = 0 \) Monotonicity If \( E  \subseteq F \subset \mathbb{R}^d \), then \( m^{*}(E) \le m^{*}(F) \). Read more...

Richard–Berry paradox

Math and science::INF ML AI Richard–Berry paradox A paradox highlighting an issue with using description length as a measure of complexity. Define a specific natural number as "the least natural number that [...]". 

Richard–Berry paradox (answer)

Math and science::INF ML AI Richard–Berry paradox A paradox highlighting an issue with using description length as a measure of complexity. Define a specific natural number as "the least natural number that cannot be described in fewer than 20 words".  If such a number does exist, then we have just described it in 13 words, contradicting its definition. If such a number doesn't exist, then all natural numbers can be described in fewer than 20 words. Read more...

The two types of compressors

Math and science::INF ML AI The two types of compressors There are only two ways in which a purported compressor can compress files. Each makes a trade-off.

The two types of compressors (answer)

Math and science::INF ML AI The two types of compressors There are only two ways in which a purported compressor can compress files. Each makes a trade-off. Lossy compression A lossy compression compresses some (possibly all) files, but it maps some files to the same encoding. When decompression if an ambiguous files is encountered, there is no way to know for sure which of the multiple files having that encoding was the original file. Read more...

Derivative of monotone functions

\( \newcommand{\cat}[1] {\mathrm{#1}} \newcommand{\catobj}[1] {\operatorname{Obj}(\mathrm{#1})} \newcommand{\cathom}[1] {\operatorname{Hom}_{\cat{#1}}} \newcommand{\multiBetaReduction}[0] {\twoheadrightarrow_{\beta}} \newcommand{\betaReduction}[0] {\rightarrow_{\beta}} \newcommand{\betaEq}[0] {=_{\beta}} \newcommand{\string}[1] {\texttt{"}\mathtt{#1}\texttt{"}} \newcommand{\symbolq}[1] {\texttt{`}\mathtt{#1}\texttt{'}} \newcommand{\groupMul}[1] { \cdot_{\small{#1}}} \newcommand{\groupAdd}[1] { +_{\small{#1}}} \newcommand{\inv}[1] {#1^{-1} } \newcommand{\bm}[1] { \boldsymbol{#1} } \require{physics} \require{ams} \require{mathtools} \) Math and science::Analysis::Tao::10: Differentiation of functions Derivative of monotone functions Monotone increasing implies [...] Let \( X \) be a subset of \( \mathbb{R} \), and let \( x_0 \in X \) be a limit point of \( X \). Read more...

Derivative of monotone functions (answer)

\( \newcommand{\cat}[1] {\mathrm{#1}} \newcommand{\catobj}[1] {\operatorname{Obj}(\mathrm{#1})} \newcommand{\cathom}[1] {\operatorname{Hom}_{\cat{#1}}} \newcommand{\multiBetaReduction}[0] {\twoheadrightarrow_{\beta}} \newcommand{\betaReduction}[0] {\rightarrow_{\beta}} \newcommand{\betaEq}[0] {=_{\beta}} \newcommand{\string}[1] {\texttt{"}\mathtt{#1}\texttt{"}} \newcommand{\symbolq}[1] {\texttt{`}\mathtt{#1}\texttt{'}} \newcommand{\groupMul}[1] { \cdot_{\small{#1}}} \newcommand{\groupAdd}[1] { +_{\small{#1}}} \newcommand{\inv}[1] {#1^{-1} } \newcommand{\bm}[1] { \boldsymbol{#1} } \require{physics} \require{ams} \require{mathtools} \) Math and science::Analysis::Tao::10: Differentiation of functions Derivative of monotone functions Monotone increasing implies a non-negative derivative Let \( X \) be a subset of \( \mathbb{R} \), and let \( x_0 \in X \) be a limit point of \( X \). Read more...
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