abikoushi

%ref:
%https://tex.stackexchange.com/questions/516073/how-to-draw-3d-matrix-using-tikz
%https://tikz.net/tikz-table/
%https://tikz.net/conv2d/
%
\documentclass[tikz,border=10pt]{standalone}
\usetikzlibrary{matrix,positioning}
\begin{document}

\tikzset{ 

abikoushi

%ref:
%https://tex.stackexchange.com/questions/516073/how-to-draw-3d-matrix-using-tikz
%https://tikz.net/tikz-table/
%
\documentclass[tikz,border=10pt]{standalone}
\usetikzlibrary{matrix,positioning}
\begin{document}

\tikzset{ 
    table/.style={

abikoushi

#ref:
#Jan Laukemann et al. (2025) Accelerating Sparse Tensor Decomposition Using Adaptive Linearized Representation
#https://arxiv.org/abs/2403.06348

ALTO_indexing <- function(object, data = environment(object), ...) {
  mf <- model.frame(object, data, ...)
  t <- if (missing(data)) terms(object) else terms(object, data = data)
  labs <- attr(t, "term.labels")

  mf <- lapply(labs, function(x) {

abikoushi

library(moltenNMF)
library(Matrix)

df = expand.grid(letters[1:2], LETTERS[1:2])
X = sparse_onehot(~., data = df)

A = matrix(
  c(0.5, 0.5, 0.5, 0.5, 0, 1, 0, 0, 0, 0, 0, 1),
  nrow = 4,
  ncol = 3

abikoushi

#ref:
#Jan Laukemann et al. (2025) Accelerating Sparse Tensor Decomposition Using Adaptive Linearized Representation
#https://arxiv.org/abs/2403.06348

library(dplyr)
ALTO_indexing <- function(object, data = environment(object), ...) {
  mf <- model.frame(object, data, ...)
  t <- if (missing(data)) terms(object) else terms(object, data = data)
  labs <- attr(t, "term.labels")

abikoushi

library(ggplot2)
library(dplyr)
library(tidyr)
library(rvest)
library(readr)

url = "https://ja.wikipedia.org/wiki/2015年韓国におけるMERSの流行"
taball <- read_html(url) |>
  html_table()

abikoushi

library(moltenNMF)
library(Matrix)

df = expand.grid(letters[1:2], LETTERS[1:2])
X = sparse_onehot(~. , data = df)

A=matrix(c(0.5,0.5,0.5,0.5,
           0,1,0,0,
           0,0,0,1), 4,3)

abikoushi

module VI

using LogExpFunctions
using SparseArrays
using SpecialFunctions
using Distributions

# A = sparse([1, 1, 2, 3], [1, 3, 2, 3], [0, 1, 2, 0])
# A.m # Number of rows
# A.n # Number of columns

abikoushi

library(dplyr)
library(gt)

doors = LETTERS[1:3]
policy1 = 0L
policy2 = 0L
iter = 100000
res_raw = matrix(NA_character_, iter, 4)
set.seed(1124)
system.time({

abikoushi

Ut <- function(x,alpha,beta,lambda){
  ifelse(x>0, x^alpha, -lambda*((-x)^beta))
}

params <- list(
  list(alpha=1,beta=1,lambda=1),
  list(alpha=1,beta=1,lambda=2),
  list(alpha=1/2,beta=1/2,lambda=2),
  list(alpha=2,beta=2,lambda=1)
)