carian buku
buku
Menyokong
Log masuk ke
Log masuk ke
pengguna yang dibenarkan mempunyai akses kepada:
cadangan peribadi
Bot Telegram
sejarah muat turun
menghantar ke E-mel atau Kindle
pengurusan senarai buku
penyimpanan ke favorit
Peribadi
Permintaan buku
Penelitian
Z-Recommend
Senarai buku
Yang paling popular
Kategori
Penyertaan
Menyokong
Muat naik
Litera Library
Menyumbangkan buku kertas
Menambahkan buku-buku kertas
Search paper books
LITERA Point saya
Carian kata kunci
Main
Carian kata kunci
search
1
statistical reinforcement learning modern machine learning approaches
policy
figure
function
reinforcement
samples
iteration
error
functions
parameter
reward
graph
approximation
statistical
generalization
kernels
gaussian
sample
flattening
transition
policies
squares
importance
ggks
sampling
immediate
goal
obtained
values
optimal
reuse
denotes
chosen
variance
examples
ggk
illustrated
task
estimator
method
probability
rewards
srpi
active
defined
episodes
iwcv
kernel
maze
solution
validation
Bahasa:
chinese
Fail:
PDF, 29.83 MB
Tag anda:
0
/
0
chinese
2
Statistical Reinforcement Learning: Modern Machine Learning Approaches
CRC Press
Sugiyama
,
Masashi
policy
figure
iteration
samples
reinforcement
function
pgpe
parameter
gradient
method
error
gaussian
search
trajectory
transition
statistical
obtained
variance
reward
sample
sampling
ℓ
importance
policies
estimation
probability
lscde
density
functions
prior
brush
denotes
chosen
optimal
approximation
conditional
standard
reduction
estimator
goal
generalization
reuse
squares
approach
rewards
defined
immediate
baseline
joint
methods
Tahun:
2015
Bahasa:
english
Fail:
PDF, 7.25 MB
Tag anda:
5.0
/
5.0
english, 2015
3
Statistical Reinforcement Learning: Modern Machine Learning Approaches
Chapman and Hall/CRC
Masashi Sugiyama
policy
figure
iteration
samples
reinforcement
function
pgpe
parameter
gradient
error
method
search
gaussian
trajectory
transition
statistical
obtained
variance
reward
sample
sampling
importance
estimation
policies
probability
density
functions
prior
lscde
brush
denotes
chosen
optimal
approximation
conditional
reduction
standard
estimator
goal
reuse
generalization
ℓ
approach
rewards
squares
defined
immediate
baseline
dimensionality
joint
Tahun:
2015
Bahasa:
english
Fail:
PDF, 11.55 MB
Tag anda:
1.0
/
1.0
english, 2015
1
Ikuti
pautan ini
atau cari bot "@BotFather" dalam Telegram
2
Hantar arahan /newbot
3
Berikan nama untuk bot anda
4
Berikan nama pengguna untuk bot
5
Salin mesej terbaharu daripada BotFather dan tampalkannya di sini
×
×