nhaliday + bandits   19

CS229T/STATS231: Statistical Learning Theory
Course by Percy Liang covers a mix of statistics, computational learning theory, and some online learning. Also surveys the state-of-the-art in theoretical understanding of deep learning (not much to cover unfortunately).
yoga  stanford  course  machine-learning  stats  👳  lecture-notes  acm  kernels  learning-theory  deep-learning  frontier  init  ground-up  unit  dimensionality  vc-dimension  entropy-like  extrema  moments  online-learning  bandits  p:***  explore-exploit  advanced 
june 2016 by nhaliday

bundles : academeacm

related tags

acm  acmtariat  advanced  adversarial  ai  algorithmic-econ  algorithms  amortization-potential  average-case  bandits  best-practices  biases  bio  blog  classification  combo-optimization  conference  confidence  context  cool  cornell  course  critique  data-science  decision-making  deep-learning  deepgoog  dimensionality  discrete  distributional  engineering  ensembles  entropy-like  ethical-algorithms  ethics  evan-miller  events  expert  expert-experience  explanation  exploration-exploitation  explore-exploit  exposition  extrema  frontier  game-theory  games  gradient-descent  ground-up  hmm  homepage  iidness  init  interdisciplinary  justice  kernels  learning-theory  lecture-notes  lectures  linearity  liner-notes  list  machine-learning  magnitude  metabuch  mit  moments  nibble  off-convex  online-learning  optimization  org:bleg  org:inst  org:mat  org:nat  p:***  p:someday  papers  people  pragmatic  prediction  preprint  princeton  prof  quixotic  reflection  regression  regularization  regularizer  reinforcement  research  rhetoric  sample-complexity  sebastien-bubeck  sparsity  speedometer  stanford  state-of-art  stats  stochastic-processes  stream  study  submodular  talks  tech  technocracy  techtariat  toolkit  tutorial  unit  unsupervised  vc-dimension  video  yoga  👳 

Copy this bookmark: