nhaliday + princeton   40

Information Processing: Mathematical Theory of Deep Neural Networks (Princeton workshop)
"Recently, long-past-due theoretical results have begun to emerge. These results, and those that will follow in their wake, will begin to shed light on the properties of large, adaptive, distributed learning architectures, and stand to revolutionize how computer science and neuroscience understand these systems."
hsu  scitariat  commentary  links  research  research-program  workshop  events  princeton  sanjeev-arora  deep-learning  machine-learning  ai  generalization  explanans  off-convex  nibble  frontier  speedometer  state-of-art  big-surf  announcement 
january 2018 by nhaliday
The Government is the Largest Source of University Funding | Free By 50
wonkish  data  visualization  let-me-see  higher-ed  academia  money  variance-components  distribution  monetary-fiscal  local-global  government  multi  usa  org:edu  org:ngo  chart  roots  org:lite  counter-revolution  class-warfare  nascent-state  pdf  white-paper  org:data  analysis  objektbuch  harvard  princeton  elite  stanford 
july 2017 by nhaliday
COS597C: How to solve it
- Familiarity with tools. You have to know the basic mathematical and conceptuatl tools, and over the semester we will encounter quite a few of them.
- Background reading on your topic. What is already known and how was it proven? Research involves figuring out how to stand on the shoulders of others (could be giants, midgets, or normal-sized people).
- Ability to generate new ideas and spot the ones that dont work. I cannot stress the second part enough. The only way you generate new ideas is by shooting down the ones you already have.
- Flashes of genius. Somewhat overrated; the other three points are more important. Insights come to the well-prepared.
course  tcs  princeton  yoga  👳  unit  toolkit  metabuch  problem-solving  sanjeev-arora  wire-guided  s:*  p:** 
october 2016 by nhaliday
Mental Wilderness | Holden Lee
Holden Lee takes a lot of amazing notes (both live-TeXed and in Workflowy): https://pinboard.in/u:nhaliday/b:ca7feec10ca8

also he wrote that pretty inspirational essay a while back
people  students  princeton  math  tcs  notetaking  homepage  blog  todo  phd  oly  mathtariat  multi 
june 2016 by nhaliday
Graduate Program | Computer Science Department at Princeton University
Sanjeev Arora and his new research group, Mark Braverman (algorithmic econ+ML-type stuff), Moses Charikar, Elad Hazan (the kind of ML i like), and Zeev Dvir (more of a mathematician)
schools  phd  princeton  grad-school  cs  fall-2016 
april 2016 by nhaliday

bundles : academe

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