Inspired from lil’log and feynman’s technique, I started to log things I learn here.

Note: I have started digitising my notes at the start of covid break. So, many of these might be incomplete. Hopefully I would complete it by the end of the outbreak

Paper-summaries

These are unorganised. These mostly include the papers I read for some of my projects. I will try to organise them in a few days

• Graphical Models

  • DAG with NOTEARS
  • Continuous time bayesian networks

• Optimisation

  • Small Steps and Giant Leaps: Minimal Newton Solvers for Deep Learning
  • Underdamped Langevin MCMC: A non-asymptotic analysis
  • Why random reshuffling beats stochastic gradient descent
  • SGD Without Replacement
  • Global Convergence of SGHMC for Non-Convex Stochastic Optimisation
  • Nonlinear Gossip

• Active Learning

  • Deep Bayesian Active Learning for Multiple Correct Outputs
  • Bayesian representation learning with oracle constraints

• Generalisation

  • Deep Learning generalises because the parameter - function map is biased towards simple functions

• Algebra

  • Generalised Solutions for Sylvester Equations
  • Iterative Methods for solving Sylvester Equations

• Reinforcement Learning

  • On the Role of Tracking in Stationary environments

• ASR

  • Audio-Visual Scene Analysis with Self-Supervised Multisensory Features

My-Notes

These are some write-up’s by me, Again these will be organised in somedays

• Gaussian Processes an Overview
• Active Learning
• Perceptual Distance Metric Learning
• Solving Sylvester Equations
• Stochastic Approximation - 1
• Stochastic Approximation - 2
• Imitation Learning for Robotic Surgery
• Brownian Motion
• Distributed Stochastic Gradient Methods

---

Presentations

• Undergrad Project - 1
• Undergrad Project - 2
• RnD - 1
• RnD - 2

---

Non-Technical

• Procrastination and Scheduling
• Learning Piano
• Mentalism and Mind Reading
• A mind of a Mnemonist - book summary
• Codingame - pod control
• What everybody is saying - book summary
• Learning Japanese

---

Resources

• The Yossil Gil LateX Guide for Graduate Students
• Piano Video Lessons by Lisa Pianista
• Bash Scripting Tutorial by Ryan Chadwick
• Self Authoring Program by Jordan Peterson
• Markov Chains in Latex by Steven Thornton