Study in first semester

I will make a conclusion about what I learn.

Analytical method in complexity and algorithm

  • Complexity and gradient decent
  • Multiplicative weight update
  • online convex optimization
  • Graphs, Eigenvalues and Laplacians
  • Graph Partition
  • Electrical and combination flow
  • Complexity of Conjugated Gradient method
  • Expectation Maximization and Entropy(KL Divergence)
  • Sparse Coding and Dictionary Learning
  • Neural Network and Back propagation

Scribing lecture notes by my team: Lect2 Scribing Finalized

Distributed Algorithm 6/6

  • reliable broadcast
  • casual broadcast
  • totalorder broadcast
  • consensus
  • non-blocking atomic commit
  • terminating reliable broadcast
  • group membership and view synchronous communication
  • share memory
  • byzantine general problem
  • byzantine fault tolerance and consensus
  • distributed computing in mobile tiny device
  • computability in population protocol
  • coloring and self-stabilization

Intelligent Agent 5/6

  • reactive agents
  • deliberate agents(adversary search, multiarm)
  • factor representation
  • multiagent system
  • distributed multi agent system
  • game theory and nash equilibrium
  • negotiation
  • mechanism
  • agent auction
  • coalition and group decision
  • agent application

Project in Github: https://github.com/OVSS/Intelligent-Agent

Foundation of Software

  • Introduction and Combinator Parsers
  • Arithmetic Expressions
  • The Untyped Lambda Calculus
  • The Simply Typed Lambda Calculus
  • Extensions to STLC
  • Recursion and State in STLC
  • Type Reconstruction and Polymorphism
  • Subtyping
  • Objects
  • Featherweight Java
  • Featherweight Scala

Project in Github:https://github.com/OVSS/Foundation-of-software

Pattern Cognition and machine learning

  • generalized linear model
  • bias and variance decomposition
  • kernel ridge regression
  • support vector machine
  • gaussian mixture model and EM method
  • matrix factorzation
  • SVD and PCA
  • Bayesian Networks and Belief Propagation
  • MLP,CNN,DBN
  • decision tree and random forest
  • gaussian process

Project1: http://icapeople.epfl.ch/mekhan/pcml15/project-1/index.html

Project2: http://icapeople.epfl.ch/mekhan/pcml15/project-2/objectDetection.html