{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# Course Outline and Administrative Issues\n", "\n", "### Adaptive Information Processing (5SSB0)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### AIP Logistic Issues\n", "\n", "- **When**: 3rd quartile, at $8$ weeks of $4$ hours per week.\n", "\n", "- **Load**: Total workload is 5 ECTS $\\Rightarrow 5\\times 28 \\text{[hrs/ECTS]} = 140$ hours or $140/32 \\approx 4.4$ study hours per lecture.\n", "\n", "- **Web**: [http://www.5ssb0.nl](http://www.5ssb0.nl) (or goto teaching tab at [http://biaslab.org](http://biaslab.org) ) \n", "\n", "- **Feedback**: The source materials for these lecture notes are at https://github.com/bertdv/AIP-5SSB0 . Please file a github issue if something is wrong or just unclear in these notes." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Course comes in Two Parts\n", "\n", "##### Part I: **Linear Gaussian Models and the EM Algorithm**\n", "\n", "- $4 \\times 4=16$ lecture hours, mostly in February\n", "- Instructor: [Bert de Vries](http://bertdv.nl), rm. FLUX-7.060 (on Wednesdays)\n", "- email (preferred) or \n", "- Code examples in [Julia](http://julialang.org)\n", "- Consult the **teaching assistants** Ismail Senoz () or Magnus Koudahl () (both in FLUX-7.060) first for help on Julia code examples or exercises." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "##### Part II: **Model Complexity Control and the MDL Principle**\n", "\n", "- $4 \\times 4=16$ lecture hours, mostly in March\n", "- Instructor: Tjalling Tjalkens, rm. FLUX-7.101\n", "- email " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Why Take This Class?\n", "\n", "- Suppose you need to develop an algorithm for a complex DSP task. This is what you'll do:\n", "\n", " 1. Choose a set of candidate algorithms $y=H_k(x;\\theta)$ where $k \\in \\{1,2,\\ldots,K\\}$ and $\\theta \\in \\Theta_k$; (you think that) there's an algorithm $H_{k^*}(x;\\theta^*)$ that performs according to your liking. \n", " 2. You collect a set of examples $D=\\{(x_1,y_1),(x_2,y_2),\\ldots,(x_N,y_N)\\}$ that are consistent with the correct algorithm behavior." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ " \n", "- Using the methods from this class, you will be able to design a suitable algorithm through:\n", " 1. **model selection**, i.e., find $k^*$ (mostly discussed in part 2 of this class)\n", " 2. **parameter estimation**, i.e., find $\\theta^*$ (mostly in part 1 of this class)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Materials\n", "\n", "- Book ([free download link](https://www.microsoft.com/en-us/research/people/cmbishop/#!prml-book)): \n", "\n", "- Background reading; covers about the same stuff as (mandatory) slides.\n", "- Contains much more material; great for future study and reference." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Exam Guide\n", "- Tested material consists of these lecture notes, reading assignments (as assigned in the first cell/slide of each lecture notebook) and exercises (see class website)." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "- Slides that are not required for the exam are indicated by the word (OPTIONAL) in the header." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "- Advice: download (and make free use of) Sam Roweis' cheat sheets for [Matrix identities](https://github.com/bertdv/AIP-5SSB0/blob/master/lessons/notebooks/files/RoweisS-matrix_identities.pdf) and [Gaussian formulas](https://github.com/bertdv/AIP-5SSB0/blob/master/lessons/notebooks/files/RoweisS-gaussian_formulas.pdf)." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "- **Very strong advice**: Make old exams!" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "- You are not allowed to use books nor bring printed or handwritten formula sheets to the exam. Difficult-to-remember formulas are supplied at the exam sheet (see old exams). " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "- You may use a simple pocket calculator, but no smartphones (only arithmetic assistance is allowed.)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "- Further exam instructions for part-2 from Tjalling." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ " " ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "slideshow": { "slide_type": "skip" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "open(\"../../styles/aipstyle.html\") do f\n", " display(\"text/html\", read(f,String))\n", "end" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "celltoolbar": "Slideshow", "kernelspec": { "display_name": "Julia 1.1.0", "language": "julia", "name": "julia-1.1" }, "language_info": { "file_extension": ".jl", "mimetype": "application/julia", "name": "julia", "version": "1.1.0" } }, "nbformat": 4, "nbformat_minor": 1 }