| """ Module to compute projections on the positive simplex or the L1-ball | |
| A positive simplex is a set X = { \mathbf{x} | \sum_i x_i = s, x_i \geq 0 } | |
| The (unit) L1-ball is the set X = { \mathbf{x} | || x ||_1 \leq 1 } | |
| Adrien Gaidon - INRIA - 2011 | |
| """ | |
| """ | |
| Implementation of pairwise ranking using scikit-learn LinearSVC | |
| Reference: "Large Margin Rank Boundaries for Ordinal Regression", R. Herbrich, | |
| T. Graepel, K. Obermayer. | |
| Authors: Fabian Pedregosa <fabian@fseoane.net> | |
| Alexandre Gramfort <alexandre.gramfort@inria.fr> | |
| """ |
| # Configure this makefile if needed then run | |
| # $ make all | |
| # to compile and link | |
| # What files to compile | |
| OBJS=money.cpp | |
| # What file to compile to | |
| MAINFILE=money | |
| # What compiler to use | |
| CC=g++ |
| #include "std_try.h" | |
| #include <math.h> | |
| using namespace Halide; | |
| #define PI 3.14159 | |
| /* | |
| Interpolations | |
| */ |
| /* Turn off features that will not work on Windows. | |
| */ | |
| #define NGETRUSAGE | |
| #define NALLSIGNALS |
| Copyright 2013 Robert T. McGibbon | |
| Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: | |
| The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. | |
| THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE O |
This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.
The script is here:
#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"
| """l-bfgs-b L1-Logistic Regression solver""" | |
| # Author: Vlad Niculae <vlad@vene.ro> | |
| # Suggested by Mathieu Blondel | |
| from __future__ import division, print_function | |
| import numpy as np | |
| from scipy.optimize import fmin_l_bfgs_b |
| """ | |
| License: BSD | |
| Author: Mathieu Blondel | |
| Implements three algorithms for projecting a vector onto the simplex: sort, pivot and bisection. | |
| For details and references, see the following paper: | |
| Large-scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex | |
| Mathieu Blondel, Akinori Fujino, and Naonori Ueda. |
| """ | |
| Implementations of: | |
| Probabilistic Matrix Factorization (PMF) [1], | |
| Bayesian PMF (BPMF) [2], | |
| Modified BPFM (mBPMF) | |
| using `pymc3`. mBPMF is, to my knowledge, my own creation. It is an attempt | |
| to circumvent the limitations of `pymc3` w/regards to the Wishart distribution: |