MATLAB implementations of a variety of machine learning/signal processing algorithms.
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Updated
Aug 24, 2016 - MATLAB
MATLAB implementations of a variety of machine learning/signal processing algorithms.
Matlab implementation of the Adam stochastic gradient descent optimisation algorithm
Implement of SVM using Stochastic gradient descent - Stony Brook CSE512 Machine learning
Train a SVM and for detecting human upper bodies in TV series The Big Bang Theory
Implemented Kernel SVM using Quadratic Programming and Stochastic Gradient Descent
AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)
Code in MATLAB for 1st order optimization algorithms implemented for elastic net regularized convex objective functions.
Simple MATLAB toolbox for deep learning network: Version 1.0.3
Stochastic Gradient Descent implementation for SoftSVM
Neural network-based character recognition using MATLAB. The algorithm does not rely on external ML modules, and is rigorously defined from scratch. A report is included which explains the theory, algorithm performance comparisons, and hyperparameter optimization.
A Single Layer Neural Network to recognize digits making use of unconstrained, non-linear optimization
Images have to be entered in the database using Image Data Collection Program
Single layer perceptron to process images of alphabet letters
Cat vs. car detection with multi-layer NN
Classify 6 types of human activity from time series sensor data
Subsampled Riemannian trust-region (RTR) algorithms
Riemannian stochastic optimization algorithms: Version 1.0.3
OnLine Low-rank Subspace tracking by TEnsor CP Decomposition in Matlab: Version 1.0.1
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
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