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The code written on the understanding of the paper: "Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples"
EKF SLAM USING KNOWN AND UNKNOWN CORRESPONDENCES
Run the 'run.m' file in the hw3p3 folder, this is the main driver The train data should be placed in the same folder as of 'run.m' 1) train-images.idx3-ubyte 2) train-labels.idx1-ubyte The test data for the MNIST dataset should be in the same folder as of 'run.m' 1) t10k-images.idx3-ubyte 2) t10k-labels.idx1-ubyte FOR SVHN DATASET, SPECIFY THE PATH THAT CONTAINS THE TEST IMAGES ON LINE 106 OF 'run.m' INCLUDE digitStruct.mat in the same folder as 'run.m' THE HELPER FUNCTIONS are in the same folder as 'run.m' 1) loadMNISTLabels 2) loadMNISTImages 3) display_network
K-NN built without the use of inbuilt functions
Repositories
5The code written on the understanding of the paper: "Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples"
EKF SLAM USING KNOWN AND UNKNOWN CORRESPONDENCES
Run the 'run.m' file in the hw3p3 folder, this is the main driver The train data should be placed in the same folder as of 'run.m' 1) train-images.idx3-ubyte 2) train-labels.idx1-ubyte The test data for the MNIST dataset should be in the same folder as of 'run.m' 1) t10k-images.idx3-ubyte 2) t10k-labels.idx1-ubyte FOR SVHN DATASET, SPECIFY THE PATH THAT CONTAINS THE TEST IMAGES ON LINE 106 OF 'run.m' INCLUDE digitStruct.mat in the same folder as 'run.m' THE HELPER FUNCTIONS are in the same folder as 'run.m' 1) loadMNISTLabels 2) loadMNISTImages 3) display_network
K-NN built without the use of inbuilt functions
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