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multi_imbalance

Our implementations of the Multi-class Imbalance learning algorithms (for the KBS paper)

multi_task_learning

Multi-task feature learning

multitask-emotion-recognition-with-incomplete-labels

This is the repository containing the solution for FG-2020 ABAW Competition

multitask-representation

Code for experiments in paper "The Benefit of Multitask Representation Learning"

multiview-learning

Multi-view Learning with Vector-valued RKHS - ICML 2013

multiviewlearning

Multi-view learning codes

mura-image-data-generation-and-augmentation

Mura缺陷样本增强

music_eda_emotion

musical-instrument-recognition

Machine Learning Project, using Artificial Neural Networks in Musical instrument Recognition.

musicrecognition

Music Recognition Application using MATLAB

mutual-information-feature-selection

Use mutual information to select features in a Titanic data set

mutual_info_knn

Mutual Information measures using kNN for both continuous and categorical (discrete) variables [Matlab code]

mv-leap

Multi-View LEArning-based data Proliferator (MV-LEAP) for boosting classification using highly imbalanced classes.

mvadl

code for Multi-View Analysis Dictionary Learning for Image Classification

mvcnn

Multi-view CNN (MVCNN) for shape recognition

mvcsc

The source code and synthetic dataset for paper 'Auto-weighted Multi-view Constrained Spectral Clustering'.

mvmrml

Multi-View Multi-Relational Multi-Label Learning

mvod

code for "Latent Discriminant Subspace Representations for Multi-View Outlier Detection, AAAI 2018"

mvpa-light

Matlab toolbox for classification and regression of multi-dimensional data

my_augmentor

Sementic Segmentation data augmentation

ncr-ins2013

Rule learning for classification based on neighborhood covering reduction

nighttime-pedestrian-detection-using-fasterrcnn

Pedestrian detection based on faster R-CNN in nighttime by fusing deep convolutional features of successive images

nndescriptors

A siamese neural network that can learn to discriminate like/unlike image pairs

noise

Generative noise models with fitting functions and functions to produce confidence intervals.

nonlinear-dimensionality-reduction

Computed low-dimensional embedding through a path mapping algorithm by avoiding pairwise geodesic distances where the number of paths are lesser than data points. Produced results with improved time and memory complexity on synthetic and real-world datasets.

object-detection-vehicle

Object Detection using SVM+Sliding Window, YOLO and CNN on Tensorflow

ofse

Online bagging & boosting for feature selection

online-feature-selection-

Feature Selection using Mutual Information for High Dimensional DataSets

online-multiview-clustering-with-incomplete-view

open-aff

code and trained models for "Attentional Feature Fusion"