Graphical Models

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computer vision

Active Contours Camera Models Color Edge Detection Histogram of Oriented Gradients Hough Transform Image Features Image Segmentation Linear Filters Object Detection Optical Flow Patch Extraction Sampling and Aliasing Scale Invariant Feature Transforms Segmentation via Clustering Stereo Vision Transformers for Computer Vision

gpu programming

CUDA Architecture CUDA Memory Architecture GPU Pattern: Convolution GPU Pattern: Parallel Histogram GPU Pattern: Parallel Scan GPU Pattern: Reduction GPU Pattern: Stencils Heterogeneous Data Parallel Computing Introduction to GPGPU Programming Multidimensional Grids and Data Parallel Sorting Algorithms Profiling CUDA Applications Sparse Matrix Computation

machine learning

Boosting Clustering Convolutional Neural Networks Decision Trees Fine-Tuning LLMs Gradient Boosting Kernels Linear Discriminant Analysis Linear Regression Logistic Regression Markov Decision Processes Naive Bayes Neural Networks Perceptron Policy Gradient Methods Positional Encoding Pretraining Large Language Models Probability Theory Regularization Reinforcement Learning Sequential Minimal Optimization Support Vector Machine

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//Graphical Models

22 Feb 2022
Machine Learning, Graphical Models

Hidden Markov Models

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