TimeGazer: Temporal Modeling of Predictive Gaze Stabilization for AR Interaction

Wed, 01 Oct 2025 00:00:00 +0000

arXiv:

机器学习

Mon, 01 Sep 2025 00:00:00 +0000

A 40-hour elective for first-year graduate students, designed to establish a foundation for research in pattern recognition and machine learning. The course uses Python.

Course Information

Statistical Learning

Unit	Topic	Files
01	Machine Learning and Statistical Learning
02	Perceptron
03	k-Nearest Neighbors
04	Bayesian Classifiers
06	Logistic Regression and Maximum Entropy
07	Support Vector Machines and Kernels
09	Expectation-Maximization	· ·
13	Unsupervised Learning
14	Clustering
15	Singular Value Decomposition	·
16	Principal Component Analysis
Appendix	Distribution Measures

Supplementary materials:

Deep Learning

These lectures refer to the and its .

Unit	Topic	Files
01	Overview, Linear Algebra, and NDArray
03	Derivatives, Backpropagation, and Complexity
04	Linear Methods and Optimization
05	Maximum Likelihood and Logistic Regression
06	Multilayer Perceptrons
08	Numerical Stability, Activations, and Hardware
11	Convolution and Pooling
12	LeNet, AlexNet, VGG, and NiN
13	Inception, Batch Normalization, and Residual Networks
15	Image Augmentation, Fine-Tuning, and Style Transfer
16	Object Detection and Training Techniques
18	Sequence Models
19	Recurrent Neural Networks
20	Advanced Recurrent Neural Networks
24	Attention and Vision Transformers	·
25	Optimization

Language Models

Generative Models

3D Vision

Covered topics include ray tracing of volume densities, EWA volume splatting, NeRF, and 3D Gaussian Splatting.

Assignments

References

Hang Li, Statistical Learning Methods, 2nd edition, Tsinghua University Press, 2019.
Hang Li, Machine Learning Methods, Tsinghua University Press, 2022.
Aston Zhang et al., Dive into Deep Learning, PyTorch edition, Posts & Telecom Press, 2023.
Koki Saitoh, Deep Learning from Scratch, Posts & Telecom Press, 2018.

Machine Learning | Shaorong Wang | Visual Computing