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Course Materials - Spring 2025

ML813:Topics in Dimensionality Reduction and Manifold Learning

 TB = Textbook or Required reading                     REF = Reference or supplemental reading

Type ..................... Title

eBook

Print  

Call Number
Image of the cover of the book 'Elements of Dimensionality Reduction and Manifold Learning'

B. Ghojogh, M. Crowley, F. Karray, and A. Ghodsi, Elements of Dimensionality Reduction and Manifold Learning. Cham, Switzerland: Springer Nature, 2023.

 

 Springer On Order
Image of the cover of the book 'Foundations of Machine Learning, second edition'

M. Mohri, A. Rostamizaheh, and A. Talwalkar, Foundations of Machine Learning, MIT, 2018.

 Yes Q325.5 .M64 2018
Chen, Ting, et al. "A simple framework for contrastive learning of visual representations." International conference on machine learning. PMLR, 2020.  A simple framework for contrastive learning of visual representations Open Access NA  
Higgins, Irina, et al. "beta-vae: Learning basic visual concepts with a constrained variational framework." International conference on learning representations. 2016. beta-vae: Learning basic visual concepts with a constrained variational framework NA  
Khemakhem, Ilyes, et al. "Variational autoencoders and nonlinear ica: A unifying framework." International Conference on Artificial Intelligence and Statistics. PMLR, 2020. Variational autoencoders and nonlinear ica: A unifying framework
 
Open Access
 NA  
Khosla, Prannay, et al. "Supervised contrastive learning." Advances in neural information processing systems 33 (2020): 18661-18673. Supervised contrastive learning NA  
Radford, Alec, et al. "Learning transferable visual models from natural language supervision." International conference on machine learning. PMLR, 2021. Learning transferable visual models from natural language supervision
 
Open Access

NA

 

  
Kipf T N, Welling M. Semi-supervised classification with graph convolutional networks[J]. arXiv preprint arXiv:1609.02907, 2016 Semi-supervised classification with graph convolutional networks
 
Open Access		 NA  
Vaswani A, Shazeer N, Parmar N, et al. Attention is all you need[J]. Advances in neural information processing systems, 2017, 30 Attention is all you need NA