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Homepage of Xiaotian YU (余晓填) at CUHK
Ph.D. Candidate (Aug. 2014 ~ )
Biography
- Biography
- Curriculum Vitae
- Research Interests
- Teaching and Industrial Experiences
- Education
- Personal Hobby
Rm 1024, Ho Sin-Hang Engineering Building,
Department of Computer Science and Engineering,
CUHK, N.T., Hong Kong
Email: xtyu@cse.cuhk.edu.hk
Research Projects
- Project Descriptions
- Project Demo
Publications
Journal Publications
Book Chapters
Conference Publications
Technical Reports
Miscellaneous
Books on Optimization, Online Learning and Deep Learning
Deterministic Optimization
1. Nesterov, Yurii. Introductory lectures on convex optimization: A basic course. (2004)
https://link.springer.com/book/10.1007%2F978-1-4419-8853-9
2. Boyd, Stephen, and Lieven Vandenberghe. Convex optimization. (2004)
https://web.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf
Stochastic Convex Optimization
1. Duchi, John. Introductory lectures on stochastic optimization. (2009)
https://stanford.edu/~jduchi/PCMIConvex/Duchi16.pdf
2. Ben-Tal, Aharon, Laurent El Ghaoui, and Arkadi Nemirovski. Robust optimization. (2009)
https://sites.google.com/site/robustoptimization/
Online Learning and Online Convex Optimization
1. Shalev-Shwartz, Shai. Online learning and online convex optimization. (2011)
http://www.cs.huji.ac.il/~shais/papers/OLsurvey.pdf
2. Bubeck, Sébastien. Convex optimization: Algorithms and complexity. (2014)
https://arxiv.org/abs/1405.4980
3. Hazan, Elad. Introduction to online convex optimization. (2016)
http://ocobook.cs.princeton.edu/OCObook.pdf
Learning Theory and Bandits
1. Cesa-Bianchi, Nicolo, and Gábor Lugosi. Prediction, learning, and games. (2006)
http://www.ii.uni.wroc.pl/~lukstafi/pmwiki/uploads/AGT/Prediction_Learning_and_Games.pdf
2. Bubeck, Sébastien, and Nicolo Cesa-Bianchi. Regret analysis of stochastic and nonstochastic multi-armed bandit problems. (2012)
https://arxiv.org/pdf/1204.5721.pdf
3. Shalev-Shwartz, Shai, and Shai Ben-David. Understanding machine learning: From theory to algorithms. (2014)
http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf