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'''Wee Sun Lee''',<ref>Lee Wee Sun in Asian standard template [LAST NAME][FIRST NAME]</ref><br/>
a Singaporean computer scientist and professor at the department of computer science of [https://en.wikipedia.org/wiki/National_University_of_Singapore National University of Singapore].
He holds a Ph.D. in computer science from [[Australian National University]] in 1996 with the thesis title ''Agnostic Learning and Single Hidden Layer Neural Networks'' under supervision of [[Mathematician#PBartlett|Peter Bartlett]] and [[Mathematician#RCWilliamson|Robert C. Williamson]].
His research interests include [[Learning|machine learning]] theory and applications, and [[Planning|planning]] under uncertainty. Along with his Ph.D. student [[Yew Jin Lim]], he published on [[Pruning|Forward Pruning]] in [[Search|Game-Tree Search]], in particular on [[RankCut]].
<ref>[http://www.comp.nus.edu.sg/%7Eleews/publications/publications.html Lee Wee Sun - Publications]</ref> <ref>[https://dblp.uni-trier.de/pers/hd/l/Lee:Wee_Sun.html dblp: Wee Sun Lee]</ref>
==1995 ...==
* [[Wee Sun Lee]], [[Mathematician#PBartlett|Peter Bartlett]], [[Mathematician#RCWilliamson|Robert C. Williamson]] ('''1995'''). ''On Efficient Agnostic Learning of Linear Combinations of Basis Functions''. [https://dblp.uni-trier.de/db/conf/colt/colt1995.html COLT 1995], [http://users.cecs.anu.edu.au/~williams/papers/P68.pdf pdf]* [[Wee Sun Lee]], [[Mathematician#PBartlett|Peter Bartlett]], [[#RCWilliamsonMathematicianRCWilliamson|Robert C. Williamson]] ('''1996'''). ''The Importance of Convexity in Learning with Squared Loss''. [https://dblp.uni-trier.de/db/conf/colt/colt1996.html COLT 1996], [http://users.cecs.anu.edu.au/~williams/papers/P77.pdf pdf]
* [[Wee Sun Lee]] ('''1996'''). ''Agnostic Learning and Single Hidden Layer Neural Networks''. Ph.D. thesis, [[Australian National University]], [http://www.comp.nus.edu.sg/~leews/publications/thesis.ps ps]
* [[Robert Schapire]], [[Yoav Freund]], [[Mathematician#PBartlett|Peter Bartlett]], [[Wee Sun Lee]] ('''1998'''). ''Boosting the margin: A new explanation for the effectiveness of voting methods''. [https://en.wikipedia.org/wiki/Annals_of_Statistics Annals of Statistic], [https://www.cc.gatech.edu/~isbell/tutorials/boostingmargins.pdf pdf]
