About CLLab
CLLab works on machine learning, the study that allows computational systems to adaptively improve their performance with experience accumulated from the data observed—external examples, feedback of the environment, or other pieces of information. The importance of machine learning is rapidly and continuously growing with collaboration opportunities on a broad spectrum of applications inside and outside of computer science. In multimedia, machines can learn to construct semantic structures of digital contents to help users in their search for the desired scene. In architecture, machines can learn to effectually manage computing resources, such as the laptop battery, based on the working pattern of the owner. In bioinformatics, machines can learn to identify cancer genes and suggest promising medicines. In e-commerce, machines can learn the preference of each individual customer and show targeted advertisements.
Fundamental machine learning research is driven by the following three major questions (directions):
- How broadly can machines learn? (application)
- How efficiently can machines learn? (algorithm)
- How precisely can machines learn? (theory)
Research in CLLab usually starts from one of the directions above and then extends freely to other interconnected directions. Our goal is to develop state-of-the-art tools for various learning tasks based on sound theoretical principles. Some of our ongoing success stories include studies on ranking and cost-sensitive classification.
Feel free to send an email to 
if you are interested in joining the CLLab!
News
- (2009/09/20) Congratulations to Hsuan-Tien for getting formally engaged.
- (2009/09/05) Congratulations to Chao-Kai for getting a SODA paper.
- (2009/06/29) Congratulations to Ken-Yi, Chun-Sung, Chia-Hsuan, Shang-Tse, and Hsuan-Tien for being part of the team that wins the third place in the slow track of KDDCup 2009.
- (2009/06/23) Congratulations to Chun-Sung, Chia-Hsuan, and Shang-Tse for getting their undergraduate research proposals approved by the NSC.
- (2009/06/19) Congratulations to Hsuan-Tien for getting the outstanding teacher award, given by the students of the course Machine Learning 2008 Fall.
- (2009/06/17) Congratulations to Ming-Feng and Hanhsing for getting the excellent TA award (of the course Machine Learning 2008 Fall) from NTU CSIE.
- (2009/06/05) Congratulations to Hanhsing for finishing the lab's first student-written conference paper.
Learners
Absolute Learner
Hsuan-Tien Lin (2008.08–)
Associate Learner
Chao-Kai Chiang (2008.09–; co-advise with Dr. Chi-Jen Lu at Institute of Information Science, Sinica)
Assistant Learner
Te-Kang Jan (2008.09–), KenYi Lin (2008.09–) 
, Chen-Wei Hung (2009.09–), Yu-Xun Ruan (2009.09–)
Active Learner
Chia-Hsuan Wang (2009.02–), Chun-Sung Ferng (2009.02–), Joseph Wen (2009.05–), Shang-Tse Chen (2009.05–), Yao-Nan Chen (2009.05–), Polone Chen (2009.08–)
Attentive Learner
Farbound Tai (2009.05–), Hanhsing Tu (2009.08–; Assistant 2008.08–2009.07)
Affiliate Learner
Ming-Feng Tsai (2008.09–2009.08 from NTU CSIE Natural Language Processing Laboratory), Yi-Hung Huang (2009.10 from IIS Sinica AIIA Lab)
