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About CLLab @ Room 536

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 advance machine learning by developing state-of-the-art tools for various learning tasks based on theoretical principles and/or domain knowledge. Some of our past success stories include studies on multi-label classification, ranking, cost-sensitive classification and active learning. We have also been active participants in several data mining and machine learning competitions and several meteorology studies.

Feel free to send an email to if you are interested in joining the CLLab!

Learners

Absolute Learner

Associate Learners (a.k.a. Ph.D. students)

  • 056. Yu-Ying Chou (2018.09–; co-advise with Dr. Tyng-Luh Liu at IIS Sinica)
  • 041. Si-An Chen (2020.09–; Attentive 2019.06–2020.08; Assistant 2016.07–2018.06; Active 2014.12–2016.06); M.S. Thesis: Improving Deep Reinforcement Learning with Uncertainty-Based Interaction with Experts (co-advise with Prof. Masashi Sugiyama at University of Tokyo; 2018 TAAI Best Thesis Award; related publications in MLJ: ECML journal track)
  • 066. Po-Yi Lu (2021.01–)
  • 072. Mai Tan Ha (2021.10–)

Assistant Learners (a.k.a. M.S. students)

  • 065. Yu-Chu Yu (2020.04–)
  • 067. Yu-Hsin Chou (2021.07–)
  • 068. Oscar Chew (2021.07–)
  • 054. Wei-I Lin (2021.08–; Active 2018.02–2021.07)

Active Learners (a.k.a. undergraduate students)

  • 069. Hsin-Kai Lin (2021.07–)
  • 070. Ming-Hsin Chen (2021.07–)
  • 073. Kuo-Ming Huang (2022.02–)
  • 074. Cheng-Ying Chang (2022.02–)
  • 075. Hsiu-Hsuan Wang (2022.10–)
  • 076. Nai-Xuan Ye (2022.10–)
  • 077. Huai-Yuan Kuo (2022.10–)

Attentive Learners (a.k.a. research assistants)

Alumni Learners

  • 001. Han-Hsing Tu (Assistant 2008.08–2009.07; Attentive 2009.08–2011.02; now in Cellopoint); M.S. Thesis: Regression Approaches for Multi-class Cost-sensitive Classification (related publications in ICML)
  • 002. Dr. Te-Kang Jan (Assistant 2008.09–2010.07; Attentive 2010.08–2011.04; joint RA with Academia Sinica 2011.05–2014.05; Ph.D. from Virginia Tech; now in Amazon); M.S. Thesis: A Comparison of Methods for Cost-sensitive Support Vector Machines (related publications in KDD)
  • 003. Ken-Yi Lin (Assistant 2008.09–2010.07; now in Delta IOT); M.S. Thesis: Data Selection Techniques for Large-scale RankSVM (related publications in TAAI)
  • 004. Dr. Chao-Kai Chiang (Associate 2008.09–2013.12; co-advise with Dr. Chi-Jen Lu at IIS Sinica; Ph.D. from NTU; now in University of Tokyo); Ph.D. Thesis: Toward Realistic Online Learning (2014 TAAI Best Thesis Award; related publications in SODA, COLT, ACML)
  • 005. Dr. Chia-Hsuan Wang (Active 2009.02–2010.06; Ph.D. from Johns Hopkins; now in RIKEN Center for Brain Science)
  • 006. Chun-Sung Ferng (Active 2009.02–2010.06; Assistant 2010.07–2012.06; now in Google); M.S. Thesis: Multi-label Classification with Hard-/soft-decoded Error-correcting Codes (related publications in IEEE TNN)
  • 007. Farbound Tai (Attentive 2009.05–2010.07; now in Facebook)
  • 008. Joseph Wen (Active 2009.05–2010.06; now in Google)
  • 009. Dr. Shang-Tse Chen (Active 2009.05–2010.06; joint RA with Academia Sinica 2011.07–2013.06; Ph.D. from Georgia Tech; now assistant professor at NTU)
  • 010. Yao-Nan Chen (Active 2009.05–2010.06; Assistant 2010.07–2012.06; now in Appier); M.S. Thesis: Feature-aware Label Space Dimension Reduction for Multi-label Classification Problem (related publications in NeurIPS)
  • 011. Po-Lung Chen (Active 2009.08–2010.06; Assistant 2010.07–2012.06; now in Instagram); M.S. Thesis: Active Learning for Multiclass Cost-sensitive Classification Using Probabilistic Models (related publications in TAAI)
  • 012. Chen-Wei Hung (Assistant 2009.09–2011.08; now in AlpacaTech); M.S. Thesis: Multi-label Active Learning with Auxiliary Learner (related publications in ACML)
  • 013. Yu-Xun Ruan (Assistant 2009.09–2011.08; now in Vivotek); M.S. Thesis: Studies on Ordinal Ranking with Regression (related publications in Information Retrieval)
  • 014. Dr. Yi-Hung Huang (Associate 2009.10–2015.12; Ph.D. from NTU; co-advise with Dr. Chun-Nan Hsu at IIS Sinica); Ph.D. Thesis: A Study of Data Citation (related publications in ICDM, TAAI, PloS one)
  • 015. Yu-Cheng Chou (Active 2010.03–2011.06; Assistant 2011.07–2013.07; now in Google); M.S. Thesis: Machine Learning Approaches for Interactive Verification (related publications in PAKDD)
  • 016. Ku-Chun Chou (Assistant 2010.05–2013.07; now in Kabam); M.S. Thesis: Pseudo-reward Algorithms for Linear Contextual Bandit Problems (related publications in ACML)
  • 017. Kuan-Sung Huang (Active 2010.05–2011.06; joint RA with Academia Sinica 2013.07–2015.06; now in Facebook)
  • 018. Wei-Yuan Shen (Active 2010.05–2011.06; Assistant 2011.07–2013.07; now in Microsoft); M.S. Thesis: Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking (2013 TAAI Best Thesis Award; related publications in ACML)
  • 019. Ya-Hsuan Chang (Active 2010.06–2011.06; Assistant 2011.07–2013.07; now in Bridgewell); M.S. Thesis: Study on Contextual Bandit Problem with Multiple Actions (related publications in TAAI)
  • 020. Chun-Yen Ho (Active 2010.07–2012.06; Assistant 2012.07–2014.06; now in Google); M.S. Thesis: Contract Bridge Bidding by Learning (related publications in Workshop on Computer Poker and Imperfect Information @ AAAI)
  • 021. Dr. Chun-Liang Li (Active 2011.01–2012.06; Assistant 2012.07–2013.07; joint RA with Academia Sinica 2013.08–2014.07; Ph.D. from CMU; now in Google); M.S. Thesis: Condensed Filter Tree For Cost Sensitive Multi-Label Classification (2013 TAAI Best Thesis Award; related publications in ICML)
  • 022. Yi-Wen Huang (Active 2011.06–2012.06; Assistant 2012.07–2012.09)
  • 023. Han-Jay Yang (Active 2012.02–2012.06; Assistant 2012.07–2014.06; now in Google); M.S. Thesis: A Practical Divide-and-Conquer Approach for Preference-Based Learning to Rank (related publications as Best Paper Award of TAAI 2015)
  • 024. Kuan-Hao Huang (Active 2012.06–2014.06; Assistant 2014.07–2016.06; now a PhD student at UCLA); M.S. Thesis: Cost-sensitive Label Embedding for Multi-label Classification (2016 TAAI Thesis Award Honorable Mention; related publications in MLJ: ECML journal track, ICDM)
  • 025. Yi-An Lin (Active 2013.02–2014.01; Assistant 2014.02–2016.01; now in Microsoft); M.S. Thesis: Cyclic Classifier Chain for Multilabel Classification (related publications in DSAA)
  • 026. Sheng-Chi You (Assistant 2013.07–2015.06; now in Synopsys); M.S. Thesis: Dynamic Unlearning for Online learning on Concept-drifting Data (related publications in PAKDD)
  • 027. Meng-Huan Yu (Active 2013.08–2014.12; now in Google)
  • 028. Dr. Yao-Yuan Yang (Active 2013.08–2016.06; Ph.D. from UCSD; now in DeepMind)
  • 029. Yu-Ping Wu (Active 2013.08–2014.01; Assistant 2014.02–2016.01; now in Google); M.S. Thesis: Progressive Random k-Labelsets for Cost-Sensitive Multi-Label Classification (related publications in MLJ: ACML journal track)
  • 030. Dr. Yu-An Chung (Active 2013.08–2016.06; Ph.D. from MIT; now in Meta Research)
  • 031. Dr. Wei-Ning Hsu (Active 2013.08–2014.06; Ph.D. from MIT; now in Meta Research)
  • 032. Hsuan-Li Ren (Active 2013.08–2014.01)
  • 033. Chih-Wei Chang (Active 2014.02–2015.06; now in Facebook)
  • 034. Hong-Min Chu (Active 2014.02–2015.06; Assistant 2015.07–2017.07; now a PhD student at UMD); M.S. Thesis: Dynamic Principal Projection for Cost-sensitive Online Multi-label Classification (related publication in MLJ: ECML journal track)
  • 035. Yu-Jeng Fang (Active 2014.02–2016.07; now in Bloomberg)
  • 036. Yu-Lin Tsou (Active 2014.02–2015.01; Assistant 2015.02–2017.07; now in Microsoft); M.S. Thesis: Annotation Cost-sensitive Active Learning by Tree Sampling (2017 TAAI Thesis Award Honorable Mention; related publications in MLJ: ACML journal track)
  • 037. Kuo-Hsuan Lo (Assistant 2014.04–2017.01; now in mcFallout); M.S. Thesis: Cost-sensitive Encoding for Label Space Dimension Reduction Algorithms on Multi-label Classification (2017 TAAI Thesis Award Honorable Mention; related publications in TAAI)
  • 038. Shao-Chuan Lee (Active in Open Source Track 2014.07–2015.07, now in Google)
  • 039. Chin-Huang Lin (Active 2014.07–2017.06)
  • 040. Tung-En Wu (Attentive 2014.10–2016.04)
  • 042. Dr. Chih-Kuan Yeh (Active 2015.04–2016.07; Ph.D. from CMU; now in Google)
  • 043. Hsien-Chun Chiu (Assistant 2015.07–2017.10; Active 2014.12–2015.06; now in Google); M.S. Thesis: Multi-label Classification with Feature-aware Cost-sensitive Label Embedding (related publications in TAAI)
  • 044. Cheng-Yu Hsieh (Assistant 2016.02–2018.07; Attentive 2018.08–2019.09; now a Ph.D. student at UWashington); M.S. Thesis: A Deep Model with Local Surrogate Loss for General Cost-sensitive Multi-label Learning (related publications in AAAI)
  • 045. Yu-Shao Peng (Assistant 2016.07–2018.07; now in HTC DeepQ); M.S. Thesis: Exploring Sparse Features in Deep Reinforcement Learning towards Fast Disease Diagnosis (2018 TAAI Thesis Award Honorable Mention; related publications in NeurIPS)
  • 046. Boyo Chen (Assistant 2016.07–2018.07; now in UTokyo); M.S. Thesis: Tropical Cyclone Intensity Estimation With Specialized Convolutional Neural Network (related publications in KDD, Weather and Forecasting)
  • 047. Yu-Ting Chou (Active 2016.07–2018.07; Assistant 2018.08–2020.08; now in Kronos); M.S. Thesis: A New Surrogate Loss Framework for Complementary Learning (co-advise with Prof. Masashi Sugiyama at University of Tokyo; 2020 TAAI Best Thesis Award; related publications in ICML)
  • 048. Chia-You Chen (Active 2017.03–2018.07; Assistant 2018.08–2020.08; now in Google); M.S. Thesis: Improving Meta-Learning by Regularized Pre-training (related publications in Workshop on Meta-Learning @ NeurIPS)
  • 049. I-Ting Chen (Assistant 2017.07–2019.08; now in HTC DeepQ); M.S. Thesis: Improving Unsupervised Domain Adaptation with Representative Selection Techniques (related publications in Workshop on Interactive Adaptive Learning @ ECML/PKDD)
  • 050. Kuen-Han Tsai (Assistant 2017.07–2019.10; now in Google); M.S. Thesis: Learning from Label Proportions with Consistency Regularization (related publications in ACML)
  • 051. Chien-Min Yu (Active 2017.07–2018.07; Assistant 2018.08–2020.08; now in Cubist); M.S. Thesis: Learning Key Steps to Attack Deep Reinforcement Learning Agents (related publications submitted)
  • 052. Chun-Yi Tu (Active 2017.07–2019.02; now in Verizon)
  • 053. Jyun-Gu Ye (Associate 2018.02–2019.06)
  • 055. Ching-Yuan Bai (Active 2018.08–2021.08, now a PhD student at UCLA)
  • 057. Wei-Chao Cheng (Assistant 2019.03–2021.07, now in Synopsys); M.S. Thesis: From SMOTE to Mixup for Deep Imbalanced Classification (related publications submitted)
  • 058. Sheng-Feng Wu (Assistant 2019.07–2021.12; now in Qualcomm); M.S. Thesis: Improving Clustering Uncertainty-weighted Embeddings for Active Domain Adaptation (related publications in TAAI)
  • 059. Dr. Michelle Yuan (Attentive 2019.09–2020.10; visited from UMD; now in Amazon)
  • 060. Chi-Chang Lee (Assistant 2019.12–2021.02)
  • 061. Pin-Yen Huang (Assistant 2019.12–2022.09)
  • 062. Ashesh (Attentive 2020.01–2021.06; now a Ph.D. student at MPI)
  • 063. Chi-Fan Lo (Active 2020.02–2022.06; now a MSCS student at CMU)
  • 064. Li-Heng Lin (Active 2020.06–2022.06; now a MS student at Stanford)
  • 071. Feng-Yi Wang (Active 2021.09–2022.09)

Affiliate Learner

  • Dr. Ming-Feng Tsai (2008.09–2009.08 from NTU CSIE Natural Language Processing Laboratory; now an Associate Professor at National Cheng-Chi University)
  • Yu-Chiao Huang (Cloud Computing Program, 2011.03–2011.06)
  • Che-Chun Lee (Cloud Computing Program, 2010.09–2011.06)
  • Yan-Shan Lin (Cloud Computing Program, 2012.09–2013.01)
  • Chi-Hsien Yen (Cloud Computing Program, 2012.09–2013.01)

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start.txt · Last modified: 2022/11/28 06:03 by lupoy