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Machine Learning and Data Mining Are
Everywhere of Our Lives
Game playing and
problem solving
Intelligent virtual environments
for treatment and rehabilitation
Machine Learning
and Data Mining
Industrial and
engineering applications
Medicine, bioinformatics
and systems biology
Homeland security
applications
……
Economics, business and
forecasting applications
My Research in ML and DM
Putative protein
function prediction
Multi-Label
Learning
Image/video/music
tagging
Multi-Instance
Learning
Structured
Sparsity Learning
Disease sensitive
biomarker identification
Drug development
Disease causative
gene prediction
Directed Graph
Learning
Transfer
Learning
Heterogeneous
Data Integration
Video completion
Human emotion
detection
Multi-Relational
Learning
Social network
analysis
Web page ranking
Detect Gene Mutations for Human Diseases
• Many major human diseases, such as cancer and
neurodegenerative disorders, affects millions of people
worldwide.
• Cause of these diseases: gene mutations (such as singlenucleotide polymorphism (SNP) or copy number variations).
Mining Materials Genome Data for Performance
Prediction and Design Guidance of Nanoparticle
Synthesis
Multi-Instance Learning
• The main challenge in MIL is instance-level labeling ambiguity. I tackle this
by proposing a novel Class-to-Bag (C2B) distance.
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Wang et al. AAAI’11
Wang et al. NIPS’11
Wang et al. ACM Multimedia’11
Wang et al. IEEE CVPR’12
Multi-Relational Learning
• Most traditional clustering algorithms concentrate on dealing with
homogeneous data, in which all the objects are of one single type.
• Recently, rapid progress of Internet and computational technologies have
brought Web data much richer in structure, involving objects of multiple
types that are related to each other.
― Wang et al. ACM CIKM’11
― Wang et al. IEEE ICDM’11