lab meeting, wednesday

note meeting time: 11am

10am: skype call with adam2. adam2-
11am: meeting
1pm: break
1:45pm: bryan's defense. (edited by Bryan L. to correct time. Its 1:45, not 2:00)

newbies (make them welcome)

• Kel Cecil
• Charles Corb
• Tomi Prifti

adam1:

• promise paper
• travel arrangements to bejing

timm:

• the vision thing Structured Machine Learning: Ten Problems for the Next Ten Years (Section 5 in Structured Machine Learning: The Next Ten Years). Machine Learning, 73, 3-23, 2008.
• journal paper
  
  
  
  
  

  1) Stable rankings for different effort models ;
  2) Defect prediction from static code features: current results, limitations, new approaches

  3) How to Understand Complex Models
• dod sttrt2
• clustering as compression
  Towards Parameter-Free Data Mining
  Clustering by Compression
  Compression and Machine Learning: A New Perspective on Feature Space Vectors
  Parameterless Outlier Detection in Data Stream
• temporal data mining and anomaly detection
  the joy of sax: Visually Mining and Monitoring Massive Time Series
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  

tomi:

• what news?

fayola:

• did not understand your last explanation of your distance measure (i.e. is 20% more or less movement). help me, please, to obtain clarity
• does your result hold as you increase number of clusters?
• starting 3 papers

ekrem, andrew:

• start a sub-group: active learning.
• begin lit reviewing
• that experiment with people in front of interfaces..

andrew-

• what news on ddp?
• papers for comparing compass against other clusterers:
  Evalaution of Hierarchical Clustering
  A Comparison of Document Clustering Techniques

ekrem:

• what news on using teac as an instance selector for other data miners

william:

• effort estimation data table
• -instance collection environment