This workshop has concluded!
The International Workshop on Data-Mining and Statistical Science (DMSS2007) will be held at the Institute of Statistical Mathematics, Tokyo, Japan on October 5 and 6, 2007.
- Oct. 5 - 6, 2007
- The Institute of Statistical Mathematics
- Registration fee:
The recent development of information technology enables us to access a wide variety of data through computer networks. Along with that, the amount of data that are generated, collected and stored has been rapidly increasing, and the issue of how to analyze and utilize them becomes more and more important. One potent approach is application of data mining technology that enables us to `mine' significant knowledge from a large amount of data.
We have dealt with many studies on data mining in various workshops such as SIG-KBS and SIG-FPAI in JSAI. In response to the further broadening of researches on data mining, we newly started the workshop "data mining and statistical mathematics (SIG-DMSM)." This workshop deals with data mining based on statistical approach as well as machine learning, and aims at bringing together machine learning researchers and statisticians to synthesize both approaches and creating new data mining technologies. We solicit papers addressing theoretical and methodological aspects of machine learning, statistical science, and their relevant fields, which contribute to understanding and development of data mining.
Topics of interest
include, but not limited to, the following areas:
Statistical modeling, Bayesian modeling, Machine Learning, Probablistic Reasoning, Statistical Reasoning, Data Mining, Data Visualization, Applications of Data Mining and Statistical Sciences to real world tasks, e.g., Bioinformatics and Marketing. Any researches on Data Mining and Statistical Sciences.
- Alexander J. Smola (National ICT Australia/ANU, Canberra, Australia)
"Machine learning for Web page ranking and collaborative filtering" (presentation slides[PDF])
- Jean-Philippe Vert (Centre for Computational Biology, ParisTech - Ecole des Mines de Paris, France)
"Statistical learning with graph kernels" (abstract) (presentation slides[PDF])
- Paul Sheridan and Hidetoshi Shimodaira (Department of Mathematical and Computing Sciences, Tokyo Institute of Technology)
"Scale-free network priors in Bayesian inference with applications to Bioinformatics"