Knowledge Discovery and Data Mining Professional Interest Community (KDD PIC) - Seminar
Seminar Talks 2009
Tom Mitchell (CMU): Brains, Meaning and Corpus Statistics
Tim Hancock (Institute for Chemical Research, Kyoto University): A Markov Classification Model for Metabolic Pathways
Mark Schmidt (University of British Columbia): Optimizing Costly Functions with Simple Constraints
Hisashi Kashima (Tokyo Research Labs): A Semi-supervised Learning Algorithm for Link Prediction
Tsuyoshi Ide (Tokyo Research Labs): Recent Research Activities in Data Analyatics at TRL: Sensor Analytics and Simulation Research.
Ping Li (Cornell University): ABC-MART: Recent Improvements in Boosting, Trees and Classification Algorithms
Jerry Zhu (Univ. of Wisc. Madison): HAMLET (Human, Animal, and Machine Learning: Experiment and Theory)
Jie Tang (Tsinghua University): ArnetMiner-Extraction and Mining of Academic Networks
Tong Zhang (Rutgers University): Algorithmic Strategies for Non-convex Optimization in Sparse Learning
Jonathan Chang (Princeton Univ.): Uncovering, understanding, and predicting links
Smile Student Open House
The Statistical Machine Learning and its Applications (SMiLe): Student Open House was held on October 8th and 9th, 2009, at the IBM Thomas J. Watson Research Center in Yorktown Heights, NY.
The event was joint organized by the AI, KDD, NLP, and UIT PICs, and hosted 28 Ph.D. students from top academic institutions in the US. Participants presented their research in 15 minute talks.
Details on the event can be found in the main SMiLe page.