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ICML
2007
IEEE
15 years 11 months ago
Dynamic hierarchical Markov random fields and their application to web data extraction
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
ICML
2007
IEEE
15 years 11 months ago
Multiclass core vector machine
Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these appr...
S. Asharaf, M. Narasimha Murty, Shirish Krishnaj S...
ICML
2007
IEEE
15 years 11 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
ICML
2007
IEEE
15 years 11 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
ICML
2007
IEEE
15 years 11 months ago
Cluster analysis of heterogeneous rank data
Cluster analysis of ranking data, which occurs in consumer questionnaires, voting forms or other inquiries of preferences, attempts to identify typical groups of rank choices. Emp...
Ludwig M. Busse, Peter Orbanz, Joachim M. Buhmann