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JMLR
2010
132views more  JMLR 2010»
13 years 2 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...
WABI
2009
Springer
128views Bioinformatics» more  WABI 2009»
14 years 2 months ago
Improving Inference of Transcriptional Regulatory Networks Based on Network Evolutionary Models
Abstract. Computational inference of transcriptional regulatory networks remains a challenging problem, in part due to the lack of strong network models. In this paper we present e...
Xiuwei Zhang, Bernard M. E. Moret
CCS
2003
ACM
14 years 29 days ago
Incentive-based modeling and inference of attacker intent, objectives, and strategies
Although the ability to model and infer Attacker Intent, Objectives and Strategies (AIOS) may dramatically advance the literature of risk assessment, harm prediction, and predicti...
Peng Liu, Wanyu Zang
ICASSP
2011
IEEE
12 years 11 months ago
On the success of network inference using a markov routing model
In this paper we discuss why a simple network topology inference algorithm based on network co-occurrence measurements and a Markov random walk model for routing enables perfect t...
Laura Balzano, Robert Nowak, Matthew Roughan
AAAI
2000
13 years 9 months ago
Modeling Classification and Inference Learning
Human categorization research is dominated by work in classification learning. The field may be in danger of equating the classification learning paradigm with the more general ph...
Bradley C. Love, Arthur B. Markman, Takashi Yamauc...