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ICMLA
2009
14 years 10 months ago
Discovering Characterization Rules from Rankings
For many ranking applications we would like to understand not only which items are top-ranked, but also why they are top-ranked. However, many of the best ranking algorithms (e.g....
Ansaf Salleb-Aouissi, Bert C. Huang, David L. Walt...
121
Voted
ACII
2011
Springer
14 years 20 days ago
Investigating the Prosody and Voice Quality of Social Signals in Scenario Meetings
Abstract. In this study we propose a methodology to investigate possible prosody and voice quality correlates of social signals, and test-run it on annotated naturalistic recording...
Marcela Charfuelan, Marc Schröder
97
Voted
ICML
2007
IEEE
16 years 1 months ago
A novel orthogonal NMF-based belief compression for POMDPs
High dimensionality of POMDP's belief state space is one major cause that makes the underlying optimal policy computation intractable. Belief compression refers to the method...
Xin Li, William Kwok-Wai Cheung, Jiming Liu, Zhili...
ICML
2006
IEEE
16 years 1 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
82
Voted
ICML
2003
IEEE
16 years 1 months ago
Adaptive Overrelaxed Bound Optimization Methods
We study a class of overrelaxed bound optimization algorithms, and their relationship to standard bound optimizers, such as ExpectationMaximization, Iterative Scaling, CCCP and No...
Ruslan Salakhutdinov, Sam T. Roweis