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» Sequential Inductive Learning
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KDD
2009
ACM
150views Data Mining» more  KDD 2009»
15 years 10 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
KDD
2006
ACM
183views Data Mining» more  KDD 2006»
15 years 10 months ago
Discovering interesting patterns through user's interactive feedback
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
Dong Xin, Xuehua Shen, Qiaozhu Mei, Jiawei Han
ICMI
2009
Springer
147views Biometrics» more  ICMI 2009»
15 years 4 months ago
Multimodal end-of-turn prediction in multi-party meetings
One of many skills required to engage properly in a conversation is to know the appropiate use of the rules of engagement. In order to engage properly in a conversation, a virtual...
Iwan de Kok, Dirk Heylen
IFM
2009
Springer
124views Formal Methods» more  IFM 2009»
15 years 4 months ago
Dynamic Path Reduction for Software Model Checking
We present the new technique of dynamic path reduction (DPR), which allows one to prune redundant paths from the state space of a program under verification. DPR is a very general...
Zijiang Yang, Bashar Al-Rawi, Karem Sakallah, Xiao...
ICASSP
2008
IEEE
15 years 4 months ago
Contextually adaptive signal representation using conditional principal component analysis
The conventional method of generating a basis that is optimally adapted (in MSE) for representation of an ensemble of signals is Principal Component Analysis (PCA). A more ambitio...
Rosa M. Figueras i Ventura, Umesh Rajashekar, Zhou...