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SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 5 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
KDD
2010
ACM
245views Data Mining» more  KDD 2010»
15 years 5 months ago
Learning incoherent sparse and low-rank patterns from multiple tasks
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Jianhui Chen, Ji Liu, Jieping Ye
PKDD
2009
Springer
181views Data Mining» more  PKDD 2009»
15 years 9 months ago
Active Learning for Reward Estimation in Inverse Reinforcement Learning
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Manuel Lopes, Francisco S. Melo, Luis Montesano
PAKDD
2000
ACM
140views Data Mining» more  PAKDD 2000»
15 years 6 months ago
Performance Controlled Data Reduction for Knowledge Discovery in Distributed Databases
The objective of data reduction is to obtain a compact representation of a large data set to facilitate repeated use of non-redundant information with complex and slow learning alg...
Slobodan Vucetic, Zoran Obradovic
SDMW
2004
Springer
15 years 8 months ago
Experimental Analysis of Privacy-Preserving Statistics Computation
The recent investigation of privacy-preserving data mining and other kinds of privacy-preserving distributed computation has been motivated by the growing concern about the privacy...
Hiranmayee Subramaniam, Rebecca N. Wright, Zhiqian...