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SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
11 years 11 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»
13 years 10 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»
14 years 3 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»
14 years 12 days 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
14 years 2 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...