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KDD
1999
ACM
104views Data Mining» more  KDD 1999»
15 years 8 months ago
Learning Rules from Distributed Data
In this paper a concern about the accuracy (as a function of parallelism) of a certain class of distributed learning algorithms is raised, and one proposed improvement is illustrat...
Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowye...
ICIP
2006
IEEE
16 years 5 months ago
Provably Secure Steganography: Achieving Zero K-L Divergence using Statistical Restoration
In this paper, we present a framework for the design of steganographic schemes that can provide provable security by achieving zero Kullback-Leibler divergence between the cover a...
Kaushal Solanki, Kenneth Sullivan, Upamanyu Madhow...
ICML
2004
IEEE
16 years 4 months ago
Improving SVM accuracy by training on auxiliary data sources
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Pengcheng Wu, Thomas G. Dietterich
EMNLP
2008
15 years 5 months ago
Arabic Named Entity Recognition using Optimized Feature Sets
The Named Entity Recognition (NER) task has been garnering significant attention in NLP as it helps improve the performance of many natural language processing applications. In th...
Yassine Benajiba, Mona T. Diab, Paolo Rosso
IJCNN
2006
IEEE
15 years 10 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...