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IJON
2002
130views more  IJON 2002»
14 years 9 months ago
Error-backpropagation in temporally encoded networks of spiking neurons
For a network of spiking neurons that encodes information in the timing of individual spike times, we derive a supervised learning rule, SpikeProp, akin to traditional errorbackpr...
Sander M. Bohte, Joost N. Kok, Johannes A. La Pout...
ICML
2009
IEEE
15 years 11 months ago
Good learners for evil teachers
We consider a supervised machine learning scenario where labels are provided by a heterogeneous set of teachers, some of which are mediocre, incompetent, or perhaps even malicious...
Ofer Dekel, Ohad Shamir
98
Voted
ICPR
2000
IEEE
15 years 2 months ago
Integrating Unlabeled Images for Image Retrieval Based on Relevance Feedback
Retrieval techniques based on pure similarity metrics are often suffered from the scales of image features. An alternative approach is to learn a mapping based on queries and rele...
Ying Wu, Qi Tian, Thomas S. Huang
108
Voted
ICMLA
2009
14 years 8 months ago
Knowledge Transfer for Feature Generation in Document Classification
One important problem in machine learning is how to extract knowledge from prior experience, then transfer and apply this knowledge in new learning tasks. To address this problem, ...
Jian Zhang, Shobhit S. Shakya
KDD
2008
ACM
207views Data Mining» more  KDD 2008»
15 years 10 months ago
Active learning with direct query construction
Active learning may hold the key for solving the data scarcity problem in supervised learning, i.e., the lack of labeled data. Indeed, labeling data is a costly process, yet an ac...
Charles X. Ling, Jun Du