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ICML
1996
IEEE
16 years 4 months ago
Unsupervised Learning Using MML
This paper discusses the unsupervised learning problem. An important part of the unsupervised learning problem is determining the numberofconstituent groups (componentsor classes)...
Jonathan J. Oliver, Rohan A. Baxter, Chris S. Wall...
313
Voted
BICA
2010
14 years 10 months ago
Application Feedback in Guiding a Deep-Layered Perception Model
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
Itamar Arel, Shay Berant
130
Voted
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
15 years 9 months ago
Incorporating prior knowledge with weighted margin support vector machines
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
Xiaoyun Wu, Rohini K. Srihari
ICML
2009
IEEE
16 years 4 months ago
Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery
We develop a cyclical blockwise coordinate descent algorithm for the multi-task Lasso that efficiently solves problems with thousands of features and tasks. The main result shows ...
Han Liu, Mark Palatucci, Jian Zhang
TNN
2010
205views Management» more  TNN 2010»
14 years 10 months ago
Behavior-constrained support vector machines for fMRI data analysis
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
Danmei Chen, Sheng Li, Zoe Kourtzi, Si Wu