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VL
2010
IEEE
216views Visual Languages» more  VL 2010»
13 years 8 months ago
Explanatory Debugging: Supporting End-User Debugging of Machine-Learned Programs
Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a “prog...
Todd Kulesza, Simone Stumpf, Margaret M. Burnett, ...
SDM
2009
SIAM
119views Data Mining» more  SDM 2009»
14 years 7 months ago
Twin Vector Machines for Online Learning on a Budget.
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
Zhuang Wang, Slobodan Vucetic
IJCV
2000
86views more  IJCV 2000»
13 years 9 months ago
Statistical Learning Theory: A Primer
In this paper we first overview the main concepts of Statistical Learning Theory, a framework in which learning from examples can be studied in a principled way. We then briefly di...
Theodoros Evgeniou, Massimiliano Pontil, Tomaso Po...
IROS
2006
IEEE
136views Robotics» more  IROS 2006»
14 years 4 months ago
Panoramic View-Based Navigation in Outdoor Environments Based on Support Vector Learning
— This paper describes a panoramic view-based navigation in outdoor environments. We have been developing a two-phase navigation method. In the training phase, the robot acquires...
Hideo Morita, Michael Hild, Jun Miura, Yoshiaki Sh...
IJCNN
2000
IEEE
14 years 2 months ago
A Neural Support Vector Network Architecture with Adaptive Kernels
In the Support Vector Machines (SVM) framework, the positive-definite kernel can be seen as representing a fixed similarity measure between two patterns, and a discriminant func...
Pascal Vincent, Yoshua Bengio