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JAIR
2002
163views more  JAIR 2002»
15 years 7 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
307
Voted
MICCAI
2000
Springer
15 years 11 months ago
Small Sample Size Learning for Shape Analysis of Anatomical Structures
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
Polina Golland, W. Eric L. Grimson, Martha Elizabe...
DMIN
2010
262views Data Mining» more  DMIN 2010»
15 years 5 months ago
SMO-Style Algorithms for Learning Using Privileged Information
Recently Vapnik et al. [11, 12, 13] introduced a new learning model, called Learning Using Privileged Information (LUPI). In this model, along with standard training data, the tea...
Dmitry Pechyony, Rauf Izmailov, Akshay Vashist, Vl...
199
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PATAT
2004
Springer
130views Education» more  PATAT 2004»
16 years 1 months ago
Learning User Preferences in Distributed Calendar Scheduling
Abstract. Within the field of software agents, there has been increasing interest in automating the process of calendar scheduling in recent years. Calendar (or meeting) schedulin...
Jean Oh, Stephen F. Smith
250
Voted
JMLR
2011
192views more  JMLR 2011»
15 years 2 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...