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» Splitting of Learnable Classes
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IJCAI
2007
13 years 9 months ago
Learning from Partial Observations
We present a general machine learning framework for modelling the phenomenon of missing information in data. We propose a masking process model to capture the stochastic nature of...
Loizos Michael
FOCS
1993
IEEE
13 years 11 months ago
Scale-sensitive Dimensions, Uniform Convergence, and Learnability
Learnability in Valiant’s PAC learning model has been shown to be strongly related to the existence of uniform laws of large numbers. These laws define a distribution-free conver...
Noga Alon, Shai Ben-David, Nicolò Cesa-Bian...
SIGSOFT
2008
ACM
14 years 8 months ago
The implications of method placement on API learnability
To better understand what makes Application Programming Interfaces (APIs) hard to use and how to improve them, recent research has begun studying programmers' strategies and ...
Jeffrey Stylos, Brad A. Myers
ALT
2009
Springer
14 years 4 months ago
Uncountable Automatic Classes and Learning
In this paper we consider uncountable classes recognizable by ω-automata and investigate suitable learning paradigms for them. In particular, the counterparts of explanatory, vac...
Sanjay Jain, Qinglong Luo, Pavel Semukhin, Frank S...
COLT
1999
Springer
13 years 11 months ago
Uniform-Distribution Attribute Noise Learnability
We study the problem of PAC-learning Boolean functions with random attribute noise under the uniform distribution. We define a noisy distance measure for function classes and sho...
Nader H. Bshouty, Jeffrey C. Jackson, Christino Ta...