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» Machine learning problems from optimization perspective
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125
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ICML
2006
IEEE
16 years 3 months ago
A statistical approach to rule learning
We present a new, statistical approach to rule learning. Doing so, we address two of the problems inherent in traditional rule learning: The computational hardness of finding rule...
Stefan Kramer, Ulrich Rückert
120
Voted
ICML
2006
IEEE
16 years 3 months ago
Agnostic active learning
We state and analyze the first active learning algorithm which works in the presence of arbitrary forms of noise. The algorithm, A2 (for Agnostic Active), relies only upon the ass...
Maria-Florina Balcan, Alina Beygelzimer, John Lang...
COLT
2005
Springer
15 years 8 months ago
General Polynomial Time Decomposition Algorithms
We present a general decomposition algorithm that is uniformly applicable to every (suitably normalized) instance of Convex Quadratic Optimization and efficiently approaches an o...
Nikolas List, Hans-Ulrich Simon
KDD
1994
ACM
98views Data Mining» more  KDD 1994»
15 years 6 months ago
Rule Induction for Semantic Query Optimization
Semantic query optimization can dramatically speed up database query answering by knowledge intensive reformulation. But the problem of how to learn required semantic rules has no...
Chun-Nan Hsu, Craig A. Knoblock
132
Voted
KDD
2010
ACM
245views Data Mining» more  KDD 2010»
15 years 4 months ago
Learning incoherent sparse and low-rank patterns from multiple tasks
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Jianhui Chen, Ji Liu, Jieping Ye