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ICML
2001
IEEE
16 years 7 months ago
Learning Probabilistic Models of Relational Structure
Most real-world data is stored in relational form. In contrast, most statistical learning methods work with "flat" data representations, forcing us to convert our data i...
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin...
ALT
2006
Springer
16 years 3 months ago
How Many Query Superpositions Are Needed to Learn?
Abstract. This paper introduces a framework for quantum exact learning via queries, the so-called quantum protocol. It is shown that usual protocols in the classical learning setti...
Jorge Castro
COLT
1992
Springer
15 years 10 months ago
Language Learning from Stochastic Input
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
Shyam Kapur, Gianfranco Bilardi
EUROCOLT
1995
Springer
15 years 10 months ago
The structure of intrinsic complexity of learning
Limiting identification of r.e. indexes for r.e. languages (from a presentation of elements of the language) and limiting identification of programs for computable functions (fr...
Sanjay Jain, Arun Sharma
ICML
2010
IEEE
15 years 7 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre