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CVPR
1997
IEEE
16 years 6 months ago
Global Training of Document Processing Systems Using Graph Transformer Networks
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
Léon Bottou, Yoshua Bengio, Yann LeCun
ICML
2009
IEEE
16 years 5 months ago
Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties
We describe an algorithm for constructing a set of acyclic conjunctive relational features by combining smaller conjunctive blocks. Unlike traditional level-wise approaches which ...
Filip Zelezný, Ondrej Kuzelka
ICML
2009
IEEE
16 years 5 months ago
Constraint relaxation in approximate linear programs
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
Marek Petrik, Shlomo Zilberstein
ICML
2007
IEEE
16 years 5 months ago
Revisiting probabilistic models for clustering with pair-wise constraints
We revisit recently proposed algorithms for probabilistic clustering with pair-wise constraints between data points. We evaluate and compare existing techniques in terms of robust...
Blaine Nelson, Ira Cohen
ICML
2008
IEEE
16 years 5 months ago
Manifold alignment using Procrustes analysis
In this paper we introduce a novel approach to manifold alignment, based on Procrustes analysis. Our approach differs from "semisupervised alignment" in that it results ...
Chang Wang, Sridhar Mahadevan