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ECML
2006
Springer
13 years 11 months ago
Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
Alessandro Moschitti
ECML
2006
Springer
13 years 11 months ago
Bandit Based Monte-Carlo Planning
Abstract. For large state-space Markovian Decision Problems MonteCarlo planning is one of the few viable approaches to find near-optimal solutions. In this paper we introduce a new...
Levente Kocsis, Csaba Szepesvári
ECML
2006
Springer
13 years 11 months ago
(Agnostic) PAC Learning Concepts in Higher-Order Logic
This paper studies the PAC and agnostic PAC learnability of some standard function classes in the learning in higher-order logic setting introduced by Lloyd et al. In particular, i...
Kee Siong Ng
ECML
2006
Springer
13 years 11 months ago
Deconvolutive Clustering of Markov States
In this paper we formulate the problem of grouping the states of a discrete Markov chain of arbitrary order simultaneously with deconvolving its transition probabilities. As the na...
Ata Kabán, Xin Wang
ECML
2006
Springer
13 years 11 months ago
EM Algorithm for Symmetric Causal Independence Models
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. In this pap...
Rasa Jurgelenaite, Tom Heskes
ECML
2006
Springer
13 years 11 months ago
Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
Sébastien Jodogne, Justus H. Piater
ECML
2006
Springer
13 years 11 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
ECML
2006
Springer
13 years 11 months ago
Bayesian Learning of Markov Network Structure
Abstract. We propose a simple and efficient approach to building undirected probabilistic classification models (Markov networks) that extend na
Aleks Jakulin, Irina Rish
ECML
2006
Springer
13 years 11 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
ECML
2006
Springer
13 years 11 months ago
TildeCRF: Conditional Random Fields for Logical Sequences
Abstract. Conditional Random Fields (CRFs) provide a powerful instrument for labeling sequences. So far, however, CRFs have only been considered for labeling sequences over flat al...
Bernd Gutmann, Kristian Kersting