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» Learning for stochastic dynamic programming
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ICML
2008
IEEE
16 years 2 months ago
Graph kernels between point clouds
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
Francis R. Bach
147
Voted
ECML
2007
Springer
15 years 3 months ago
Sequence Labeling with Reinforcement Learning and Ranking Algorithms
Many problems in areas such as Natural Language Processing, Information Retrieval, or Bioinformatic involve the generic task of sequence labeling. In many cases, the aim is to assi...
Francis Maes, Ludovic Denoyer, Patrick Gallinari
AAAI
2011
14 years 1 months ago
Fast Newton-CG Method for Batch Learning of Conditional Random Fields
We propose a fast batch learning method for linearchain Conditional Random Fields (CRFs) based on Newton-CG methods. Newton-CG methods are a variant of Newton method for high-dime...
Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Ok...
HAPTICS
2007
IEEE
15 years 8 months ago
Haptic Feedback Enhances Force Skill Learning
This paper explores the use of haptic feedback to abstract motor skill that requires recalling a sequence of forces. Participants are guided along a trajectory and are asked to le...
Daniel Morris, Hong Z. Tan, Federico Barbagli, Tim...
JMLR
2006
120views more  JMLR 2006»
15 years 1 months ago
Kernel-Based Learning of Hierarchical Multilabel Classification Models
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Juho Rousu, Craig Saunders, Sándor Szedm&aa...