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AAAI
2011
14 years 6 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
CLUSTER
2011
IEEE
14 years 6 months ago
Incorporating Network RAM and Flash into Fast Backing Store for Clusters
—We present Nswap2L, a fast backing storage system for general purpose clusters. Nswap2L implements a single device interface on top of multiple heterogeneous physical storage de...
Tia Newhall, Douglas Woos
EMNLP
2011
14 years 6 months ago
Lateen EM: Unsupervised Training with Multiple Objectives, Applied to Dependency Grammar Induction
We present new training methods that aim to mitigate local optima and slow convergence in unsupervised training by using additional imperfect objectives. In its simplest form, lat...
Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jura...
ICDAR
2011
IEEE
14 years 5 months ago
Trie-Lexicon-Driven Recognition for On-line Handwritten Japanese Disease Names Using a Time-Synchronous Method
— This paper describes a lexicon-driven approach to on-line handwritten Japanese disease name recognition using a time-synchronous method. A trie lexicon is constructed from a di...
Bilan Zhu, Masaki Nakagawa
CVPR
2010
IEEE
14 years 3 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu