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We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled and unlabeled training data. Our approach is based on extending the minimum entropy regularization framework to the structured prediction case, yielding a training objective that(More)
We augment naive Bayes models with statistical n-gram language models to address short-comings of the standard naive Bayes text classifier. The result is a generalized naive Bayes classifier which allows for a local Markov dependence among observations; a model we refer to as the C hain A ugmented N aive Bayes (CAN) Bayes classifier. CAN models have two(More)
The problem of automatic extraction of sentiment expressions from informal text, as in microblogs such as tweets is a recent area of investigation. Compared to formal text, such as in product reviews or news articles , one of the key challenges lies in the wide diversity and informal nature of sentiment expressions that cannot be trivially enumerated or(More)
We present two new algorithms for online learning in reproducing kernel Hilbert spaces. Our first algorithm, ILK (implicit online learning with kernels), employs a new, implicit update technique that can be applied to a wide variety of convex loss functions. We then introduce a bounded memory version, SILK (sparse ILK), that maintains a compact(More)
The aim of this study was to evaluate effect of diosgenin (DG) on rats that had osteoporosis-like features induced by ovariectomy (OVX). Seventy-two six-month-old female Wistar rats were subjected to either ovariectomy (n = 60) or Sham operation (SHAM group, n = 12). Beginning at one week post-ovariectomy, the OVX rats were treated with vehicle (OVX group,(More)
miR-126 is an endothelial-specific microRNA essential for governing vascular integrity and angiogenesis. Its role in tumor angiogenesis of gastric cancer (GC) is unclear. This study aimed at determining the role of miR-126 in GC angiogenesis. Down-regulation of miR-126 was found to inversely correlate with an increased microvessel density (MVD) and vascular(More)
We present a simple approach for Asian language text classification without word segmentation, based on statistical §-gram language modeling. In particular, we examine Chinese and Japanese text classification. With character §-gram models, our approach avoids word segmentation. However, unlike traditional ad hoc §-gram models, the statistical language(More)