Disambiguation-free partial label learning
نویسندگان
چکیده
منابع مشابه
Word Sense Disambiguation Using Label Propagation Based Semi-Supervised Learning
Shortage of manually sense-tagged data is an obstacle to supervised word sense disambiguation methods. In this paper we investigate a label propagation based semisupervised learning algorithm for WSD, which combines labeled and unlabeled data in learning process to fully realize a global consistency assumption: similar examples should have similar labels. Our experimental results on benchmark c...
متن کاملConfidence-Rated Discriminative Partial Label Learning
Partial label learning aims to induce a multi-class classifier from training examples where each of them is associated with a set of candidate labels, among which only one label is valid. The common discriminative solution to learn from partial label examples assumes one parametric model for each class label, whose predictions are aggregated to optimize specific objectives such as likelihood or...
متن کاملDeep Learning in Label-free Cell Classification.
Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low...
متن کاملDisambiguation of partial cognates
Cognates – words that have similar spelling and meaning in two or more languages – can accelerate vocabulary acquisition and facilitate the reading comprehension task. A student has to pay attention to the pairs of words that look and sound similar but have different meanings – false-friend pairs, and especially to pairs of words that share meanings in some but not all contexts – partial cognat...
متن کاملLabel Ranking with Partial Abstention using Ensemble Learning
In label ranking, the problem is to learn a mapping from instances to rankings over a finite set of predefined class labels. In this paper, we consider a generalization of this problem, namely label ranking with a reject option. Just like in conventional classification, where a classifier can refuse a presumably unreliable prediction, the idea is to concede a label ranker the possibility to abs...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SCIENTIA SINICA Informationis
سال: 2019
ISSN: 1674-7267
DOI: 10.1360/n112018-00150