搜索结果: 1-15 共查到“Semi-Supervised”相关记录19条 . 查询时间(0.109 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Optimal semi-supervised subsampling via predictive inference
预测推理 最优 半监督子采样
2023/4/26
In big data era, subsampling or sub-data selection techniques are often adopted to extract a fraction of informative individuals from the massive data. Existing subsampling algorithms focus mainly on ...
Profiled SCA with a New Twist: Semi-supervised Learning
Side-channel attacks Profiled scenario Machine learning
2017/11/13
Profiled side-channel attacks represent the most powerful category of side-channel attacks. In this context, the attacker gains ac- cess of a profiling device to build a precise model which is used to...
Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning
Semi-Supervised Unsupervised Learning
2017/4/6
Highly frequent in language and communication, metaphor represents a significant challenge
for Natural Language Processing (NLP) applications. Computational work on metaphor has
traditionally evolve...
Semi-Supervised Incremental Learning of Hierarchical Appearance Models
Detection Building Structure, Interpretation Classifi cation Incremental Learning Recognition
2015/12/8
We propose an incremental learning scheme for learning a class hierarchy for objects typically occurring multiple in images. Given oneexample of an object that appears several times in the image, e.g....
Large-scale annotated corpora are a prerequisite to developing high-performance semantic role
labeling systems. Unfortunately, such corpora are expensive to produce, limited in size, and
may not be ...
SEMI-SUPERVISED CLASSIFICATION OF LAND COVER BASED ON SPECTRAL REFLECTANCE DATA EXTRACTED FROM LISS IV IMAGE
Semi-supervised classification Hyperspectral Reflectance
2015/8/28
A methodology is proposed for extracting information on land cover based on hyperspectral reflectance
data derived from satellite image, without supervising with ground truth. The reflectance percent...
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
Inferring Label Sampling Mechanisms Semi-Supervised Learning
2015/8/21
We consider the situation in semi-supervised learning, where the “label sampling” mechanism stochastically depends on the true response (as well as potentially on the features). We suggest a method of...
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
Semi-Supervised Recursive Autoencoders Predicting Sentiment Distributions
2015/6/12
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space representations for multi...
Semi-supervised Clustering Ensemble by Voting
clustering ensembles semi supervised clustering consensus function ensemble generation.
2012/9/18
Clustering ensemble is one of the most recent advances in unsupervised learning. It aims to combine the clustering results obtained using different algorithms or from different runs of ...
Treat samples differently: Object tracking with semi-supervised online CovBoost
Object tracking semi-supervised CovBoost
2013/7/24
Most feature selection methods for object tracking assume that the labeled samples obtained in the next framesfollow the similar distribution with the samples in the previous frame. However, this assu...
SERAPH: Semi-supervised Metric Learning Paradigm with Hyper Sparsity
Semi-supervised Metric Learning Paradigm Hyper Sparsity
2011/6/15
We consider the problem of learning a distance metric from a limited amount of pairwise information as effectively as possible. The proposed SERAPH (SEmi-supervised metRic leArning Paradigm with Hyper...
Semi-supervised logistic discrimination for functional data
EM algorithm Functional data analysis Model selec-tion Regularization Semi-supervised learning
2011/3/24
Multi-class classification methods based on both labeled and unlabeled functional data sets are discussed. We present semi-supervised logistic models for classification in the context of functional da...
Semi-Supervised SimHash for Efficient Document Similarity Search
Semi-Supervised SimHash Efficient Document Similarity Search
2015/1/24
Semi-Supervised SimHash for Efficient Document Similarity Search.
Semi-Supervised Discriminant Analysis via Spectral Transduction
Semi-Supervised Discriminant Analysis Spectral Transduction
2010/12/20
Linear Discriminant Analysis (LDA) is a popular method for dimensionality reduction
and classification. In real-world applications when there is no sufficient labeled
data, LDA suffers from serious ...
Semi-Supervised Discriminant Analysis via Spectral Transduction
Semi-Supervised Discriminant Analysis via Spectral Transduction
2013/7/16
Linear Discriminant Analysis (LDA) is a popular method for dimensionality reduction and classification. In real-world applications when there is no sufficient labeled data, LDA suffers fro...