We propose a method for weakly supervised segmentation of natural images, which may contain both textured or non-textured regions. Our texture representation is based on a dictionary of image patches. To divide an image into separated regions with similar texture we use an implicit level sets representation of the curve, which makes our method topologically adaptive. In addition, we suggest a m...

Binary label information is widely used semantic information in discriminative dictionary learning and non-negative matrix factorization. A Discriminative Dictionary Learning (DDL) algorithm uses the label of some data samples to enhance the discriminative property of sparse signals. A discriminative Non-negative Matrix Factorization (NMF) utilizes label information in learning discriminative b...

One of the most important designs for a lot of machine learning methods is the determination of the similarity between instances. Especially the kernel matrix, which is also known as the Gram matrix, plays a central role in the kernel machines such as support vector machine. The simplest design of similarity function is to use the distances between instances or the Gaussian function based on th...

We study an extreme scenario in multi-label learning where each training instance is endowed with a single one-bit label out of multiple labels. We formulate this problem as a non-trivial special case of one-bit rank-one matrix sensing and develop an efficient non-convex algorithm based on alternating power iteration. The proposed algorithm is able to recover the underlying low-rank matrix mode...

Label noise is an important part in the process of machine learning. Transition matrix provides effective way to reduce impact label on classification algorithm. In this experiment, we study logistic regression algorithm and random forest We use known real transition evaluate robustness two datasets. also design a estimator estimate three datasets algorithms. average error effectiveness top-1 a...

background recombinant activated factor vii (rfviia; novoseven® rt, novo nordisk, bagsvaerd, denmark) is a synthetic pro-coagulation factor derived from hamster kidney cells. objectives the purpose of this study was to evaluate the prescribing patterns of recombinant factor viia (rfviia) at a single, tertiary care pediatric hospital by indication of usage and dose administered. materials and me...

Abstract. In context of document classification, where in a corpus of documents their label tags are readily known, an opportunity lies in utilizing label information to learn document representation spaces with better discriminative properties. To this end, in this paper application of a Variational Bayesian Supervised Nonnegative Matrix Factorization (supervised vbNMF) with label-driven spars...

Retrieving nearest neighbors across correlated data in multiple modalities, such as image-text pairs on Facebook and video-tag pairs on YouTube, has become a challenging task due to the huge amount of data. Multimodal hashing methods that embed data into binary codes can boost the retrieving speed and reduce storage requirement. As unsupervised multimodal hashing methods are usually inferior to...

label switching technology is a flexible and high performance method for forwarding layer three packets that are mapped to layer two flows. each label switch router, lsr, needs a specific label for every flow, where the number of labels depends on the mapping and granularity of flows. data and control driven methods are the most significant and popular methods in label mapping policy. the above...

Multi-label problems arise in different domains such as digital media analysis and description, text categorization, multi-topic web page categorization, image and video annotation etc. Such a situation arises when the data are associated with multiple labels simultaneously. Similar to single label problems, multi label problems also suffer from high dimensionality as multi label data often hap...