Anqi Wu

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Nearest neighbor (NN) classifier with dynamic time warping (DTW) is considered to be an effective method for time series classification. The performance of NN-DTW is dependent on the DTW constraints because the NN classifier is sensitive to the used distance function. For time series classification, the global path constraint of DTW is learned for(More)
Multitask Learning has been proven to be more effective than the traditional single task learning on many real-world problems by simultaneously transferring knowledge among different tasks which may suffer from limited labeled data. However, in order to build a reliable multitask learning model, nontrivial effort to construct the relatedness between(More)
In many problem settings, parameter vectors are not merely sparse, but dependent in such a way that non-zero coefficients tend to cluster together. We refer to this form of dependency as " region sparsity ". Classical sparse regression methods, such as the lasso and automatic relevance determination (ARD), model parameters as independent a priori, and(More)
Subunit models provide a powerful yet parsimonious description of neural responses to complex stimuli. They are defined by a cascade of two linear-nonlinear (LN) stages, with the first stage defined by a linear convolution with one or more filters and common point nonlinearity, and the second by pooling weights and an output nonlinearity. Recent interest in(More)
In many problem settings, parameter vectors are not merely sparse, but dependent in such a way that non-zero coefficients tend to cluster together. We refer to this form of dependency as " region sparsity ". Classical sparse regression methods, such as the lasso and automatic relevance determination (ARD), model parameters as independent a priori, and(More)
The effectiveness of nearest neighbor search heavily relies on the definition of distance function. Unfortunately, the meaningfulness of the frequently used distance, such as Euclidean distance, fractional distance and so on, will degrade with the increasing dimensionality. This problem, which is called distance concentration or instability, makes NN method(More)
Age is the number one risk factor for breast cancer, yet the underlying mechanisms are unexplored. Age-associated mammary stem cell (MaSC) dysfunction is thought to play an important role in breast cancer carcinogenesis. Non-human primates with their close phylogenetic relationship to humans provide a powerful model system to study the effects of aging on(More)
Murine mammary stem/progenitor cell isolation has been routinely used in many laboratories, yet direct comparison among different methods is lacking. In this study, we compared two frequently used digestion methods and three sets of frequently used surface markers for their efficiency in enriching mammary stem and progenitor cells in two commonly used mouse(More)
The mutation operator of Biogeography-Based Optimization (BBO) makes a large advance for the diversity of the solution space. Generally speaking, the quality of a solution is closely related with the maximum mutation rate, which is always decided by experience. But for the different situations, the maximum mutation rate may be different. In this paper, we(More)
Breast cancer incidence increases during aging, yet the mechanism of age-associated mammary tumorigenesis is unclear. Mammary stem cells are believed to play an important role in breast tumorigenesis, but how their function changes with age is unknown. We compared mammary epithelial cells isolated from young and old mammary glands of different cohorts of(More)