Tianqi Zhao

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This paper studies the following problem: given samples from a high dimensional discrete distribution, we want to estimate the leading (δ, ρ)-modes of the underlying distributions. A point is defined to be a (δ, ρ)-mode if it is a local optimum of the density within a δ-neighborhood under metric ρ. As we increase the "scale" parameter δ, the neighborhood(More)
We consider a partially linear framework for modelling massive heterogeneous data. The major goal is to extract common features across all sub-populations while exploring heterogeneity of each sub-population. In particular, we propose an aggregation type estimator for the commonality parameter that possesses the (non-asymptotic) minimax optimal bound and(More)
The internetware system is a complex and distributed self-adaptive system, which challenges the method for making adaptation plans. Rule based approaches are very efficient to make plans in adaptive systems. To enable effective rule-based adaptation, we need to write a set of well behaved self-adaptive rules which could always lead to desirable states. This(More)
Internetware denotes a kind of complex distributed software system, which executes in an open, uncertain and dynamic environment, and adapts itself to changes in the environment. An important problem related to the development of Internetware applications is how to define their requirements. Traditional requirements modeling methods work well with software(More)
Video delivery networks (VDNs) using cloud storage have recently started to emerge. Different to the conventional VDNs, Cloud Video Delivery Networks (CVDNs) take advantage of the cloud computing technology which helps to reduce the storage and bandwidth cost. However, the existing CVDNs model cannot guarantee the Quality of Service (QoS) adequately because(More)
Goal-oriented adaptation provides a powerful mechanism to develop self-adaptive systems, enabling systems to keep satisfying user goals in a dynamically changing environment. The goal-oriented approach normally reduces the adaptation planning as a global optimization process and leaves the system the task of determining the actions required to achieve the(More)
One of the challenges in self-adaptive systems concerns how to make adaptation to themselves at runtime in response to possible and even unexpected changes from the environment and/or user goals. A feasible solution to this challenge is rule-based adaptation, in which, adaptation decisions are made according to predefined rules that specify what particular(More)
We study the problem of estimating the relative depth order of point pairs in a monocular image. Recent advances [1], [2] mainly focus on using deep convolutional neural networks (DCNNs) to learn and infer the ordinal information from multiple contextual information of the points pair such as global scene context, local contextual information, and the(More)