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Electricity generation combined with its transmission and distribution form the majority of an electric utility's recurring operating costs. These costs are determined, not only by the aggregate energy generated, but also by the maximum instantaneous peak power demand required over time. Prior work proposes using energy storage devices to reduce these costs(More)
Exponential growth of unlabeled web-scale datasets, and class hierarchies to represent them, has given rise to new challenges for hierarchical classification. It is costly and time consuming to create a complete ontology of classes to represent entities on the Web. Hence, there is a need for techniques that can do hierarchical classification of entities(More)
In an entity classification task, topic or concept hierarchies are often incomplete. Previous work by Dalvi et al. [12] has showed that in non-hierarchical semi-supervised classification tasks, the presence of such unanticipated classes can cause semantic drift for seeded classes. The Exploratory learning [12] method was proposed to solve this problem;(More)
In this paper, we propose a single low-dimensional representation of a large collection of table and hyponym data, and show that with a small number of primitive operations , this representation can be used effectively for many purposes. Specifically we consider queries like set expansion, class prediction etc. We evaluate our methods on publicly available(More)
The effect of the network structure on the dynamics of social and communication networks has been of interest in recent years. It has been observed that network properties such as neighborhood overlap, clustering coefficient, etc. influence the tie strengths and link persistence between individuals. In this paper we study the communication records (both(More)
Recent work on information extraction has suggested that fast, interactive tools can be highly effective; however, creating a usable system is challenging, and few publi-cally available tools exist. In this paper we present IKE, a new extraction tool that performs fast, interactive bootstrapping to develop high-quality extraction patterns for targeted(More)
In multiclass semi-supervised learning, sometimes the information about data-points is present in multiple views. In this paper we propose an optimization based method to tackle semi-supervised learning in the presence of multiple views. Our techniques make use of mixed integer linear programming formulations along with the EM framework to find consistent(More)