Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
This paper discusses the impact of migrating from 2-D to 3-D on floorplanning and placement. By looking at a basic formulation of graph cuboidal dual problem, we show that the 3-...
We present a fast iterative planner (FIP) that aims to handle planning problems involving nondeterministic actions. In contrast to existing iterative planners, FIP is built upon G...
Jicheng Fu, Farokh B. Bastani, Vincent Ng, I-Ling ...
Document clustering techniques mostly depend on models that impose explicit and/or implicit priori assumptions as to the number, size, disjunction characteristics of clusters, and/...