We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
In building practical sensor networks, it is often beneficial to use only a subset of sensors to take measurements because of computational, communication, and power limitations....
Yoonheui Kim, Victor R. Lesser, Deepak Ganesan, Ra...
The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
Linear DSP kernels such as transforms and filters are comprised exclusively of additions and multiplications by constants. These multiplications may be realized as networks of ad...
Augmenting an evolutionary algorithm with knowledge of its target problem can yield a more effective algorithm, as this presentation illustrates. The Quadratic Knapsack Problem e...