Adaptive Data Embedding Scheme Based on Similar and Dissimilar Clustering Strategies

For the data sets used in this thesis we find that F-score performs well when the number of features is large, and for small data the two methods using the gradient of the

An instance associated with ≥ 2 labels e.g., a video shot includes several concepts Large-scale Data. SVM cannot handle large sets if using kernels

The remaining positions contain //the rest of the original array elements //the rest of the original array elements.

MTL – multi-task learning for STM and LM, where they share the embedding layer PSEUDO – train an STM with labeled data, generate labels for unlabeled data, and retrain STM.

• Learn the mapping between input data and the corresponding points the low dimensional manifold using mixture of factor analyzers. • Learn a dynamical model based on the points on

Since the sink is aware of the location of the interested area, simple greedy geographic routing scheme is used to send a data request (in the form of

In this thesis, we have proposed a new and simple feedforward sampling time offset (STO) estimation scheme for an OFDM-based IEEE 802.11a WLAN that uses an interpolator to recover

In this chapter, the results for each research question based on the data analysis were presented and discussed, including (a) the selection criteria on evaluating