Multilabel classification has attracted much interest in recent times due to the wide applicability of the problem and the challenges involved in learning a classifier for multilabeled data. A crucial aspect of multilabel ...

This thesis presents six novel works involving several research domains, such as reinforcement learning (RL)– both with or without function approximators including deep neural networks, multi-agent RL, stochastic optimization, ...

Multilevel converters have become the direct accepted solution for high power converter applications. They are used in wide variety of power electronic applications like power transmission and distribution, electric motor ...

Multilevel inverters have advantages over two-level inverters such as reduced THD, ability to operate at low switching frequencies, reduced switching losses etc. Moreover, higher voltage levels can be handled with devices ...

In recent years, deep neural network models have shown to outperform many state of the art algorithms. The reason for this is, unsupervised pretraining with multi-layered deep neural networks have shown to learn better ...

Interactive computer graphics systems have become powerful tools for man-machine interaction, with wide-ranging applications. One particularly exciting and important area is the synthetic generation of realistic images of ...

The convolutional neural networks (CNNs) have become the most successful models for many pattern recognition problems in the areas of computer vision, speech, text and others. One concern about CNNs has always been their ...

The Iterative Closest Point (ICP) algorithm has been an extremely popular method for 3D points or surface registration. Given two point sets, it simultaneously solves for correspondences and estimates the motion between ...

We consider the problem of reconstructing a 3D surface from its multiview scans. Typically, the computational pipeline for this problem has two phases: (I) finding point-to-point correspondences between overlapping scans, ...