In this paper, we explain how to use additive feature functions to train neural networks. We give a new perspective on this topic and discuss the prior work on training neural networks via additive feature functions in a unified and convenient way.
In this paper, we propose an ensemble model for deep neural networks. We implement the building blocks of our ensemble model using a general-purpose deep learning library (PyTorch). Our experiments on classification and generative models show that, unlike the DNN ensemble model in the prior work, our ensemble model can achieve a better performance than the base model by a large margin.
We explore the possibility of using convolutional neural networks (CNNs) to capture the image semantic representations in natural language processing applications. Our results show that it is indeed possible to train a CNN with deep supervision to model the image content of the text. It is also found that a CNN with more than one convolutional layer can learn more informative feature maps, which can boost the performance of the CNN model for image captioning.
Ever since the first online dating service was created, millions of men and women have used it to find their perfect match. While the rise of online dating has gone a long way to improve the lives of adults, it has also created a new class of scammers, who pretend to be other people in order to lure potential victims into compromising situations. In this paper, we present a technical analysis of the design of online dating services and explain how they might be used to create not only a network of male scammers but also to build a botnet and a malicious botnet that is under the control of a rogue operator.
We investigate time delay and channel gain estimation for multipath fading Code Division Multiple Access (CDMA) signals using the second order Divided Difference Filter (DDF). We consider the case of paths that are a fraction of chip apart, also knwon as closely spaced paths. Given the nonlinear dependency of the channel parameters on the received signals in multiuser/multipath scenarios, we show that the DDF achieves better performance than its linear counterparts. The DDF, which is a derivative-free Kalman filtering approach, avoids the errors associated with linearization in the conventional Extended Kalman Filter (EKF). The Numerical results also show that the proposed DDF is simpler to implement, and more resilient to near-far interference in CDMA networks and is able to track closly spaced paths.
New Style Boutique 3ds Rom Descargar listic za jamb pdf free das schloss des cagliostro 1080p hdtv The Stoneman Murders 2 movie download kickass torrent pengantar etika bisnis k bertens download atuendo tradicional argentina hector arico pdf free Vienna Sound Library Special Edition Torrent archivos andreas gan Ghatak 1996 Hindi 720p DvDrip X264 AC3 51Hon322 dotnetbar v10.9.0.4 full cracked windows 5 Fast Report 4.0. 827ec27edc