http://archive.ics.uci.edu/ml/ http://yann.lecun.com/exdb/mnist/ http://vlado.fmf.uni-lj.si/pub/networks/ data/ http://code.google.com/p/linloglayout/ http://www.music-ir.org/mirex/wiki/2007 Chen et al. (2009). It is a similarity graph of 3090 songs. The songs are evenly divided among 10 classes that roughly correspond to different music genres. The weighted edges are human judgment on how simi...

High dimensional structured data such as text and images is often poorly understood and misrepresented in statistical modeling. Typical approaches to modeling such data involve, either explicitly or implicitly, arbitrary geometric assumptions. In this paper, we review a framework introduced by Lebanon and Lafferty that is based on Čencov’s theorem for obtaining a coherent geometry for data. The...

Most studies on affective analysis of text focus on the sentiment or emotion expressed by a whole sentence or document. In this paper, we propose a novel approach to predict the affective states of a described event through the predictions of the corresponding subject, action and object involved in the described event. Rather than using a sentiment label or discrete emotion categories, the affe...

In this paper we investigate neural graph embeddings as frontend features for various deep neural network (DNN) architectures for speech recognition. Neural graph embedding features are produced by an autoencoder that maps graph structures defined over speech samples to a continuous vector space. The resulting feature representation is then used to augment the standard acoustic features at the ...

In this work we present a new approach to the treatment of property graphs using neural encoding techniques derived from machine learning. Specifically, we will deal with the problem of embedding property graphs in vector spaces. Throughout this paper we will use the term embedding as an operation that allows to consider a mathematical structure, X, inside another structure Y , through a functi...

Neural Networks (NN), Type-1 Fuzzy Logic Systems (T1FLS) and Interval Type-2 Fuzzy Logic Systems (IT2FLS) are universal approximators, they can approximate any non-linear function. Recent research shows that embedding T1FLS on an NN or embedding IT2FLS on an NN can be very effective for a wide number of non-linear complex systems, especially when handling imperfect information. In this paper we...

Using concepts and tools of embodied cognitive science, we investigate the implications of embedding neural networks in a physical structure, the body of a robot. Through this embedding the loop from a network’s outputs to its subsequent inputs is closed. This closure enables an embedded network to actively generate its own input data instead of only passively processing predesigned input patte...

Cross-lingual sentiment classification aims to adapt the sentiment resource in a resource-rich language to a resource-poor language. In this study, we propose a representation learning approach which simultaneously learns vector representations for the texts in both the source and the target languages. Different from previous research which only gets bilingual word embedding, our Bilingual Docu...

In this paper, we enhance the attention-based neural machine translation (NMT) by adding explicit coverage embedding models to alleviate issues of repeating and dropping translations in NMT. For each source word, our model starts with a full coverage embedding vector to track the coverage status, and then keeps updating it with neural networks as the translation goes. Experiments on the large-s...

On hand watermark methods employ selective Neural Network techniques for watermark embedding efficiently. Similarity Based Superior Self Organizing Maps (SBS_SOM) a neural network algorithm for watermark generation. Host image is learned by the SBS_SOM neurons and the very fine RGB feature values are mined as digital watermark. Discrete Wavelet Transform (DWT) is used for watermark entrench. Si...