Deep Learning Based Text Classification: A Comprehensive ...

arXiv:0706.3639v1 [cs.AI] 25 Jun 2007

arXiv:0706.3639v1 [cs.AI] 25 Jun 2007 Technical Report IDSIA-07-07 A Collection of Definitions of Intelligence Shane Legg IDSIA, Galleria …

  Intelligence, Collection

Deep Residual Learning for Image Recognition - …

Deep Residual Learning for Image Recognition Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun Microsoft Research fkahe, v-xiangz, v-shren, jiansung@microsoft.com

  Image, Learning, Residual, Recognition, Residual learning for image recognition

arXiv:1301.3781v3 [cs.CL] 7 Sep 2013

For all the following models, the training complexity is proportional to O = E T Q; (1) where E is number of the training epochs, T is the number of …

@google.com arXiv:1609.03499v2 [cs.SD] 19 Sep 2016

where 1 <x t <1 and = 255. This non-linear quantization produces a significantly better reconstruction than a simple linear quantization scheme. …

A Tutorial on UAVs for Wireless Networks: …

A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems Mohammad Mozaffari 1, ... to UAVs in wireless communications is the work in …

  Network, Communication, Wireless, Wireless communications, Wireless networks

Adversarial Generative Nets: Neural Network …

Adversarial Generative Nets: Neural Network Attacks on State-of-the-Art Face Recognition Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer Carnegie Mellon University

  Network, Attacks, Nets, Adversarial generative nets, Adversarial, Generative, Neural network, Neural, Neural network attacks

Massive Exploration of Neural Machine Translation ...

Massive Exploration of Neural Machine Translation Architectures Denny Britzy, Anna Goldie, Minh-Thang Luong, Quoc Le fdennybritz,agoldie,thangluong,qvlg@google.com Google Brain

  Architecture, Machine, Exploration, Translation, Neural, Exploration of neural machine translation, Exploration of neural machine translation architectures

Mastering Chess and Shogi by Self-Play with a …

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm David Silver, 1Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, 1Matthew Lai, Arthur Guez, Marc Lanctot,1

Going deeper with convolutions - arXiv

Going deeper with convolutions Christian Szegedy Google Inc. Wei Liu University of North Carolina, Chapel Hill Yangqing Jia Google Inc. Pierre Sermanet

  With, Going, Going deeper with convolutions, Deeper, Convolutions

Andrew G. Howard Menglong Zhu Bo Chen Dmitry ...

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand Marco Andreetto Hartwig Adam

  Applications

POST GRADUATE PROGRAM IN

the basics of management, Data Science techniques and applications for data-based decision making. Flexible Learning The PGP-DSBA program provides utmost learning flexibility. Learn while you earn with online sessions. We accommodate transfer cases and sabbaticals and provide the option to catch up even when you have missed classes. Hands-On ...

  Applications, Data, Asdb, Pgp dsba

Sentiment Analysis and Opinion Mining

and comprehensive introductory text, as well as a survey to the subject. 1.1 Sentiment Analysis Applications Opinions are central to almost all human activities because they are key influencers of our behaviors. Whenever we need to make a decision, we want to know others’ opinions. In the real world, businesses and

  Applications, Analysis, Texts, Sentiment, Sentiment analysis, Sentiment analysis applications

EXPLORATORY DATA ANALYSIS USING R

Mining Unstructured Information for Hypothesis Generation Scott Spangler Event Mining Algorithms and Applications Tao Li Text Mining and Visualization Case Studies Using Open-Source Tools Markus Hofmann and Andrew Chisholm Graph-Based Social Media Analysis Ioannis Pitas Data Mining A Tutorial-Based Primer, Second Edition Richard J. Roiger Data ...

  Applications, Analysis, Using, Data, Texts, Exploratory, Unstructured, Exploratory data analysis using r

Spark SQL: Relational Data Processing in Spark

Spark SQL: Relational Data Processing in Spark Michael Armbrusty, Reynold S. Xiny, Cheng Liany, Yin Huaiy, Davies Liuy, Joseph K. Bradleyy, Xiangrui Mengy, Tomer Kaftanz, Michael J. Franklinyz, Ali Ghodsiy, Matei Zahariay yDatabricks Inc. MIT CSAIL zAMPLab, UC Berkeley ABSTRACT Spark SQL is a new module in Apache Spark that integrates rela-

  Data, Spark

Sentiment Analysis and Subjectivity

Sentiment analysis, also known as opinion mining, grows out of this need. It is a challenging natural language processing or text mining problem. Due to its tremendous value for practical applications, there has been an explosive growth of both research in academia and applications in …

  Applications, Analysis, Texts

LECTURE NOTES ON DATA PREPARATION AND ANALYSIS …

deliver the resultant data product. Data gathering is a non-trivial step of the process; it normally involves gathering unstructured data from different sources. To give an example, it could involve writing a crawler to retrieve reviews from a website. This involves dealing with text,

  Analysis, Data, Texts, Unstructured, Unstructured data

Disease Prediction Using Machine Learning

handle structured data, we consult hospital experts to know useful features. In the case of unstructured text data, we select the features automatically with the help of k-mean algorithm. We propose a k-mean algorithm for both structured and unstructured data. 3.1 The k …

  Data, Texts, Unstructured, Unstructured data, Of unstructured text data