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Update with 13 new papers to Deeplearning.University

Links to Deep Learning Subtopics

[acoustic][acoustic model][cognition][embedded][feature][linear model][linear models][overview][regression][review][search][social][speech][speech recognition][survey][theory][visual]

Acoustic

 

Acoustic Model

 

Cognition

 

Embedded

 

Feature

 

Linear Model

 

Linear Models

 

Overview

 

Regression

 

Review

 

Search

 

Social

 

Speech

 

Speech Recognition

 

Survey

 

Theory

 

Visual

 

BIBLIOGRAPHY

@misc{2015ABPatelTNguyenRGBaraniuk,
  title = {A Probabilistic Theory of Deep Learning},
  author = {AB Patel, T Nguyen, RG Baraniuk}
}


@misc{2015ABernsteinAKuleshovYYanovich,
  title = {Manifold Learning in Regression Tasks},
  author = {A Bernstein, A Kuleshov, Y Yanovich}
}


@misc{2015AZometGChechik,
  title = {Image search results by seasonal time period},
  author = {A Zomet, G Chechik}
}


@misc{2015BvanRooyenRCWilliamson,
  title = {A Theory of Feature Learning},
  author = {B van Rooyen, RC Williamson}
}


@misc{2015FPavónJVegaSDCanto,
  title = {Som and Feature Weights Based Method for Dimensionality Reduction in Large Gauss Linear Models},
  author = {F Pavón, J Vega, SD Canto}
}


@misc{2015GEDahl,
  title = {Deep learning approaches to problems in speech recognition, computational chemistry, and natural language text processing},
  author = {GE Dahl}
}


@misc{2015HKPengRMarculescu,
  title = {Multi-scale compositionality: identifying the compositional structures of social dynamics using deep learning.},
  author = {HK Peng, R Marculescu}
}


@misc{2015MKYoonSMohanJChoiLSha,
  title = {Memory Heat Map: Anomaly Detection in Real-Time Embedded Systems Using Memory Behavior},
  author = {MK Yoon, S Mohan, J Choi, L Sha}
}


@misc{2015VMPatelRGopalanRLiRChellappa,
  title = {Visual Domain Adaptation: A survey of recent advances},
  author = {VM Patel, R Gopalan, R Li, R Chellappa}
}


@misc{2015YXue,
  title = {Recent Development in Analog Computation-A Brief Overview},
  author = {Y Xue}
}


@misc{2015ZHLingSYKangHZenASeniorMSchuster,
  title = {Deep Learning for Acoustic Modeling in Parametric Speech Generation: A systematic review of existing techniques and future trends},
  author = {ZH Ling, SY Kang, H Zen, A Senior, M Schuster}
}


@misc{2015ZWangJYangHJinEShechtmanAAgarwala,
  title = {Real-World Font Recognition Using Deep Network and Domain Adaptation},
  author = {Z Wang, J Yang, H Jin, E Shechtman, A Agarwala}
}

 

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About Amund Tveit (@atveit - amund@memkite.com)

Amund Tveit works in Memkite on developing large-scale Deep Learning and Search (Convolutional Neural Network) with Swift and Metal for iOS (see deeplearning.education for a Memkite app video demo). He also maintains the deeplearning.university bibliography (github.com/memkite/DeepLearningBibliography)

Amund previously co-founded Atbrox , a cloud computing/big data service company (partner with Amazon Web Services), also doing some “sweat equity” startup investments in US and Nordic startups. His presentations about Hadoop/Mapreduce Algorithms and Search were among top 3% of all SlideShare presentations in 2013 and his blog posts has been frequently quoted by Big Data Industry Leaders and featured on front pages of YCombinator News and Reddit Programming

He previously worked for Google, where he was tech.lead for Google News for iPhone (mentioned as “Google News Now Looks Beautiful On Your iPhone” on Mashable.com), lead a team measuring and improving Google Services in the Scandinavian Countries (Maps and Search) and worked as a software engineer on infrastructure projects. Other work experience include telecom (IBM Canada) and insurance/finance (Storebrand).

Amund has a PhD in Computer Science. His publications has been cited more than 500 times. He also holds 4 US patents in the areas of search and advertisement technology, and a pending US patent in the area of brain-controlled search with consumer-level EEG devices.

Amund enjoys coding, in particular Python, C++ and Swift (iOS)

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