![\"hande\"](\"http:\/\/lig-membres.imag.fr\/alemdar\/wp-content\/uploads\/sites\/186\/2015\/03\/hande-286x300.png\")
<\/h3>\n<\/h3>\nPost-doctoral Researcher Laboratoire d\u2019Informatique de Grenoble (LIG) You can find me on\u00a0Google Scholar<\/a>,\u00a0Web of Science<\/a>,\u00a0Research Gate<\/a>,\u00a0DBLP<\/a><\/p>\n You can follow me on\u00a0twitter<\/a><\/p>\n Machine Learning and Pattern Recognition<\/strong> Data Science<\/b> Pervasive and Ubiquitous Computing<\/strong> Researching deep learning algorithms on a hardware solution for pattern mining in high throughput data streams. This solution, which could be proposed as a support hardware card, will be able to test simultaneously the presence of a large number of patterns in the data. The benefits of such a solution are (i) to process faster streams than purely software approaches, and (ii) to use less servers to process data streams, thus reducing energy consumption. I study on constrained deep neural networks with binary and ternary weights in order to make use of this power efficient hardware without compromising accuracy.<\/p>\n
\nSLIDE<\/a>\u00a0research group<\/p>\nContact Information<\/h6>\n
\nUniversit\u00e9 Grenoble Alpes (UGA)
\nB\u00e2timent IMAG – Bureau 310
\n700 Avenue Centrale
\n38401 Saint-Martin d\u2019H\u00e8res \u2013 FRANCE
\nTel: +33 4\u00a057\u00a042\u00a016\u00a010
\nEmail: FirstName.LastName@univ-grenoble-alpes.fr<\/p>\nResearch Interests<\/h3>\n
\nDeep Learning, Probabilistic Models,\u00a0Active Learning, Semi-supervised Learning, Transfer Learning<\/p>\n
\nReal World Big Data Mining, Sports Analytics, Privacy Implications of Data Analytics<\/p>\n
\nHuman activity recognition, Behavior analysis,\u00a0Ambient Assisted Living (AAL) Applications<\/p>\nProjects<\/h3>\n