Deep Learning for Industrial Applications
Seminar an der Universität des Saarlandes, Fachrichtung Informatik, LVst 109686
The current assignment of topics and dates to pre-registered participants for presentations and their opponents is as follows:
Topic#
Topic and Presenter
Date
Opponents
Finance
1a
L Zhang et al. (2017): Stock Price Prediction via Discovering Multi-Frequency Trading Patterns.
Gabriele Lamarck Silveira
16.4.
Chen, Baig
Healthcare
2b
N Tajbakhsh et al. (2016): Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
Ayan Majumdar
23.4.
cancelled
3
Z Che et al. (2017): Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records.
Karolina Kume
7.5.
Verma, Anwari
Autonomous Driving
4
A Uçar et al. (2017): Object Recognition and Detection with Deep Learning for Autonomous Driving Applications.
Mossad Helali
14.5.
Othman, Silveira
5
X Huazhe et al. (2017): End-to-end Learning of Driving Models from Large-scale Video Datasets.
Anilkumar Erappanakoppal Swamy
18.6.
6
X Wang et al. (2017): Capturing Car-Following Behaviors by Deep Learning.
Hanan Othman
4.6.
7
J Zhang et al. (2016): Deep Reinforcement Learning with Successor Features for Navigation Across Similar Environments.
Tejaswani Verma
11.6.
Helali, Kume
8
H Zou et al. (2018): Understanding Human Behaviors in Crowds by Imitating the Decision-Making Process.
Shreya Soans
28.5.
9
WC Ma et al. (2017): Forecasting Interactive Dynamics of Pedestrians with Fictitious Play.
Muhammad Ehtisham Ali
Recommendation
10
C Chen et al. (2017): Location-Aware Personalized News Recommendation With Deep Semantic Analysis.
Ahmed Sohail Anwari
25.6.
11
S Zhang et al. (2017): AutoSVD++: An Efficient Hybrid Collaborative Filtering Model via Contractive Autoencoders.
Mirza Misbah Mubeen Baig
2.7.
12
X He et al. (2017): Neural collaborative filtering.
Dingfan Chen
9.7.
Impressum