@inproceedings{
  author = {E. Beck and C. Bockelmann and A. Dekorsy},
  year = {2020},
  month = {Feb},
  title = {Concrete MAP Detection: A Machine Learning Inspired Relaxation},
  volume = {24},
  URL = {https://cgi.tu-harburg.de/~c00wsa20/index.php},
  address={Hamburg, Germany},
  abstract={Motivated by large linear inverse problems where the complexity of the Maximum A-Posteriori (MAP) detector grows exponentially with system dimensions, e.g., large MIMO, we introduce a method to relax a discrete MAP problem into a continuous one. The relaxation is inspired by recent ML research and offers many favorable properties reflecting its quality. Hereby, we derive an iterative detection algorithm based on gradient descent optimization: Concrete MAP Detection (CMD). We show numerical results of application in large MIMO systems that demonstrate superior performance w.r.t. all considered State of the Art approaches.},
  booktitle={24th International ITG Workshop on Smart Antennas (WSA 2020)}
}