Mohamad Dia

Learn More
Factorizing low-rank matrices has many applications in machine learning and statistics. For probabilistic models in the Bayes optimal setting, a general expression for the mutual information has been proposed using heuristic statistical physics computations, and proven in few specific cases. Here, we show how to rigorously prove the conjectured formula for(More)
We consider the estimation of a signal from the knowledge of its noisy linear random Gaussian projections, a problem relevant in compressed sensing, sparse superposition codes or code division multiple access just to cite few. There has been a number of works considering the mutual information for this problem using the heuristic replica method from(More)
Recently, a new class of codes, called sparse superposition or sparse regression codes, has been proposed for communication over the AWGN channel. It has been proven that they achieve capacity using power allocation and various forms of iterative decoding. Empirical evidence has also strongly suggested that the codes achieve capacity when spatial coupling(More)
In this paper, we consider the design of 3G/WiFi heterogeneous networks under realistic operational conditions. The aim is reduce the energy consumed from batteries on mobile devices by utilizing the multiple available wireless interfaces and dynamically switching between 3G and WiFi. We conduct a set of experimental measurements in various network(More)
We recently proved threshold saturation for spatially coupled sparse superposition codes on the additive white Gaussian noise channel [1]. Here we generalize our analysis to a much broader setting. We show for any memoryless channel that spatial coupling allows generalized approximate message-passing (GAMP) decoding to reach the potential (or Bayes optimal)(More)
We consider the estimation of a signal from the knowledge of its noisy linear random Gaussian projections. A few examples where this problem is relevant are compressed sensing, sparse superposition codes, and code division multiple access. There has been a number of works considering the mutual information for this problem using the replica method from(More)
—Sparse superposition (SS) codes were originally proposed as a capacity-achieving communication scheme over the additive white Gaussian noise channel (AWGNC) [1]. Very recently, it was discovered that these codes are universal, in the sense that they achieve capacity over any memoryless channel under generalized approximate message-passing (GAMP) decoding(More)
—Spatial coupling has been successfully applied to various problems, ranging from error correcting codes to compressive sensing, and shown to have outstanding performance under message-passing algorithms. In particular, spatially coupled low-density parity-check (LDPC) codes were proven to universally achieve capacity under belief-propagation (BP) decoding.(More)
  • 1