Probabilistic low-rank matrix completion on finite alphabets

  title={Probabilistic low-rank matrix completion on finite alphabets},
  author={Jean Lafond and Olga Klopp and Eric Moulines and Joseph Salmon},
The task of reconstructing a matrix given a sample of observed entries is known as the matrix completion problem. It arises in a wide range of problems, including recommender systems, collaborative filtering, dimensionality reduction, image processing, quantum physics or multi-class classification to name a few. Most works have focused on recovering an unknown real-valued low-rank matrix from randomly sub-sampling its entries. Here, we investigate the case where the observations take a finite… CONTINUE READING