EdusalsaDiscover Your Stanford

EE 378B

Inference, Estimation, and Information Processing

  • Not Offered

3 units

Letter or Credit/No Credit

Techniques and models for signal, data and information processing, with emphasis on incomplete data, non-ordered index sets and robust low-complexity methods. Linear models; regularization and shrinkage; dimensionality reduction; streaming algorithms; sketching; clustering, search in high dimension; low-rank models; principal component analysis. Applications include: positioning from pairwise distances; distributed sensing; measurement/traffic monitoring in networks; finding communities/clusters in networks; recommendation systems; inverse problems. Prerequisites: EE278 and EE263 or equivalent. Recommended but not required: EE378A

Course Prequisites

Sign Up

To save EE 378B to your course bucketlist

Already Have An Account? Log In