90 citations · 470 across the 39 of their papers we have counts for
6 papers · 1 filter
Universality in Learning from Linear Measurements
Ehsan Abbasi, Fariborz Salehi, Babak Hassibi
We study the problem of recovering a structured signal from independently and identically drawn linear measurements. A convex penalty function is considered which penali…
Stochastic Mirror Descent on Overparameterized Nonlinear Models: Convergence, Implicit Regularization, and Generalization
Navid Azizan, Sahin Lale, Babak Hassibi
Most modern learning problems are highly overparameterized, meaning that there are many more parameters than the number of training data points, and as a result, the training loss…
The Impact of Regularization on High-dimensional Logistic Regression
Fariborz Salehi, Ehsan Abbasi, Babak Hassibi
Logistic regression is commonly used for modeling dichotomous outcomes. In the classical setting, where the number of observations is much larger than the number of parameters, pro…
Gabidulin Codes with Support Constrained Generator Matrices
Hikmet Yildiz, Babak Hassibi
Gabidulin codes are the first general construction of linear codes that are maximum rank distant (MRD). They have found applications in linear network coding, for example, when the…
MOCZ for Blind Short-Packet Communication: Some Practical Aspects
Philipp Walk, Peter Jung, Babak Hassibi +1
We will investigate practical aspects for a recently introduced blind (noncoherent) communication scheme, called modulation on conjugate-reciprocal zeros (MOCZ), which enables reli…
Stochastic Linear Bandits with Hidden Low Rank Structure
Sahin Lale, Kamyar Azizzadenesheli, Anima Anandkumar +1
High-dimensional representations often have a lower dimensional underlying structure. This is particularly the case in many decision making settings. For example, when the represen…