26 citations · 137 across the 41 of their papers we have counts for
6 papers · 1 filter
Parallelism versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes
Seyyed Ali Hashemi, Marco Mondelli, Arman Fazeli +3
This paper characterizes the latency of the simplified successive-cancellation (SSC) decoding scheme for polar codes under hardware resource constraints. In particular, when the nu…
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh Nguyen, Marco Mondelli, Guido Montufar
A recent line of work has analyzed the theoretical properties of deep neural networks via the Neural Tangent Kernel (NTK). In particular, the smallest eigenvalue of the NTK has bee…
Sparse Multi-Decoder Recursive Projection Aggregation for Reed-Muller Codes
Dorsa Fathollahi, Nariman Farsad, Seyyed Ali Hashemi +1
Reed-Muller (RM) codes are one of the oldest families of codes. Recently, a recursive projection aggregation (RPA) decoder has been proposed, which achieves a performance that is c…
Approximate Message Passing with Spectral Initialization for Generalized Linear Models
Marco Mondelli, Ramji Venkataramanan
We consider the problem of estimating a signal from measurements obtained via a generalized linear model. We focus on estimators based on approximate message passing (AMP), a famil…
Optimal Combination of Linear and Spectral Estimators for Generalized Linear Models
Marco Mondelli, Christos Thrampoulidis, Ramji Venkataramanan
We study the problem of recovering an unknown signal given measurements obtained from a generalized linear model with a Gaussian sensing matrix. Two popular solutio…
Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology
Quynh Nguyen, Marco Mondelli
Recent works have shown that gradient descent can find a global minimum for over-parameterized neural networks where the widths of all the hidden layers scale polynomially with …