2 citations · 3 across the 7 of their papers we have counts for
11 papers
Privacy-Preserving Near Neighbor Search via Sparse Coding with Ambiguation
Behrooz Razeghi, Sohrab Ferdowsi, Dimche Kostadinov +2
In this paper, we propose a framework for privacy-preserving approximate near neighbor search via stochastic sparsifying encoding. The core of the framework relies on sparse coding…
Unsupervised Feature Learning for Event Data: Direct vs Inverse Problem Formulation
Dimche Kostadinov, Davide Scaramuzza
Event-based cameras record an asynchronous stream of per-pixel brightness changes. As such, they have numerous advantages over the standard frame-based cameras, including high temp…
Online Weight-adaptive Nonlinear Model Predictive Control
Dimche Kostadinov, Davide Scaramuzza
Nonlinear Model Predictive Control (NMPC) is a powerful and widely used technique for nonlinear dynamic process control under constraints. In NMPC, the state and control weights of…
Network Parameter Learning Using Nonlinear Transforms, Local Representation Goals and Local Propagation Constraints
Dimche Kostadinov, Behrooz Razdehi, Slava Voloshynovskiy
In this paper, we introduce a novel concept for learning of the parameters in a neural network. Our idea is grounded on modeling a learning problem that addresses a trade-off betwe…
Clustering with Jointly Learned Nonlinear Transforms Over Discriminating Min-Max Similarity/Dissimilarity Assignment
Dimche Kostadinov, Behrooz Razeghi, Taras Holotyak +1
This paper presents a novel clustering concept that is based on jointly learned nonlinear transforms (NTs) with priors on the information loss and the discrimination. We introduce…
Privacy-Preserving Identification via Layered Sparse Code Design: Distributed Servers and Multiple Access Authorization
Behrooz Razeghi, Slava Voloshynovskiy, Sohrab Ferdowsi +1
We propose a new computationally efficient privacy-preserving identification framework based on layered sparse coding. The key idea of the proposed framework is a sparsifying trans…