154 citations · 861 across the 94 of their papers we have counts for
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Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs
Karthik Elamvazhuthi, Xuechen Zhang, Samet Oymak +1
In numerous robotics and mechanical engineering applications, among others, data is often constrained on smooth manifolds due to the presence of rotational degrees of freedom. Comm…
Certainty Equivalent Quadratic Control for Markov Jump Systems
Zhe Du, Yahya Sattar, Davoud Ataee Tarzanagh +3
Real-world control applications often involve complex dynamics subject to abrupt changes or variations. Markov jump linear systems (MJS) provide a rich framework for modeling such…
Simple Error Bounds for Regularized Noisy Linear Inverse Problems
Christos Thrampoulidis, Samet Oymak, Babak Hassibi
Consider estimating a structured signal from linear, underdetermined and noisy measurements , via solving a variant of…
A Simplified Approach to Recovery Conditions for Low Rank Matrices
Samet Oymak, Karthik Mohan, Maryam Fazel +1
Recovering sparse vectors and low-rank matrices from noisy linear measurements has been the focus of much recent research. Various reconstruction algorithms have been studied, incl…
New Null Space Results and Recovery Thresholds for Matrix Rank Minimization
Samet Oymak, Babak Hassibi
Nuclear norm minimization (NNM) has recently gained significant attention for its use in rank minimization problems. Similar to compressed sensing, using null space characterizatio…