Promises of conic relaxation for contingency-constrained optimal power flow problem. - Ramtin Madani; Morteza Ashraphijuo; Javad Lavaei (Allerton, 2014)

Inverse function theorem for polynomial equations using semidefinite programming. - Morteza Ashraphijuo; Ramtin Madani; Javad Lavaei (CDC, 2015)

A strong semidefinite programming relaxation of the unit commitment problem. - Morteza Ashraphijuo; Salar Fattahi; Javad Lavaei; Alper Atamtürk (CDC, 2016)

Characterization of rank-constrained feasibility problems via a finite number of convex programs. - Morteza Ashraphijuo; Ramtin Madani; Javad Lavaei (CDC, 2016)

Power system state estimation with a limited number of measurements. - Ramtin Madani; Morteza Ashraphijuo; Javad Lavaei; Ross Baldick (CDC, 2016)

Deterministic and Probabilistic Conditions for Finite Completability of Low Rank Tensor. - Morteza Ashraphijuo; Vaneet Aggarwal; Xiaodong Wang 001 (CoRR, 2016)

An approximation of the CP-rank of a partially sampled tensor. - Morteza Ashraphijuo; Xiaodong Wang 001; Vaneet Aggarwal (Allerton, 2017)

A characterization of sampling patterns for low-tucker-rank tensor completion problem. - Morteza Ashraphijuo; Vaneet Aggarwal; Xiaodong Wang 001 (ISIT, 2017)

A characterization of sampling patterns for low-rank multi-view data completion problem. - Morteza Ashraphijuo; Xiaodong Wang 001; Vaneet Aggarwal (ISIT, 2017)

Characterization of Deterministic and Probabilistic Sampling Patterns for Finite Completability of Low Tensor-Train Rank Tensor. - Morteza Ashraphijuo; Xiaodong Wang 001 (CoRR, 2017)

Scaled Nuclear Norm Minimization for Low-Rank Tensor Completion. - Morteza Ashraphijuo; Xiaodong Wang 001 (CoRR, 2017)

Deterministic and Probabilistic Conditions for Finite Completability of Low-rank Multi-View Data. - Morteza Ashraphijuo; Xiaodong Wang 001; Vaneet Aggarwal (CoRR, 2017)

Fundamental Conditions for Low-CP-Rank Tensor Completion. - Morteza Ashraphijuo; Xiaodong Wang 001 (J. Mach. Learn. Res., 2017)

Rank Determination for Low-Rank Data Completion. - Morteza Ashraphijuo; Xiaodong Wang 001; Vaneet Aggarwal (J. Mach. Learn. Res., 2017)

A Characterization of Sampling Patterns for Union of Low-Rank Subspaces Retrieval Problem. - Morteza Ashraphijuo; Xiaodong Wang 001 (ISAIM, 2018)

On Deterministic Sampling Patterns for Robust Low-Rank Matrix Completion. - Morteza Ashraphijuo; Vaneet Aggarwal; Xiaodong Wang 001 (IEEE Signal Process. Lett., 2018)

On the DoF of Two-Way 2×2×2 MIMO Relay Networks. - Mehdi Ashraphijuo; Morteza Ashraphijuo; Xiaodong Wang 001 (IEEE Trans. Veh. Technol., 2018)

Fundamental conditions on the sampling pattern for union of low-rank subspaces retrieval. - Morteza Ashraphijuo; Xiaodong Wang 001 (Ann. Math. Artif. Intell., 2019)

Clustering a union of low-rank subspaces of different dimensions with missing data. - Morteza Ashraphijuo; Xiaodong Wang 001 (Pattern Recognit. Lett., 2019)

Deterministic and Probabilistic Conditions for Finite Completability of Low-Tucker-Rank Tensor. - Morteza Ashraphijuo; Vaneet Aggarwal; Xiaodong Wang 001 (IEEE Trans. Inf. Theory, 2019)

Low-Rank Data Completion With Very Low Sampling Rate Using Newton's Method. - Morteza Ashraphijuo; Xiaodong Wang 001; Junwei Zhang 006 (IEEE Trans. Signal Process., 2019)

Characterization Of sampling patterns for low-tt-rank tensor retrieval. - Morteza Ashraphijuo; Xiaodong Wang 001 (Ann. Math. Artif. Intell., 2020)

Union of Low-Rank Tensor Spaces: Clustering and Completion. - Morteza Ashraphijuo; Xiaodong Wang 001 (J. Mach. Learn. Res., 2020)

Structured Alternating Minimization for Union of Nested Low-Rank Subspaces Data Completion. - Morteza Ashraphijuo; Xiaodong Wang 001 (IEEE J. Sel. Areas Inf. Theory, 2020)

Fundamental sampling patterns for low-rank multi-view data completion. - Morteza Ashraphijuo; Xiaodong Wang 001; Vaneet Aggarwal (Pattern Recognit., 2020)