Van Vu

30 papers A* 3B 1Journal 24Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Eigenvalue Stability and New Perturbation Bounds for the extremal eigenvalues of a matrix.
CoRR
Phuc Tran, Van Vu
2025 J jnl
Davis-Kahan Theorem under a moderate gap condition.
CoRR
Phuc Tran, Van Vu
2025 J jnl
Fast exact recovery of noisy matrix from few entries: the infinity norm approach.
CoRR
BaoLinh Tran, Van Vu
2025 J jnl
New perturbation bounds for low rank approximation of matrices via contour analysis.
CoRR
Phuc Tran, Van Vu
2025 J jnl
The "Power of Few" Phenomenon: The Sparse Case.
Random Struct. Algorithms
BaoLinh Tran, Van Vu
2024 J jnl
A Short Proof of Kahn-Kalai Conjecture.
Electron. J. Comb.
Phuc Tran, Van Vu
2024 J jnl
Matrices With Gaussian Noise: Optimal Estimates for Singular Subspace Perturbation.
IEEE Trans. Inf. Theory
Sean O'Rourke, Van Vu, Ke Wang
2024 A* conf
Matrix Perturbation: Davis-Kahan in the Infinity Norm.
SODA
Abhinav Bhardwaj, Van Vu
2024 J jnl
Matrix perturbation bounds via contour bootstrapping.
CoRR
Phuc Tran, Van Vu
2023 J jnl
Entry-wise dissipation for singular vector perturbation bounds.
CoRR
Abhinav Bhardwaj, Van Vu
2023 B conf
Optimal Subspace Perturbation Bounds under Gaussian Noise.
ISIT
Sean O'Rourke, Van Vu, Ke Wang
2023 J jnl
Reaching a Consensus on Random Networks: The Power of Few.
Theory Comput.
Linh V. Tran, Van Vu
2022 J jnl
VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography.
CoRR
Hieu T. Nguyen, Ha Q. Nguyen, Hieu H. Pham, Khanh Lam, Linh T. Le, Minh Dao, Van Vu
2021 — conf
VinDr-SpineXR: A Deep Learning Framework for Spinal Lesions Detection and Classification from Radiographs.
MICCAI (5)
Hieu T. Nguyen, Hieu H. Pham, Nghia T. Nguyen, Ha Q. Nguyen, Thang Q. Huynh, Minh Dao, Van Vu
2021 J jnl
VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs.
CoRR
Hieu T. Nguyen, Hieu H. Pham, Nghia T. Nguyen, Ha Q. Nguyen, Thang Q. Huynh, Minh Dao, Van Vu
2020 — conf
Reaching a Consensus on Random Networks: The Power of Few.
APPROX-RANDOM
Linh V. Tran, Van Vu
2019 J jnl
Law of the iterated logarithm for random graphs.
Random Struct. Algorithms
Asaf Ferber, Daniel Montealegre, Van Vu
2019 J jnl
Spectrum of Complex Networks.
Internet Math.
Daniel Montealegre, Van Vu
2018 J jnl
A Simple SVD Algorithm for Finding Hidden Partitions.
Comb. Probab. Comput.
Van Vu
2018 J jnl
Packing perfect matchings in random hypergraphs.
Random Struct. Algorithms
Asaf Ferber, Van Vu
2018 J jnl
Random perturbation and matrix sparsification and completion.
CoRR
Sean O'Rourke, Van Vu, Ke Wang
2017 J jnl
Random matrices have simple spectrum.
Comb.
Terence Tao, Van Vu
2016 J jnl
Anti-concentration for Polynomials of Independent Random Variables.
Theory Comput.
Raghu Meka, Oanh Nguyen, Van Vu
2016 J jnl
Eigenvectors of random matrices: A survey.
J. Comb. Theory A
Sean O'Rourke, Van Vu, Ke Wang
2015 J jnl
Anti-concentration for random polynomials.
CoRR
Oanh Nguyen, Van Vu
2015 A* conf
Random Matrices: l1 Concentration and Dictionary Learning with Few Samples.
FOCS
Kyle Luh, Van Vu
2015 A* conf
Stochastic Block Model and Community Detection in Sparse Graphs: A spectral algorithm with optimal rate of recovery.
COLT
Peter Chin, Anup Rao, Van Vu
2015 J jnl
Stochastic Block Model and Community Detection in the Sparse Graphs: A spectral algorithm with optimal rate of recovery.
CoRR
Peter Chin, Anup Rao, Van Vu
2014 J jnl
A simple SVD algorithm for finding hidden partitions.
CoRR
Van Vu
2011 J jnl
Singular vectors under random perturbation.
Random Struct. Algorithms
Van Vu