7 citations · 27 across the 17 of their papers we have counts for
25 papers
On Neural Network approximation of ideal adversarial attack and convergence of adversarial training
Rajdeep Haldar, Qifan Song
Adversarial attacks are usually expressed in terms of a gradient-based operation on the input data and model, this results in heavy computations every time an attack is generated.…
A New Paradigm for Generative Adversarial Networks based on Randomized Decision Rules
Sehwan Kim, Qifan Song, Faming Liang
The Generative Adversarial Network (GAN) was recently introduced in the literature as a novel machine learning method for training generative models. It has many applications in st…
Matrix Completion from General Deterministic Sampling Patterns
Hanbyul Lee, Rahul Mazumder, Qifan Song +1
Most of the existing works on provable guarantees for low-rank matrix completion algorithms rely on some unrealistic assumptions such that matrix entries are sampled randomly or th…
PyXAB -- A Python Library for -Armed Bandit and Online Blackbox Optimization Algorithms
Wenjie Li, Haoze Li, Jean Honorio +1
We introduce a Python open-source library for -armed bandit and online blackbox optimization named PyXAB. PyXAB contains the implementations for more than 10 $\mathcal…
Support Recovery in Sparse PCA with Non-Random Missing Data
Hanbyul Lee, Qifan Song, Jean Honorio
We analyze a practical algorithm for sparse PCA on incomplete and noisy data under a general non-random sampling scheme. The algorithm is based on a semidefinite relaxation of the…
Support Recovery in Sparse PCA with Incomplete Data
Hanbyul Lee, Qifan Song, Jean Honorio
We study a practical algorithm for sparse principal component analysis (PCA) of incomplete and noisy data. Our algorithm is based on the semidefinite program (SDP) relaxation of th…