4 citations · 13 across the 6 of their papers we have counts for
6 papers
An Efficient Nonlinear Acceleration method that Exploits Symmetry of the Hessian
Huan He, Shifan Zhao, Ziyuan Tang +3
Nonlinear acceleration methods are powerful techniques to speed up fixed-point iterations. However, many acceleration methods require storing a large number of previous iterates an…
GDA-AM: On the effectiveness of solving minimax optimization via Anderson Acceleration
Huan He, Shifan Zhao, Yuanzhe Xi +2
Many modern machine learning algorithms such as generative adversarial networks (GANs) and adversarial training can be formulated as minimax optimization. Gradient descent ascent (…
Temporal Network Embedding via Tensor Factorization
Jing Ma, Qiuchen Zhang, Jian Lou +2
Representation learning on static graph-structured data has shown a significant impact on many real-world applications. However, less attention has been paid to the evolving nature…
CrowdTeacher: Robust Co-teaching with Noisy Answers & Sample-specific Perturbations for Tabular Data
Mani Sotoodeh, Li Xiong, Joyce C. Ho
Samples with ground truth labels may not always be available in numerous domains. While learning from crowdsourcing labels has been explored, existing models can still fail in the…
Controlled Molecule Generator for Optimizing Multiple Chemical Properties
Bonggun Shin, Sungsoo Park, JinYeong Bak +1
Generating a novel and optimized molecule with desired chemical properties is an essential part of the drug discovery process. Failure to meet one of the required properties can fr…
SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors
Ardavan Afshar, Kejing Yin, Sherry Yan +4
Existing tensor factorization methods assume that the input tensor follows some specific distribution (i.e. Poisson, Bernoulli, and Gaussian), and solve the factorization by minimi…