69 citations · 160 across the 29 of their papers we have counts for
7 papers · 1 filter
End to End Generative Meta Curriculum Learning For Medical Data Augmentation
Meng Li, Brian Lovell
Current medical image synthetic augmentation techniques rely on intensive use of generative adversarial networks (GANs). However, the nature of GAN architecture leads to heavy comp…
Unified Framework for Histopathology Image Augmentation and Classification via Generative Models
Meng Li, Chaoyi Li, Can Peng +1
Deep learning techniques have become widely utilized in histopathology image classification due to their superior performance. However, this success heavily relies on the availabil…
End-to-End Modeling via Information Tree for One-Shot Natural Language Spatial Video Grounding
Mengze Li, Tianbao Wang, Haoyu Zhang +9
Natural language spatial video grounding aims to detect the relevant objects in video frames with descriptive sentences as the query. In spite of the great advances, most existing…
Resilience-Motivated Distribution System Restoration Considering Electricity-Water-Gas Interdependency
Jiaxu Li, Yin Xu, Ying Wang +4
A major outage in the electricity distribution system may affect the operation of water and natural gas supply systems, leading to an interruption of multiple services to critical…
Geometry of the Minimum Volume Confidence Sets
Heguang Lin, Mengze Li, Daniel Pimentel-Alarcón +1
Computation of confidence sets is central to data science and machine learning, serving as the workhorse of A/B testing and underpinning the operation and analysis of reinforcement…
New Penalized Stochastic Gradient Methods for Linearly Constrained Strongly Convex Optimization
Meng Li, Paul Grigas, Alper Atamturk
For minimizing a strongly convex objective function subject to linear inequality constraints, we consider a penalty approach that allows one to utilize stochastic methods for probl…