papers

Publications (16)

cs.CL2022

LEAP: Learnable Pruning for Transformer-based Models

Zhewei Yao, Xiaoxia Wu, Linjian Ma +4

Pruning is an effective method to reduce the memory footprint and computational cost associated with large natural language processing models. However, current pruning algorithms e…

cs.CV2023

TongueSAM: An Universal Tongue Segmentation Model Based on SAM with Zero-Shot

Shan Cao, Qunsheng Ruan, Linjian Ma

Tongue segmentation serves as the primary step in automated TCM tongue diagnosis, which plays a significant role in the diagnostic results. Currently, numerous deep learning based…

math.NA2020

Comparison of Accuracy and Scalability of Gauss-Newton and Alternating Least Squares for CP Decomposition

Navjot Singh, Linjian Ma, Hongru Yang +1

Alternating least squares is the most widely used algorithm for CP tensor decomposition. However, alternating least squares may exhibit slow or no convergence, especially when high…

quant-ph2023

Tensor Rank and Other Multipartite Entanglement Measures of Graph States

Louis Schatzki, Linjian Ma, Edgar Solomonik +1

Graph states play an important role in quantum information theory through their connection to measurement-based computing and error correction. Prior work has revealed elegant conn…

quant-ph2024

Approximate Contraction of Arbitrary Tensor Networks with a Flexible and Efficient Density Matrix Algorithm

Linjian Ma, Matthew Fishman, Miles Stoudenmire +1

Tensor network contractions are widely used in statistical physics, quantum computing, and computer science. We introduce a method to efficiently approximate tensor network contrac…

cs.CV2025

Probing Human Visual Robustness with Neurally-Guided Deep Neural Networks

Zhenan Shao, Linjian Ma, Yiqing Zhou +4

Humans effortlessly navigate the dynamic visual world, yet deep neural networks (DNNs), despite excelling at many visual tasks, are surprisingly vulnerable to minor image perturbat…