Publications (14)
Gradient Dynamic Approach to the Tensor Complementarity Problem
Xuezhong Wang, Maolin Che, Liqun Qi +1
Nonlinear gradient dynamic approach for solving the tensor complementarity problem (TCP) is presented. Theoretical analysis shows that each of the defined dynamical system models e…
Efficient randomized algorithms for the fixed Tucker-rank problem of Tucker decomposition with adaptive shifts
Maolin Che, Yimin Wei, Chong Wu +1
Randomized numerical linear algebra is proved to bridge theoretical advancements to offer scalable solutions for approximating tensor decomposition. This paper introduces fast rand…
Positive Definite Tensors to Nonlinear Complementarity Problems
Maolin Che, Liqun Qi, Yimin Wei
The main purpose of this note is to investigate some kinds of nonlinear complementarity problems (NCP). For the structured tensors, such as, symmetric positive definite tensors and…
ELFATT: Efficient Linear Fast Attention for Vision Transformers
Chong Wu, Maolin Che, Renjie Xu +2
The attention mechanism is the key to the success of transformers in different machine learning tasks. However, the quadratic complexity with respect to the sequence length of the…
Effective algorithms for tensor train decomposition via the UTV framework
Yuchao Wang, Maolin Che, Yimin Wei
The tensor-train (TT) decomposition is widely used to compress large tensors into a more compact form by exploiting their inherent data structures. A fundamental approach for const…
BFLA: Block-Filtered Long-Context Attention Mechanism
Chong Wu, Zhenan Feng, Renjie Xu +5
This paper proposes Block-Filtered Long-Context Attention (BFLA), a training-free sparse prefill attention mechanism for long-context inference. BFLA adopts a two-stage design. In…
Intrinsic Low-Tucker-Rank Theory and Unified Tensor CUR Decomposition for High-Dimensional Hyperinterpolation
Maolin Che, Yimin Wei, Chong Wu
High-dimensional hyperinterpolation is severely hampered by the curse of dimensionality, as its coefficient tensors grow exponentially with the ambient dimension. Existing research…
sparseGeoHOPCA: A Geometric Solution to Sparse Higher-Order PCA Without Covariance Estimation
Renjie Xu, Chong Wu, Maolin Che +3
We propose sparseGeoHOPCA, a novel framework for sparse higher-order principal component analysis (SHOPCA) that introduces a geometric perspective to high-dimensional tensor decomp…
UniFormer: Unified and Efficient Transformer for Reasoning Across General and Custom Computing
Zhuoheng Ran, Chong Wu, Renjie Xu +2
The success of neural networks such as convolutional neural networks (CNNs) has been largely attributed to their effective and widespread deployment on customised computing platfor…
How many integrals should be evaluated at least in two-dimensional hyperinterpolation?
Maolin Che, Congpei An, Yimin Wei +1
This paper introduces a novel approach to approximating continuous functions over high-dimensional hypercubes by integrating matrix CUR decomposition with hyperinterpolation techni…
Randomized algorithms for computing the tensor train approximation and their applications
Maolin Che, Yimin Wei, Hong Yan
In this paper, we focus on the fixed TT-rank and precision problems of finding an approximation of the tensor train (TT) decomposition of a tensor. Note that the TT-SVD and TT-cros…
Stochastic Tensors to Stochastic Tensor Complementarity Problems
Maolin Che, Liqun Qi, Yimin Wei
The main purpose of this paper is devoted to an introduction of the stochastic tensor complementarity problem. We consider the expected residual minimization formulation of the sto…
Efficient algorithms for Tucker decomposition via approximate matrix multiplication
Maolin Che, Yimin Wei, Hong Yan
This paper develops fast and efficient algorithms for computing Tucker decomposition with a given multilinear rank. By combining random projection and the power scheme, we propose…
Randomized algorithms for the low multilinear rank approximations of tensors
Maolin Che, Yimin Wei, Hong Yan
In this paper, we focus on developing randomized algorithms for the computation of low multilinear rank approximations of tensors based on the random projection and the singular va…