6 papers
Conditional Indexing Lower Bounds and Normalization Boundaries for Elastic Subsequence Matching
Zemin Chao, Zitong Li, Xiangyu Gao +1
We study static indexes for exact subsequence matching over all equal-length windows of a time series. Under deterministic SETH, for every fixed and , we exclude…
A New Lower Bounding Paradigm and Tighter Lower Bounds for Elastic Similarity Measures
Zemin Chao, Boyu Xiao, Zitong Li +3
Elastic similarity measures are fundamental to time series similarity search because of their ability to handle temporal misalignments. These measures are inherently computationall…
Fused3S: Fast Sparse Attention on Tensor Cores
Zitong Li, Aparna Chandramowlishwaran
Sparse attention is a core building block in many leading neural network models, from graph-structured learning to sparse sequence modeling. It can be decomposed into a sequence of…
Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE Solvers
Arthur Feeney, Zitong Li, Ramin Bostanabad +1
Mosaic Flow is a novel domain decomposition method designed to scale physics-informed neural PDE solvers to large domains. Its unique approach leverages pre-trained networks on sma…
Efficient Computation of Tucker Decomposition for Streaming Scientific Data Compression
Saibal De, Zitong Li, Hemanth Kolla +1
The Tucker decomposition, an extension of singular value decomposition for higher-order tensors, is a useful tool in analysis and compression of large-scale scientific data. While…
Parallel Randomized Tucker Decomposition Algorithms
Rachel Minster, Zitong Li, Grey Ballard
The Tucker tensor decomposition is a natural extension of the singular value decomposition (SVD) to multiway data. We propose to accelerate Tucker tensor decomposition algorithms b…