Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Tabaghi P"'
Autor:
Luo, Zhishang, Hy, Truong Son, Tabaghi, Puoya, Koh, Donghyeon, Defferrard, Michael, Rezaei, Elahe, Carey, Ryan, Davis, Rhett, Jain, Rajeev, Wang, Yusu
The run-time for optimization tools used in chip design has grown with the complexity of designs to the point where it can take several days to go through one design cycle which has become a bottleneck. Designers want fast tools that can quickly give
Externí odkaz:
http://arxiv.org/abs/2404.00477
Autor:
Tabaghi, Puoya, Wang, Yusu
A main object of our study is multiset functions -- that is, permutation-invariant functions over inputs of varying sizes. Deep Sets, proposed by \cite{zaheer2017deep}, provides a \emph{universal representation} for continuous multiset functions on s
Externí odkaz:
http://arxiv.org/abs/2310.13829
Principal Component Analysis (PCA) is a workhorse of modern data science. While PCA assumes the data conforms to Euclidean geometry, for specific data types, such as hierarchical and cyclic data structures, other spaces are more appropriate. We study
Externí odkaz:
http://arxiv.org/abs/2301.02750
Optimal transport provides a metric which quantifies the dissimilarity between probability measures. For measures supported in discrete metric spaces, finding the optimal transport distance has cubic time complexity in the size of the space. However,
Externí odkaz:
http://arxiv.org/abs/2210.12288
Publikováno v:
کتابداری و اطلاعرسانی, Vol 27, Iss 1, Pp 159-185 (2024)
Objective: The purpose of this study in knowledge-based organizations is to investigate the impact of future developments in information and communication technologies (ICT) on organizational knowledge engineering. Given the importance of information
Externí odkaz:
https://doaj.org/article/d436c7f58cca4424bd98d15dd96eb563
The problem of fitting distances by tree-metrics has received significant attention in the theoretical computer science and machine learning communities alike, due to many applications in natural language processing, phylogeny, cancer genomics and a
Externí odkaz:
http://arxiv.org/abs/2205.09721
Many high-dimensional practical data sets have hierarchical structures induced by graphs or time series. Such data sets are hard to process in Euclidean spaces and one often seeks low-dimensional embeddings in other space forms to perform the require
Externí odkaz:
http://arxiv.org/abs/2203.03730
Many high-dimensional and large-volume data sets of practical relevance have hierarchical structures induced by trees, graphs or time series. Such data sets are hard to process in Euclidean spaces and one often seeks low-dimensional embeddings in oth
Externí odkaz:
http://arxiv.org/abs/2109.03781
Embedding methods for product spaces are powerful techniques for low-distortion and low-dimensional representation of complex data structures. Here, we address the new problem of linear classification in product space forms -- products of Euclidean,
Externí odkaz:
http://arxiv.org/abs/2102.10204
Autor:
Tabaghi, Puoya, Dokmanic, Ivan
Congruent Procrustes analysis aims to find the best matching between two point sets through rotation, reflection and translation. We formulate the Procrustes problem for hyperbolic spaces, review the canonical definition of the center of point sets,
Externí odkaz:
http://arxiv.org/abs/2102.03723