Results 111 to 120 of about 223,331 (198)

Robust Factorizations and Colorings of Tensor Graphs

SIAM Journal on Discrete Mathematics
Since the seminal result of Karger, Motwani, and Sudan, algorithms for approximate 3-coloring have primarily centered around SDP-based rounding. However, it is likely that important combinatorial or algebraic insights are needed in order to break the $n^{o(1)}$ threshold.
Joshua Brakensiek, Sami Davies
openaire   +3 more sources

Communication Efficient Federated Generalized Tensor Factorization for Collaborative Health Data Analytics. [PDF]

Proc Int World Wide Web Conf, 2021
Ma J, Zhang Q, Lou J, Xiong L, Ho JC.
europepmc   +1 more source

Semantic Social Network Analysis by Cross-Domain Tensor Factorization

, 2017
Analyzing “what topics” a user discusses with others is important in social network analysis. Since social relationships can be represented as multiobject relationships (e.g., those composed of a user, another user, and the topic of communication), they ...
Xiaohui Lu, Zhang, Qingpeng, Hendler, James A., Nakatsuji, Makoto, Bassem Makni, Lu, Xiaohui, Makni, Bassem, Qingpeng Zhang, Makoto Nakatsuji, James A. Hendler   +9 more
core   +1 more source

Author Correction: Avocado: a multi-scale deep tensor factorization method learns a latent representation of the human epigenome. [PDF]

Genome Biol, 2021
Schreiber J, Durham T, Bilmes J, Noble WS.   +3 more
europepmc   +1 more source

Multi-mode Tensor Train Factorization with Spatial-spectral Regularization for Remote Sensing Images Recovery

, 2022
Tensor train (TT) factorization and corresponding TT rank, which can well express the low-rankness and mode correlations of higher-order tensors, have attracted much attention in recent years.
Qi, Liqun, Wan, Shaochun, Xu, Yanwei, Yu, Gaohang   +3 more
core  

Factorizing binary tensors into quantics tensor trains

The conversion of functions to quantics tensor trains is a well-established procedure and can either be done analytically or numerically. Numerical conversion schemes are based on singular value decompositions, where access to the full tensor is necessary, or on cross interpolations, which only depend on sampling a function.
Haubenwallner, Paul, Heller, Matthias
openaire   +2 more sources

Fast Quantum Simulation of Electronic Structure by Spectral Amplification

Physical Review X
The most advanced techniques using fault-tolerant quantum computers to estimate the ground-state energy of a chemical Hamiltonian involve compression of the Coulomb operator through tensor factorizations, enabling efficient block encodings of the ...
Guang Hao Low, Robbie King, Dominic W. Berry, Qiushi Han, A. Eugene DePrince, III, Alec F. White, Ryan Babbush, Rolando D. Somma, Nicholas C. Rubin   +8 more
doaj   +1 more source

Unique Tensor Factorization of Algebras

, 1998
Tensor product decomposition of algebras is known to be non-unique in many cases. But, as will be shown here, an additively indecomposable, finite-dimensional C-algebra A has an essentially unique tensor factorization A=A1x...xAr into non-trivial, x ...
Nüsken, Michael
core  

Distributed flexible nonlinear tensor factorization

, 2016
Tensor factorization is a powerful tool to analyse multi-way data. Recently proposed nonlinear factorization methods, although capable of capturing complex relationships, are computationally quite expensive and may suffer a severe learning bias in case ...
Gharamani, Z, Zhe, S, Xu, Z, Wang, P, Qi, Y, ,, Zhang, K, Lee, KC   +7 more
core  

Accelerated unconstrained latent factorization of tensor model for Web service QoS estimation

Tongxin xuebao
Aiming at the problem that the Web service quality of service (QoS) estimation methods based on the non-negative latent factorization of tensor model (NLFT) depend heavily on non-negative initial random data and specially designed non-negative training ...
Mingwei LIN, Wenqiang LI, Xiuqin XU, Jian LIU   +3 more
doaj   +2 more sources