Tensor Decomposition

127 papers with code • 0 benchmarks • 0 datasets

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Use these libraries to find Tensor Decomposition models and implementations
3 papers

Most implemented papers

Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition

jacobgil/pytorch-tensor-decompositions 19 Dec 2014

We propose a simple two-step approach for speeding up convolution layers within large convolutional neural networks based on tensor decomposition and discriminative fine-tuning.

MEIM: Multi-partition Embedding Interaction Beyond Block Term Format for Efficient and Expressive Link Prediction

tranhungnghiep/meim-kge 30 Sep 2022

Knowledge graph embedding aims to predict the missing relations between entities in knowledge graphs.

When Are Nonconvex Problems Not Scary?

sunju/pr_plain 21 Oct 2015

In this note, we focus on smooth nonconvex optimization problems that obey: (1) all local minimizers are also global; and (2) around any saddle point or local maximizer, the objective has a negative directional curvature.

Canonical Tensor Decomposition for Knowledge Base Completion

facebookresearch/kbc ICML 2018

The problem of Knowledge Base Completion can be framed as a 3rd-order binary tensor completion problem.

Convolutional neural networks with low-rank regularization

chengtaipu/lowrankcnn 19 Nov 2015

Recently, tensor decompositions have been used for speeding up CNNs.

Expressive power of recurrent neural networks

rballester/tntorch ICLR 2018

In this paper, we prove the expressive power theorem (an exponential lower bound on the width of the equivalent shallow network) for a class of recurrent neural networks -- ones that correspond to the Tensor Train (TT) decomposition.

Learning a Wavelet-like Auto-Encoder to Accelerate Deep Neural Networks

tianshuichen/Wavelet-like-Auto-Encoder 20 Dec 2017

In this work, aiming at a general and comprehensive way for neural network acceleration, we develop a Wavelet-like Auto-Encoder (WAE) that decomposes the original input image into two low-resolution channels (sub-images) and incorporate the WAE into the classification neural networks for joint training.

Binarized Knowledge Graph Embeddings

KokiKishimoto/cp_decomposition 8 Feb 2019

This limitation is expected to become more stringent as existing knowledge graphs, which are already huge, keep steadily growing in scale.

Nonnegative Tucker Decomposition with Beta-divergence for Music Structure Analysis of Audio Signals

amarmore/musicntd 27 Oct 2021

Nonnegative Tucker decomposition (NTD), a tensor decomposition model, has received increased interest in the recent years because of its ability to blindly extract meaningful patterns, in particular in Music Information Retrieval.

Dimensionality Reduction of Longitudinal 'Omics Data using Modern Tensor Factorization

uriamorp/mprod_package 28 Nov 2021

Precision medicine is a clinical approach for disease prevention, detection and treatment, which considers each individual's genetic background, environment and lifestyle.