Tensor Decomposition
126 papers with code • 0 benchmarks • 0 datasets
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Use these libraries to find Tensor Decomposition models and implementationsMost implemented papers
Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition
jacobgil/pytorch-tensor-decompositions
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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
Knowledge graph embedding aims to predict the missing relations between entities in knowledge graphs.
When Are Nonconvex Problems Not Scary?
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
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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
Recently, tensor decompositions have been used for speeding up CNNs.
Expressive power of recurrent neural networks
rballester/tntorch
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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
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
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
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
Precision medicine is a clinical approach for disease prevention, detection and treatment, which considers each individual's genetic background, environment and lifestyle.
