Word embeddings in NLP

We will discuss word embeddings this week. Word embeddings represent a fundamental shift in natural language processing (NLP) ...
Forbes

Getting Serious About Handling Sparse Models! Re-Examining Dense Tensors In The AI Age

What can you do about data sparsity? What do you do when you have a matrix with a bunch of zeros in it, and you can't get a good look at a complex system because so many of the nodes are empty? Matrix ...
EurekAlert!

DSD-MatchingNet: Deformable sparse-to-dense feature matching for learning accurate correspondences

Detection methods based on deep convolutional networks search for interest points by constructing response maps using supervised, self-supervised, and unsupervised methods. Supervised methods use ...
Business Wire

Numenta Demonstrates 100x Performance Acceleration in Deep Learning Networks Using Sparse Techniques

REDWOOD CITY, Calif.--(BUSINESS WIRE)--Numenta, Inc. announced it has achieved greater than 100x performance improvements on inference tasks in deep learning networks without any loss in accuracy. In ...
Semiconductor Engineering

ISA and Microarchitecture Extensions Over Dense Matrix Engines to Support Flexible Structured Sparsity for CPUs (Georgia Tech, Intel Labs)

A technical paper titled “VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs” was published (preprint) by researchers at Georgia Tech and Intel Labs. “Deep ...