Researchers proposed an automatic structured pruning framework, AutoCompress, which adopts the 2018 ADMM-based weight pruning algorithm and outperforms previous automatic model compression methods while maintaining high accuracy.
Proposed by researchers from the Rutgers University and Samsung AI Center in the UK, CookGAN uses an attention-based ingredients-image association model to condition a generative neural network tasked with synthesizing meal images.
Google teamed up with researchers from Synthesis AI and Columbia University to introduce a deep learning approach called ClearGrasp as a first step to teaching machines how to “see” transparent materials.
Researchers from Google Brain and Carnegie Mellon University have released models trained with a semi-supervised learning method called “Noisy Student” that achieve 88.4 percent top-1 accuracy on ImageNet.
Leading scientific publication Nature announced it is launching a trial starting this week that will give authors of newly published papers the option of appending contents of the discussions they’ve had with and reports they’ve received from their reviewers.
In a new paper, researchers from the New York University and Modl.ai, a company applying machine learning to game developing, suggest that simple spacial processing methods such as rotation, translation and cropping could help increase model generality.
A new paper from the University of Washington Seattle and the University of California, Berkeley looks at saddle points on Riemannian Manifolds. In this article Synced takes a deep dive into this important research.
On Fridays, Synced selects seven studies from the last seven days that present topical, innovative or otherwise interesting or important research that we believe may be of special interest to our readers.
Synced has surveyed last week’s crop of papers in the fields of machine learning, computer vision, computation and language, and beyond, and identified seven studies that we believe may be of special interest to our readers.
The Synced Machine Intelligence Awards 2019 focus is “the power of industry” and the selection process will key in on AI companies’ products, application cases and industry landings — with the most noteworthy companies chosen based on real and objective industry performance.