news.ucsb.edu

Proving the value of an old algorithm in training deep-learning models for AI

For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...
InfoQ

Google Uses AutoML to Discover More Efficient AI Training Algorithm

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
InfoQ

Berkeley Researchers Announce Robot Training Algorithm DayDreamer

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Birgitta Böckeler, Distinguished Engineer at ...
Science Daily

Training algorithm breaks barriers to deep physical neural networks

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...
VentureBeat

New AI framework autonomously optimizes training data, architectures and algorithms — outperforming human baselines

AI R&D runs on a cycle of hypothesis, experiment, and analysis — each step demanding substantial manual engineering effort. A new framework from researchers at SII-GAIR aims to close that bottleneck ...
Technology Networks

Predictive Modeling for Compound Prioritization

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...