Healthcare

Stanford and UC San Diego Researchers Propose A New Approach To Quickly Remove Traces of Sensitive User Information From Machine Learning Models

Machine learning works by sifting through databases and assigning various prediction weights to data features, such as an online shopper’s age, location, previous purchase history, or a streamer’s past viewing… Read More »Stanford and UC San Diego Researchers Propose A New Approach To Quickly Remove Traces of Sensitive User Information From Machine Learning Models

MIT Researchers Open-Sourced ‘MADDNESS’: An AI Algorithm That Speeds Up Machine Learning Using Approximate Matrix Multiplication (AMM)

Matrix multiplication is one of the essential operations in machine learning (ML). However, these operations are extensively computationally costly due to the extensive use of multiply-add instructions. Therefore, many studies… Read More »MIT Researchers Open-Sourced ‘MADDNESS’: An AI Algorithm That Speeds Up Machine Learning Using Approximate Matrix Multiplication (AMM)

Baidu Research Introduces PP-LCNet: A Lightweight CPU Convolutional Neural Network With Better Accuracy And Performance

Convolutional neural networks (CNNs) have been used to achieve computer vision applications for the past few years. These networks can be trained and applied in many fields, including image classification,… Read More »Baidu Research Introduces PP-LCNet: A Lightweight CPU Convolutional Neural Network With Better Accuracy And Performance

Facebook AI Unveils Dynatask, A New Paradigm For Benchmarking AI, Enabling Custom NLP Tasks For AI Community

Last year, Facebook AI launched Dynabench as a first-of-its-kind platform that rethinks benchmarking in artificial intelligence. Now, they are introducing ‘Dynatask’, a new feature unlocking Dynabench’s full capabilities for the AI community.… Read More »Facebook AI Unveils Dynatask, A New Paradigm For Benchmarking AI, Enabling Custom NLP Tasks For AI Community

MIT Researchers Introduce ‘MedKnowts’, A System That Combines Machine Learning And Human-Computer Interaction To Create A Better EHR

Electronic health records (EHRs) have become widely used in the hopes of saving time and improving patient care quality. Physicians, however, typically spend more time navigating these systems than dealing… Read More »MIT Researchers Introduce ‘MedKnowts’, A System That Combines Machine Learning And Human-Computer Interaction To Create A Better EHR

Researchers at TUM Introduce A Machine Learning Method That can Learn Local Equilibria in Symmetric Auction Games Using Artificial Neural Networks

Computer scientists have been researching the prospect of applying game theory and (AI) artificial intelligence technologies to chess, the abstract strategic board game, and other games for several decades. Another… Read More »Researchers at TUM Introduce A Machine Learning Method That can Learn Local Equilibria in Symmetric Auction Games Using Artificial Neural Networks