Truthout

MN Senate Passes Nation’s First Ban on Apps That Create Nonconsensual Deepfakes

The legislation is the first of its kind in the US to take on the growing phenomena of tech-facilitated sexual abuse.
Opinion
HackadayOpinion

Why Model Collapse In LLMs Is Inevitable With Self-Learning

There is a persistent belief in the ‘AI’ community that large language models (LLMs) have the ability to learn and self-improve by tweaking the weights in their vector space. Although ...

AI computation enables clearer views of the deep brain, bypassing the need for expensive equipment

Professor Iksung Kang (School of Electrical Engineering), in collaboration with Professor Na Ji's research team at UC ...
Frontiers

Synergic entanglements between Structural Biology and Machine Learning: Looking into the future

The rapid advances in machine learning (ML) and artificial intelligence (AI) are transforming biology and opening new directions for scientific inquiry.
TMCnet

MicroAlgo Inc. Develops Quantum Algorithm Technology for Feedforward Neural Networks to Drive Neural Network Revolution

MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced that they have developed a set of quantum algorithms for feedforward neural networks, breaking through the performance ...
Frontiers

Low-rank tensor completion with fractal-inspired multi-scale energy regularization

Low-rank tensor completion has become a fundamental tool for recovering high-dimensional data from incomplete observations. However, conventional methods rely primarily on algebraic low-rank priors ...
The New York Times

Trump Administration Approves Ultra-Deepwater Oil Drilling Plan

The $5 billion project in the Gulf of Mexico is expected to help produce up to 10 billion barrels of oil by the end of this decade. Critics say it could endanger people and marine life. By Lisa ...
IEEE

Research on the Robustness of Cooperative Multi-Agent Deep Reinforcement Learning: A Policy Regularization Method Based on Transfer Learning

Huang et al. [1]first applied adversarial attacks to deep reinforcement learning(DRL) and discovered the security vulnerabilities of DRL, there are many attack and defense methods [2]–[5] proposed for ...
Scientific Research Publishing

Moradi, R., Berangi, R. and Minaei, B. (2019) A Survey of Regularization Strategies for Deep Models. Artificial Intelligence Review, 53, 3947-3986.

ABSTRACT: Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of ...
Scientific Research Publishing

Nusrat, I. and Jang, S. (2018) A Comparison of Regularization Techniques in Deep Neural Networks. Symmetry, 10, Article 648.

ABSTRACT: Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of ...
IEEE

A deep dictionary learning framework for device-free localization based on nonconvex sparse regularization and DC programming

Abstract: Received signal strength (RSS) based device-free localization (DFL) is commonly used in the Internet of Things (IoT) field. However, the current DFL algorithms have limitations in terms of ...