A type of artificial intelligence that focuses on designing systems that can learn from and make decisions based on data.
The article presents DOO-RE, a dataset aimed at recognizing user activities using machine learning methods and IoT technology. The dataset includes streams from various ambient sensors like Sound and Projector,…
Continue readingThe paper introduces a multimodal Theory of Mind (ToM) question answering benchmark, MMToM-QA, and a new method, BIP-ALM (Bayesian Inverse Planning Accelerated by Language Models), for engineering multimodal ToM capacity….
Continue readingThis academic article introduces DeLF (Designing Learning Environments with Foundation Models), a method for designing components of the Reinforcement Learning (RL) environment for a specific, user-intended application. The authors focus…
Continue readingThe research introduces the Continuous Time Continuous Space Homeostatic Regulated Reinforcement Learning (CTCS-HRRL) framework. This framework extends the Homeostatic Regulated Reinforcement Learning (HRRL) framework to a continuous time-space environment. The…
Continue readingThe article, published in the International Journal of Computer Science & Information Technology, discusses a method for predicting cryptocurrency prices using the Adaptive Network Based Fuzzy Inference System (ANFIS). The…
Continue readingThis paper introduces Brave, a protocol that ensures Byzantine resilience and privacy-preserving property for Peer-to-Peer (P2P) Federated Learning (FL). In FL, multiple participants collaboratively train a global machine learning model…
Continue readingThe paper presents O2C, a system designed to enforce OS kernel compartmentalization on the fly using the latest advancements of the eBPF ecosystem and machine learning. O2C provides immediate remediation…
Continue readingThe study discusses the development of a unique binary linear tree commitment-based ownership protection model for distributed machine learning. This model ensures computational integrity with limited overhead and concise proof….
Continue readingThe article explores the possibility of AI systems learning deceptive behavior and maintaining this behavior despite safety training techniques. This is demonstrated by training models to write secure code for…
Continue readingThe article discusses the development of SEShield, a framework designed to detect social engineering (SE) attacks in-browser. It consists of three components: SECrawler, a custom security crawler that gathers examples…
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