Adam Dziedzic, a senior scientist at CISPA, is working on addressing the major challenges of machine learning such as privacy, confidentiality, robustness, interpretability, security,…
Browsing: Robustness
This article discusses the recent advancements in deep learning and its impact on various industries and domains. It highlights the success of deep learning…
Recent revelations in the AI landscape have highlighted the need for trustworthy AI systems. IBM has established five principles of trustworthy AI, including explainability…
Marzyeh Ghassemi, an assistant professor at MIT, discusses the importance of creating “healthy” machine learning models that are robust, private, and fair in the…
This article presents a proposed botnet detection approach that integrates hybrid feature selection strategies with an additional trees ensemble classifier. The model is able…
This Special Issue focuses on the most recent advances in the models, algorithms, theories, and applications of Graph Machine Learning (GML), both in academic…
Adversarial Machine Learning is a rapidly growing research area at the intersection of machine learning, cybersecurity, and artificial intelligence. It deals with the study…
Blockchain and Artificial Intelligence (AI) have emerged as two of the most influential technological advancements in the modern era. Blockchain offers a decentralized ledger…
Researchers at the University of Zurich have developed a method called PlantServation which uses big data, machine learning and field observations to show how…
Rekord, a leading IoT connectivity company, has achieved a groundbreaking new record as the primary contributor of over 100 million transactions processed on the…