Heurísticas Aplicadas a la Comparación - diffeo - de Binarios
Explora técnicas avanzadas de comparación de binarios utilizando heurísticas, mejorando la eficiencia en análisis de malware y seguridad informática.
Towards Values-Based NLP
Explore the future of NLP with Pascale Fung as she discusses the importance of integrating ethical values and human-centric approaches in developing advanced language technologies.
The Rise of Hypersocial Artificial Intelligence
Explore the emergence of hypersocial AI and its implications for global security and peace with insights from a former California Supreme Court justice and international policy expert.
Bias Preservation in Machine Learning - The Legality of Fairness Metrics Under EU Non-Discrimination Law
Explore the legal implications of fairness metrics in machine learning under EU non-discrimination law, examining bias preservation and its impact on algorithmic decision-making.
Explainable ML in the Wild - When Not to Trust Your Explanations
Explore the limitations and potential pitfalls of explainable machine learning, focusing on when to be cautious about trusting ML explanations in real-world applications.
Explainable ML in the Wild - When Not to Trust Your Explanations
Explore the limitations and potential pitfalls of explainable machine learning, focusing on when to be cautious about trusting ML explanations in real-world applications.
Evaluation of Adaptive Systems
Learn techniques for evaluating adaptive systems, including user modeling, personalization, and group-based approaches to improve search rankings and address data sparsity challenges.
Innovating with AI
Explore cutting-edge AI innovations and their impact on technology and society in this keynote address by Google's Ashwin Ram at the IUI 2019 conference.
Tea - A High-level Language and Runtime System for Automating Statistical Analysis
Introduces Tea, a declarative language for automating statistical analysis. Simplifies hypothesis testing by determining valid tests based on study design and assumptions, lowering barriers to accurate statistical research.
Digital Assistance for Quality Assurance - Augmenting Workspaces Using Deep Learning for Tracking Near-Symmetrical Objects
Innovative deep learning approach for quality assurance in manufacturing, focusing on tracking and measuring near-symmetrical objects like LEGO bricks using visual guides and fine-grained feature detection.
How to Work in the Car of the Future - A Neuroergonomical Study Assessing Concentration, Performance and Workload Based on Subjective, Behavioral and Neurophysiological Insights
Neuroergonomical study explores optimal car interior configurations for productive work during autonomous driving, assessing concentration, performance, and workload using subjective, behavioral, and EEG measures.
Algorithmic Fairness in Predicting Opioid Use Disorder using Machine Learning
Explore machine learning's role in predicting opioid use disorder, focusing on algorithmic fairness and ethical considerations in healthcare applications.
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information
Explore methods for assessing ML model fairness with limited data, addressing challenges in uncertain and incomplete information scenarios.
Reasons, Values, Stakeholders - A Philosophical Framework for Explainable AI
Explore a philosophical framework for explainable AI, examining the interplay between reasons, values, and stakeholders to enhance transparency and ethical considerations in artificial intelligence systems.
Hacking the Human Bias in AI
Explore human bias in AI systems, its impact on decision-making, and strategies to mitigate these biases for more equitable and ethical artificial intelligence.
Explainable AI in Industry - Practical Challenges and Lessons Learned
Explore practical challenges and industry insights on implementing explainable AI, featuring expert perspectives from leading tech companies and researchers.
Challenges of Incorporating Algorithmic Fairness into Industry Practice
Explore challenges in implementing algorithmic fairness in industry, covering stakeholder involvement, data gathering, resourcing, and prioritizing tradeoffs. Gain insights into practical approaches and potential pitfalls.
KinectFusion - Real-Time 3D Reconstruction and Interaction Using a Moving Depth Camera
Explore real-time 3D reconstruction using depth cameras in this award-winning talk on KinectFusion, showcasing innovative techniques for interactive spatial mapping and modeling.
Human Enhancement and the Future of BCI
Explore the impact of AI on neurotechnologies for human augmentation, including brain-computer interfaces, neurofeedback, and neuromodulation, and their potential to revolutionize human-computer interaction.
I Agree with the Decision, but They Didn't Deserve This - Future Developers' Perception of Fairness
Explore future developers' perceptions of algorithmic fairness, examining how they evaluate and interpret automated decision-making processes in various contexts.
Formalizing Trust in Artificial Intelligence - Prerequisites, Causes and Goals of Human Trust in AI
Explore the formalization of human trust in AI, examining prerequisites, causes, and goals in this research-focused presentation on the complex relationship between humans and artificial intelligence.