3 citations · 6 across the 6 of their papers we have counts for
6 papers
Optimistic Gradient Learning with Hessian Corrections for High-Dimensional Black-Box Optimization
Yedidya Kfir, Elad Sarafian, Sarit Kraus +1
Black-box algorithms are designed to optimize functions without relying on their underlying analytical structure or gradient information, making them essential when gradients are i…
Explaining Decisions of Agents in Mixed-Motive Games
Maayan Orner, Oleg Maksimov, Akiva Kleinerman +2
In recent years, agents have become capable of communicating seamlessly via natural language and navigating in environments that involve cooperation and competition, a fact that ca…
Contrastive Explainable Clustering with Differential Privacy
Dung Nguyen, Ariel Vetzler, Sarit Kraus +1
This paper presents a novel approach to Explainable AI (XAI) that combines contrastive explanations with differential privacy for clustering algorithms. Focusing on k-median and k-…
ADESSE: Advice Explanations in Complex Repeated Decision-Making Environments
Sören Schleibaum, Lu Feng, Sarit Kraus +1
In the evolving landscape of human-centered AI, fostering a synergistic relationship between humans and AI agents in decision-making processes stands as a paramount challenge. This…
Intelligent Agents for Auction-based Federated Learning: A Survey
Xiaoli Tang, Han Yu, Xiaoxiao Li +1
Auction-based federated learning (AFL) is an important emerging category of FL incentive mechanism design, due to its ability to fairly and efficiently motivate high-quality data o…
The Impact of Snippet Reliability on Misinformation in Online Health Search
Anat Hashavit, Tamar Stern, Hongning Wang +1
Search result snippets are crucial in modern search engines, providing users with a quick overview of a website's content. Snippets help users determine the relevance of a document…