The join operation, which combines tuples from multiple relations, is the most fundamental
and, typically, the most expensive operation in database queries. The standard approach to …

… Second, it is also possible that the civilian beneficiaries of humanitarian intervention can
permissibly be made to share some of the risks with the combatants who intervene on their …

… public opinion about the ethics of war, Scott Sagan and Benjamin Valentino report three …
Equality of Combatants,” Scott Sagan and Benjamin Valentino have revealed a wealth of informa…

We demonstrate that it is possible to train large recurrent language models with user-level
differential privacy guarantees with only a negligible cost in predictive accuracy. Our work …

In this paper, we consider the multi-level aggregation problem with deadlines (MLAPD)
previously studied by Bienkowski et al. (2015), Buchbinder et al. (2017), and Azar and Touitou (…

… While federated learning offers many practical privacy benefits, providing stronger guarantees
via differential privacy [14, 13, 1], secure multi-party computation [18], or their combination …

… with our sense that it is appropriate for certain minority groups to take pride in their distinctness
and to maintain certain discriminatory practices that preserve their distinctness and ben…

cDNA clones corresponding to an Mr approximately 80,000 receptor (type I receptor) for
interleukin‐1 (IL‐1) have been isolated previously by mammalian expression. Here, we report …

… Peter McMahan is an assistant professor of sociology at McGill University. He completed
his PhD at the University of Chicago. His work takes a relational approach to questions of …

Differential privacy (DP) and federated learning (FL) are combined as advanced privacy-preserving
methods when training on-device language models in production mobile keyboard …