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To address this problem, existing methods partition the overall DPDP into fixed-size sub-problems by caching online generated orders and solve each sub-problem, or on this basis to utilize the predicted future orders to optimize each sub-problem further. However, the solution quality and efficiency of these methods are unsatisfactory, especially when the problem scale is very large.

Tesla avoids California sales ban by removing'autopilot' from marketing Tesla will avoid a 30-day suspension of its dealer and manufacturer licenses in California, its biggest market, after the US electric vehicle maker stopped using the term "autopilot" in the marketing of its vehicles in the state. Tesla now uses the term "supervised" in references to its full self-driving technology and has stopped using "autopilot" entirely in its marketing in the state. State regulators said Tuesday that Tesla had stopped misleading drivers about the safety of its cars, and so the state will not suspend its state sales license for 30 days, as had been threatened. The decision by the California department of motor vehicles comes after CEO Elon Musk's electric vehicle company was found by an administrative law judge last year to have misled drivers about the ability of Tesla cars to drive themselves in its use of the terms "autopilot" and "full self-driving". In 2022, the DMV had accused Tesla of misleading consumers by using "autopilot" and "full self-driving" for its advanced driver-assistance features.

This paper presents an auditing procedure for the Differentially Private Stochastic Gradient Descent (DP-SGD) algorithm in the black-box threat model that is substantially tighter than prior work.