A 2023 law championed by Republicans requires the CDC have a director confirmed by the Senate. For months, though, it's had only acting directors--and the White House won't say when that will change. As the agency rotates through a cast of leaders, it's unclear when--or if--the US Centers for Disease Control and Prevention will get a permanent director under Donald Trump's second term as president. Following Jim O'Neill's departure as acting CDC director last week, National Institutes of Health director Jay Bhattacharya will now lead both agencies temporarily. It's the latest in a series of shakeups at Trump's CDC, which has lost about a quarter of its staff to mass layoffs carried out by Health and Human Services Secretary Robert F. Kennedy, Jr. last year.

While there has been much attention on the theoretical aspect of the traditional i.i.d.

Stochastic gradient descent (SGD) algorithm is the method of choice in many machine learning tasks thanks to its scalability and efficiency in dealing with large-scale problems. In this paper, we focus on the shuffling version of SGD which matches the mainstream practical heuristics. We show the convergence to a global solution of shuffling SGD for a class of non-convex functions under over-parameterized settings.

Rather than specifying a model, the GP framework revolves around selecting an appropriate kernel, transforming the problem into one of parameter estimation.