If you were watching the downhill skiing or luge at Milan-Cortina 2026 over the weekend, you will have noticed the dramatic new camera angles being provided at these Games. Drones have been used in Olympic coverage since 2014, but they have been much more prevalent at these Winter Games. Carrying cameras, the drones have been flown close behind athletes as they ski or slide, capturing dramatic footage which has never been seen at a Games before. But they have proved divisive for audiences, with social media split between admiring the footage or being put off by the noise. The whirring of the drone blades is audible in the live coverage.

The variance was computed empirically overk = 100 normally distributed samplesw. As can be seen, the variance of the kernel tends to zero only when both widths increase. The hyperkernel used corresponds to the infinite width limit ofthesame architecture. As can be seen in Figure 1, whenf is wide and kept fixed, there is a clear improvement in test performance as the width ofg increases, for every learning rate in which the networks provide non-trivial performance. Whenf is wide and kept fixed, a deeperg incurs slower training and lower overall test performance.

Moreover, our methods aretheoretically guaranteed toconvergetothePareto front.

We examine an adaptive learning framework for nonatomic congestion games where the players' cost functions may be subject to exogenous fluctuations (e.g., due to disturbances in the network, variations in the traffic going through a link, etc.).