It suggests that, for any m { k,...,n 1 } and z R, L A.2 Proofs for Lemma 2 and 3 for the case when K is unknown in 4 Lemma 2 . It suggests that, for any m { 0,...,n 1 } and z R, L For any m { 0,...,n 1 } and z R, we have L A.3 Additional tricks for methods proposed in 3. Finding optimal CP vector when z = in paraCP(n,k, ˆ T Additional pruning condition for parametric DP when K is fixed. In 3.3, we showed that Lemma 4. F orn [ N ], and k [ K ], let T Therefore, it fails to control the false positive rate. This is asymptotic test for multiple detected CPs. Fused Lasso (proposed by the same authors), is worse than BinSeg-SI. BinSeg-SI had been considered as a computationally efficient approximation of the problem in (7), where the authors additionally condition on extra information for computational tractability, e.g., the order that CPs are detected.

How would you go about checking if this proof is correct? One cumbersome way would be to directly refute the proof's claim, e.g., to demonstrate that actually

This article was featured in the One Story to Read Today newsletter. Last year, Ford CEO Jim Farley commuted in a car that wasn't made by his own company. In an effort to scope out the competition, Farley spent six months driving around in a Xiaomi SU7. The Chinese-made electric sedan is one of the world's most impressive cars: It can accelerate faster than many Porsches, has a giant touch screen that lets you turn off the lights at your house, and comes with a built-in AI assistant--all for roughly 30,000 in China. "It's fantastic," Farley said about the Xiaomi SU7 on a podcast last fall.

The original questions are in bold . The subtext to each question is in italics. The answers are in plain text with no formatting. The questions in this section are primarily intended to encourage dataset creators to clearly articulate their reasons for creating the dataset and to promote transparency about funding interests. For what purpose was the dataset created? Was there a specific task in mind? Was there a specific gap that needed to be filled? The Dollar Street dataset is a supervised image dataset derived from Gapminder's Dollar Street project ( https://www.gapminder.org/dollar-street) that contains everyday household items from homes around the world. It was created with three goals in mind: 1. Make available a highly curated set of images with valuable metadata (e.g. Our evaluation results show that the Dollar Street dataset can add significant value to accuracy improvements when considering computer vision images that represent the geographic and socioeconomic diversity of the world. Concretely, this means that the dataset only contains CC-BY-licensed works.

This dataset includes images from homes with no internet access and incomes as low as $26.99 per

Long-term forecasting refers to making predictions based on the history for a long horizon in the future, as opposed to short-term forecasting. Long-term time series forecasting has many key applications in energy, weather, economics, transportation, and so on.