Carney matches Trump tariffs with 50% tax on U.S. dairy, steel Canadian Finance Minister Francois-Philippe Champagne (C) speaks during a news conference in Ottawa, Ontario, Canada, on Tuesday. Prime Minister Mark Carney matched dollar-for-dollar the new tariffs imposed by President Donald Trump over the weekend and announced support programs for Canadian businesses hurt by the escalating trade war. Prime Minister Mark Carney matched the new tariffs imposed by President Donald Trump and announced new support programs for Canadian businesses hurt by the escalating trade war with the country's largest trading partner. Canada will double its existing counter-tariffs on U.S. steel and aluminum products to 50%. American-made milk, furniture, clothing and apparel will also have new 50% duties applied, as will video-game consoles, smartphones and other electronics. Overall, the retaliatory levies will affect $20 billion worth of annual U.S. exports to Canada, roughly matching the dollar-value impact of the tariffs the White House put on Canadian products on Saturday.

Learning causal relations from observational data is a fundamental problem with wide-ranging applications across many fields. Constraint-based methods infer the underlying causal structure by performing conditional independence tests. However, existing algorithms such as the prominent PC algorithm need to perform a large number of independence tests, which in the worst case is exponential in the maximum degree of the causal graph. Despite extensive research, it remains unclear if there exist algorithms with better complexity without additional assumptions. Here, we establish an algorithm that achieves a better complexity of $p^{\mathcal{O}(s)}$ tests, where $p$ is the number of nodes in the graph and $s$ denotes the maximum undirected clique size of the underlying essential graph. Complementing this result, we prove that any constraint-based algorithm must perform at least $2^{Ω(s)}$ conditional independence tests, establishing that our proposed algorithm achieves exponent-optimality up to a logarithmic factor in terms of the number of conditional independence tests needed. Finally, we validate our theoretical findings through simulations, on semi-synthetic gene-expression data, and real-world data, demonstrating the efficiency of our algorithm compared to existing methods in terms of number of conditional independence tests needed.

Horrifying next twist in the Alexander brothers case: MAUREEN CALLAHAN exposes an unthinkable perversion that's been hiding in plain sight Hollywood icon who starred in Psycho after Hitchcock dubbed her'my new Grace Kelly' looks incredible at 95 Alexander brothers' alleged HIGH SCHOOL gang rape video: Classmates speak out on sick'taking turns' footage... as creepy unseen photos are exposed Model Cindy Crawford, 60, mocked for her'out of touch' morning routine: 'Nothing about this is normal' Kentucky mother and daughter turn down $26.5MILLION to sell their farms to secretive tech giant that wants to build data center there Tucker Carlson erupts at Trump adviser as she hurls'SLANDER' claim linking him to synagogue shooting NFL superstar Xavier Worthy spills all on Travis Kelce, the Chiefs' struggles... and having Taylor Swift as his No 1 fan Heartbreaking video shows very elderly DoorDash driver shuffle down customer's driveway with coffee order because he is too poor to retire Amber Valletta, 52, was a '90s Vogue model who made movies with Sandra Bullock and Kate Hudson, see her now Nancy Mace throws herself into Iran warzone as she goes rogue on Middle East rescue mission: 'I AM that person' It might sound like a gardener's worst nightmare - but'very hungry caterpillars' should be left to feast on plants this spring, conservationists say. Experts are warning that moths, which caterpillars grow into, have seen their numbers plummet by a third since the 1960s. The insects, which are vital pollinators, are struggling with climate change, pollution and an increasingly built-up Britain. Now, the Royal Horticultural Society (RHS) and The Wildlife Trusts are urging green-fingered households to put up with plants being nibbled by caterpillars in order to boost numbers. They explained that caterpillars need plenty of energy to get plump, ready for transformation into a moth.

In the visual spatial understanding (VSU) area, spatial image-to-text (SI2T) and spatial text-to-image (ST2I) are two fundamental tasks that appear in dual form. Existing methods for standalone SI2T or ST2I perform imperfectly in spatial understanding, due to the difficulty of 3D-wise spatial feature modeling.

Pruning methods for neural networks [LeCun et al., 1989] replace dense weight matrices by sparse

To address this issue, we propose to evict tensors within a sliding window to ensure all evictions are contiguous and are immediately used.