Victor Wembanyama's historic game one performance was personal, Spurs star reveals in postgame interview Dana White says gnats at Trump's White House Rose Garden dinner raised concerns for outdoor UFC events High school athlete slams CIF's shared podium rule as humiliating response that fails female competitors Kuwaiti Muslim jiu-jitsu champion refuses Israeli athlete's handshake: 'We do not respect them at all' Caitlin Clark's fiery Fever teammate tells WNBA haters to relax with perfect three-word response Red Sox legend Jason Varitek's wife appears to take massive swipe at team after ugly ouster Reds vs. Phillies betting preview: Why Cincinnati is the play despite their 4-12 skid over 16 games Bubba Wallace'seeing red' after being wrecked, female driver rage-quits and cries & NASCAR missed the mark Taiwan warns US about China's regional ambitions as Trump weighs arms deal Nate Bargatze takes clean comedy to big screen with'The Breadwinner' Retired vice admiral on Iran standoff: Trump has'time on his hands' Jury dismisses Elon Musk's lawsuit against OpenAI and Sam Altman Strikes must resume if Iran fails to negotiate'in good faith': Brig Gen John Teichert Trace Gallagher: What does liberal America want? 'Rededicate 250' faith event draws thousands to DC OutKick contributor Riley Gaines discusses female high school athletes speaking out after a transgender participant won multiple events at a California track meet on'Fox & Friends.' MOORPARK, Calif. - On the morning of a day that would live in girls' sports infamy, a letter was handed out to coaches who entered a championship track and field meet at Moorpark High School. The letter announced that any girl who finished behind a biological male trans athlete would be bumped up by one spot on the podium, if that girl finished behind the trans athlete. The letter was dated May 16 -- the day of the event. The California Interscholastic Federation (CIF) will implement the pilot entry process introduced last season at the 2025 CIF Track and Field State Championships.

These target videos may vary widely in complexity of scenes, activities, camera trajectory, etc.

Here,weproposea spatio-translational embeddingmodel,called BoxE,that simultaneously addresses all these limitations.

Least absolute shrinkage and selection operator (Lasso), a popular method for high-dimensional regression, is now used widely for estimating high-dimensional time series models such as the vector autoregression (VAR). Selecting its tuning parameter efficiently and accurately remains a challenge, despite the abundance of available methods for doing so. We propose $\mathsf{autotune}$, a strategy for Lasso to automatically tune itself by optimizing a penalized Gaussian log-likelihood alternately over regression coefficients and noise standard deviation. Using extensive simulation experiments on regression and VAR models, we show that $\mathsf{autotune}$ is faster, and provides better generalization and model selection than established alternatives in low signal-to-noise regimes. In the process, $\mathsf{autotune}$ provides a new estimator of noise standard deviation that can be used for high-dimensional inference, and a new visual diagnostic procedure for checking the sparsity assumption on regression coefficients. Finally, we demonstrate the utility of $\mathsf{autotune}$ on a real-world financial data set. An R package based on C++ is also made publicly available on Github.

Topology identification and inference of processes evolving over graphs arise in timely applications involving brain, transportation, financial, power, as well as social and information networks. This chapter provides an overview of graph topology identification and statistical inference methods for multidimensional relational data. Approaches for undirected links connecting graph nodes are outlined, going all the way from correlation metrics to covariance selection, and revealing ties with smooth signal priors. To account for directional (possibly causal) relations among nodal variables and address the limitations of linear time-invariant models in handling dynamic as well as nonlinear dependencies, a principled framework is surveyed to capture these complexities through judiciously selected kernels from a prescribed dictionary. Generalizations are also described via structural equations and vector autoregressions that can exploit attributes such as low rank, sparsity, acyclicity, and smoothness to model dynamic processes over possibly time-evolving topologies. It is argued that this approach supports both batch and online learning algorithms with convergence rate guarantees, is amenable to tensor (that is, multi-way array) formulations as well as decompositions that are well-suited for multidimensional network data, and can seamlessly leverage high-order statistical information.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Chance of more showers in L.A., with a new storm set to hit Thursday A driver navigates a flooded street during a storm Monday in Santa Barbara. This is read by an automated voice. Please report any issues or inconsistencies here . Showers could linger in Los Angeles on Tuesday following four straight days of rain -- and even more rain is likely on Thursday and Friday.