New Russini-Vrabel photos raise ESPN conflict questions but the network won't answer them ESPN's Mad Dog Russo melts down over'U-S-A' chants at the RBC Heritage A piece of the UFC White House event's setup is sitting in Pennsylvania Amish country Viral Ottawa Senators fan blamed for team's 0-2 playoff start banished to Taiwan'First Take' host acts disgusted when she has to cover Vrabel-Russini drama Edward Cabrera's strikeout prop is the play as struggling Phillies face surging Cubs today Nuggets vs Timberwolves Game 3 pick hinges on Jaden McDaniels calling out Denver's entire defense Charles Barkley was disgusted by Magic's highly questionable pregame handshake ChatGPT predicted the first round of the NFL Draft and here's what it said Trump: Why would I use a nuclear weapon? California governor's race intensifies as six candidates face off Trump: US Navy to'shoot and kill' any boat placing mines in Hormuz Virginia court blocks Democrats' redistricting effort, Florida next Trump weighs in on Iran's internal power struggle and Strait of Hormuz control Hasan Piker justifies'social murder' of CEO Restaurant owner says hockey win was'beautiful sight,' defends patriotic response to media slam John Minadakis, the owner of Jimmy's Famous Seafood in Baltimore, tells Fox News Digital why he felt a need to defend USA pride after an Olympic article slam. As we have discussed several times recently, the Stanley Cup Playoffs are home to some of the most superstitious human beings on the planet. Several of the most famous traditions in the sport stem from fans and players alike doing something born out of superstition. Take the Detroit Red Wings and their octopus toss, whose eight legs symbolize the eight wins it took to win a Stanley Cup back when the league was much smaller.

The present study aims to investigate a cluster cleaning algorithm that is both computationally simple and capable of solving the PU classification when the SCAR condition is unsatisfied. A secondary objective of this study is to determine the robustness of the LassoJoint method to perturbations of the SCAR condition. In the first step of our algorithm, we obtain cleaning labels from 2-means clustering. Subsequently, we perform logistic regression on the cleaned data, assigning positive labels from the cleaning algorithm with additional true positive observations. The remaining observations are assigned the negative label. The proposed algorithm is evaluated by comparing 11 real data sets from machine learning repositories and a synthetic set. The findings obtained from this study demonstrate the efficacy of the clustering algorithm in scenarios where the SCAR condition is violated and further underscore the moderate robustness of the LassoJoint algorithm in this context.

Bayesian neural network (BNN) posteriors are often considered impractical for inference, as symmetries fragment them, non-identifiabilities inflate dimensionality, and weight-space priors are seen as meaningless. In this work, we study how overparametrization and priors together reshape BNN posteriors and derive implications allowing us to better understand their interplay. We show that redundancy introduces three key phenomena that fundamentally reshape the posterior geometry: balancedness, weight reallocation on equal-probability manifolds, and prior conformity. We validate our findings through extensive experiments with posterior sampling budgets that far exceed those of earlier works, and demonstrate how overparametrization induces structured, prior-aligned weight posterior distributions.

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Label noise - incorrect labels assigned to observations - can substantially degrade the performance of supervised classifiers. This paper proposes a label noise cleaning method based on Bernoulli random sampling. We show that the mean label noise levels of subsets generated by Bernoulli random sampling containing a given observation are identically distributed for all clean observations, and identically distributed, with a different distribution, for all noisy observations. Although the mean label noise levels are not independent across observations, by introducing an independent coupling we further prove that they converge to a mixture of two well-separated distributions corresponding to clean and noisy observations. By establishing a linear model between cross-validated classification errors and label noise levels, we are able to approximate this mixture distribution and thereby separate clean and noisy observations without any prior label information. The proposed method is classifier-agnostic, theoretically justified, and demonstrates strong performance on both simulated and real datasets.

Kentucky mother and daughter turn down $26.5MILLION to sell their farms to secretive tech giant that wants to build data center there 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 Kylie Jenner's total humiliation in Hollywood: Derogatory rumor leaves her boyfriend's peers'laughing at her' behind her back Tucker Carlson erupts at Trump adviser as she hurls'SLANDER' claim linking him to synagogue shooting Ben Affleck'scores $600m deal' with Netflix to sell his AI film start-up Long hair over 45 is ageing and try-hard. I've finally cut mine off. Alexander brothers' alleged HIGH SCHOOL rape video: Classmates speak out on sickening footage... as creepy unseen photos are exposed 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 Model Cindy Crawford, 60, mocked for her'out of touch' morning routine: 'Nothing about this is normal' Antarctica has lost an area of ice more than eight times larger than Greater London over the last 30 years, a study has revealed. Using satellite data collected over the last three decades, scientists have painstakingly mapped the frozen continent's shrinking borders. The researchers measured the'grounding line migration' - the change in location at which the continental ice shelf meets the open ocean.

Algorithmic decisions about individuals require predictions that are not only accurate but also fair with respect to sensitive attributes such as gender and race. Causal notions of fairness align with legal requirements, yet many methods assume access to detailed knowledge of the underlying causal graph, which is a demanding assumption in practice. We propose a learning framework that achieves interventional fairness by leveraging a causal graph over \textit{clusters of variables}, which is substantially easier to estimate than a variable-level graph. With possible \textit{adjustment cluster sets} identified from such a cluster causal graph, our framework trains a prediction model by reducing the worst-case discrepancy between interventional distributions across these sets. To this end, we develop a computationally efficient barycenter kernel maximum mean discrepancy (MMD) that scales favorably with the number of sensitive attribute values. Extensive experiments show that our framework strikes a better balance between fairness and accuracy than existing approaches, highlighting its effectiveness under limited causal graph knowledge.

In this paper, we study last-iterate convergence of learning algorithms in bilinear saddle-point problems, a preferable notion of convergence that captures the day-to-day behavior of learning dynamics. We focus on the challenging setting where players select actions from compact convex sets and receive only bandit feedback. Our main contribution is the design of an uncoupled learning algorithm that guarantees last-iterate convergence to the Nash equilibrium with high probability. We establish a convergence rate of $\tilde{O}(T^{-1/4})$ up to polynomial factors in problem parameters. Crucially, our proposed algorithm is computationally efficient, requiring only an efficient linear optimization oracle over the players' compact action sets. The algorithm is obtained by combining techniques from experimental design and the classic Follow-The-Regularized-Leader (FTRL) framework, with a carefully chosen regularizer function tailored to the geometry of the action set of each learner.

Bed-bound Lindsey Vonn reveals pain is'hard to manage' as she speaks out for the first time after FIFTH surgery on her broken leg'Fergie might end up having to tell her story to the police': 'Toxic' Sarah Ferguson is'broke and in a bad way' after Andrew's arrest...and looking to UAE for cash because'everyone is out to get her' The tide of sleaze rolling over Beatrice, Eugenie and Fergie is going to capsize them all. Moment Kate and William revealed their'true feelings' towards Andrew and Fergie: Princess'ignoring' Sarah and Prince'secretly scolding' his uncle... how Duchess of Kent's funeral said it all Kurt Cobain's uncle insists Nirvana legend was murdered and calls on cops to investigate clues that haunt him Kristi Noem's secret escape plan to ditch DHS revealed amid ICE raid fallout and'culture of fear' rumors Winter Olympics chiefs reach verdict on Jutta Leerdam's '$1m underwear-flashing gesture' after Jake Paul's fiancée faced covert marketing claims Country singer Conner Smith's charges DROPPED after he hit and killed a woman, 77, with his truck I ditched weight-loss shots for the new Wegovy pill and am astonished by the difference. The pounds are falling off, I have no side effects and it's cheaper The subtle early warning sign that revealed Eric Dane's illness - as Grey's Anatomy star dies of motor neurone disease Johnny Depp let Eric Dane live'rent-free in one of his LA homes' as he tried to ease Grey's Anatomy star's financial worries in the months before his death from ALS aged 53 Uproar as NYC's'communist' mayor announces crippling tax for ALL homeowners after promising to only go after billionaires Wall Street panics as America's growth stalls while everyday prices refuse to fall I stumbled across my wife's Pornhub search history and it's broken me. She told me it's'just a fantasy lots of women have' but now I fear I'll never be enough Non-binary activist wins compensation after taking year-and-a-half off work with stress because hair salon's online booking form only offered male or female cuts Courtney Love caught on camera fleeing shocking car collision... days after bombshell Kurt Cobain'homicide investigation' Trump-bashing Winter Olympics star Hunter Hess whines about'hardest weeks of his life' after being called a'real loser' by the president In a viral post on X, user @ShishirShelke1 shared their strange discovery about the clock app icon. Normally, the icon on the home screen shows the second hand smoothly gliding around the clock face.

Eric Dane dead at 53: Grey's Anatomy star dies after courageous battle with ALS... less than a year after announcing diagnosis RICHARD KAY: Andrew's fall may now be complete. The question is... Will he bring down the House of Windsor with him? Alysa Liu finally ends America's 24-year wait for a Winter Olympics figure skating gold medal as she wins nerve-shredding final The tide of sleaze rolling over Beatrice, Eugenie and Fergie is going to capsize them all. My stalker said he'd rape and dismember me. Then he turned his depraved sights on my seven-year-old daughter, says EVA LARUE.