We develop a skew-adaptive extension of split conformal prediction for regression. The method starts from an asymmetric interval family centered at a point prediction and uses the gauge approach to deduce the conformity score induced by this family. The inverse hyperbolic sine transform of signed scaled residuals provides the training target for an additional predictive model, whose role is to learn how predictive uncertainty should tilt across the feature space. The resulting procedure preserves the finite-sample marginal validity of split conformal prediction under exchangeability, while producing intervals that adapt to both local scale and local skewness. We also develop a calibration-sample-based estimator for comparing the expected relative future width of the skew-adaptive and classical scaled-score intervals. Experiments on a variety of datasets indicate gains in prediction interval efficiency over the scaled-score construction and conformalized quantile regression, and show that the proposed estimator closely matches the corresponding average width ratio observed on the test sample.

Flexible continuous-time survival modeling is critical for capturing complex time-varying hazard dynamics in high-dimensional data; however, training such models remains challenging due to the intractable integral required for likelihood estimation. We introduce QSurv, a scalable deep learning framework that enables nonparametric continuous-time modeling without relying on time discretization or restrictive distributional assumptions. We propose a training objective based on Gauss-Legendre numerical quadrature, which approximates the cumulative hazard with high-order accuracy while facilitating efficient end-to-end training via standard backpropagation. Furthermore, to effectively capture non-stationary hazard dynamics in complex architectures, we introduce time-conditioned low-rank adaptation, a mechanism that conditions general neural backbones on time by dynamically modulating weights via low-rank updates. We provide theoretical analysis establishing approximation error bounds for cumulative-hazard evaluation. Comprehensive experiments across synthetic benchmarks, large-scale real-world tabular datasets, and high-dimensional medical imaging tasks demonstrate that QSurv achieves competitive predictive performance with advantages in instantaneous hazard function estimation, enabling more interpretable characterization of time-varying risk patterns.

Differential privacy changes the effective sample size governing CVaR learning. For tail mass $τ$, the privacy-relevant sample size is not $n$, but $nτ$; equivalently, the effective private tail sample size is $εnτ$. Private CVaR excess risk decomposes into ordinary tail-risk statistical error and a privacy price. This decomposition is complete for scalar estimation and finite classes: scalar estimation has rate $Θ(B \min\{1,(nτ)^{-1/2}+(εnτ)^{-1}\})$, and finite classes of size $M$ have rate $Θ(B \min\{1,\sqrt{\log(2M)/(nτ)}+\log(2M)/(εnτ)\})$. These complete rates hold under pure DP, and their lower bounds extend to approximate DP in the stated small-$δ$ regimes. For convex Lipschitz learning, modular upper and lower reductions show that the CVaR-specific privacy term necessarily scales as $1/(εnτ)$, with dimension dependence inherited from private stochastic convex optimization. Together, these results identify ordinary private learning on $Θ(nτ)$ informative tail records as the canonical hard subproblem inside private CVaR learning.

Dependence among marginally constrained observations can break a finite-sample barrier. To formalize this phenomenon, we introduce the \emph{minimum list entropy coupling} $H(P\|Q_1,\dots,Q_m)$, the minimum conditional entropy $H(X|Y_1,\dots,Y_m)$ over all joint distributions with prescribed discrete marginals $X\sim P$ and $Y_i\sim Q_i$. Unlike classical formulations based on independent observations, our model allows $Y_1,\dots,Y_m$ to be arbitrarily dependent while keeping each marginal fixed. This enlarged coupling space reveals a sharp dichotomy: independent observations reduce residual uncertainty exponentially, whereas dependent observations can eliminate it exactly after finitely many samples. We characterize this zero-entropy regime through necessary and sufficient conditions and give concrete structural criteria under which it occurs. In particular, under mild support assumptions, zero entropy is achieved with $O(\log(1/P_{\min}))$ observations, where $P_{\min}$ is the minimum nonzero mass of $P$. We also develop a greedy algorithm with monotone approximation guarantees for computing $H(P\|Q_1,\dots,Q_m)$. Finally, we show that the same framework formalizes finite-sample limits in distribution-matching representation learning and randomness extraction, where zero entropy corresponds to exact recovery and exact extraction.

Many decision in clinical science and epidemiology -- estimating probability of technical success for a clinical trial, assessing comparative effectiveness of two therapies, imputing a placebo effect onto natural history data -- rely on combining sources of information about a clinical cohort that comes from different kinds of studies. Specifically we contrast patient-level sources that provide granular pictures of individual disease course (clinical trial, registries, or electronic health records) with aggregate sources such as published clinical trial results and the TFLs (tables figures and listings). One strategy for combining aggregate with patient-level data sources is to bring each into a common format for a unified analysis. If one wants to maintain the analytic flexibility of patient-level data, then a natural solution is to convert the aggregate data information into a simulated patient-level dataset that recapitulate those aggregate statistics. This is an under-determined inverse problem in that there are many such datasets, and it cannot be well specified without further constraints. FRESH(Fusion of Recent Evidence with Subject Histories) provides a well-defined method for solving this problem, and therefore providing maximal analytic flexibility.

No one wants to hang out with her': Why Meghan and Harry have been ditched by A-list friends as insiders reveal Oprah's merciless snub, why the Clooneys now want nothing to do with them - and how SHE'S the problem Truth about Kate Middleton's past before Prince William... we Americans see this for what it is: KENNEDY I was on track to make $1 million... then I quit my job and moved into an off-grid tiny home with no running water or electricity Professional tasters decide best and worst fast food cheeseburger - do you agree? Hamptons cancer cluster: Rates are spiking in summer enclave of New York's wealthy elite... and doctors think they know the tragic reason why Disturbing trove of images woke Los Angeles mayor Karen Bass doesn't want you to see: Filthy truth is so much worse than people think... Comedian replacing Stephen Colbert appears to take a swipe at his predecessor as he vows to avoid politics and'just be funny' Jordon Hudson blasts double standards over Mike Vrabel and Dianna Russini'affair' scandal: 'What is going on?' I've discovered my'nice' neighbor's dirty secret... what I caught him doing one night was far more disturbing than I realized: DEAR JANE SNL season finale cold open sees ghost of Jeffrey Epstein played by Will Ferrell'haunt' Trump as dark jokes leave viewers shocked Golf star becomes instant fan favorite after stopping to smoke a cigarette with crowd in the middle of the PGA Championship: 'Man of the people' New kind of penis enlargement surgery will add inches, claims the doctor set to offer it... but there is a gruesome detail that may make some think twice I saw a 40-year-old middle-class mom in a psychiatric ward after a single hit of this drug. Her symptoms were terrifying but it's so common now... here's what you must know: DR MAX PEMBERTON US airman returns home to every dog owner's nightmare as he finds his husky DEAD in garage after trusting pet sitter to take care of his beloved companion I'm an exorcist... Here's the chilling encounter that made me believe UFOs are the work of Satan A Catholic priest and exorcist who has encountered demons first-hand has revealed a chilling experience that led him to believe UFOs are actually the work of the devil. Father Carlos Martins, an Ontario-born priest who has performed exorcisms around the world, believes the UFO phenomenon is part of a larger spiritual deception designed to undermine Christianity and cast doubt on the Bible . The priest said a longtime friend who later converted to Christianity once witnessed a gigantic spacecraft hovering silently over a suburban park before it shot away'instantly to the speed of a bullet.'

SNL season finale cold open sees ghost of Jeffrey Epstein played by Will Ferrell'haunt' Trump as dark jokes leave viewers shocked Jordon Hudson blasts double standards over Mike Vrabel and Dianna Russini'affair' scandal: 'What is going on?' No one wants to hang out with her': Why Meghan and Harry have been ditched by A-list friends as insiders reveal Oprah's merciless snub, why the Clooneys now want nothing to do with them - and how SHE'S the problem Truth about Kate Middleton's past before Prince William... we Americans see this for what it is: KENNEDY Kim Kardashian roasted over'ridiculous' outfit at Gucci show as she sits front row with Anna Wintour and Mariah Carey I was on track to make $1 million... then I quit my job and moved into an off-grid tiny home with no running water or electricity Professional tasters decide best and worst fast food cheeseburger - do you agree? Hamptons cancer cluster: Rates are spiking in summer enclave of New York's wealthy elite... and doctors think they know the tragic reason why Disturbing trove of images woke Los Angeles mayor Karen Bass doesn't want you to see: Filthy truth is so much worse than people think... Taylor Swift dazzles in glittering gown as she and Travis Kelce steal the spotlight at friend's wedding in NYC Golf star becomes instant fan favorite after stopping to smoke a cigarette with crowd in the middle of the PGA Championship: 'Man of the people' New kind of penis enlargement surgery will add inches, claims the doctor set to offer it... but there is a gruesome detail that may make some think twice She was every bit the adoring mother... then a leaked video exposed a'sadistic' secret even cops said'will bring tears to your eyes' I saw a 40-year-old middle-class mom in a psychiatric ward after a single hit of this drug. Her symptoms were terrifying but it's so common now... here's what you must know: DR MAX PEMBERTON Expert reveals the best way to cut the bread - and why you should never leave a'hinge' 'I saw things I can never unsee': Man who snuck into Air India crash morgue reveals what he saw... why it could blow apart the pilot suicide theory... and what happened when we visited the lone survivor Scientists are baffled by mysterious blue flashes coming from deep space that are'unlike anything we have observed before' For almost a decade, scientists have been baffled by a series of mysterious blue flashes emerging from deep space. Since the first lit up astronomers' telescopes in 2018, only 14 of these strange pulses have been detected, making them some of the rarest astronomical events on record. Known as Luminous Fast Blue Optical Transients (LFBOTs), these lights burn faster and up to 100 times brighter than anything else scientists have seen .

SNL season finale cold open sees ghost of Jeffrey Epstein played by Will Ferrell'haunt' Trump as dark jokes leave viewers shocked Jordon Hudson blasts double standards over Mike Vrabel and Dianna Russini'affair' scandal: 'What is going on?' No one wants to hang out with her': Why Meghan and Harry have been ditched by A-list friends as insiders reveal Oprah's merciless snub, why the Clooneys now want nothing to do with them - and how SHE'S the problem Truth about Kate Middleton's past before Prince William... we Americans see this for what it is: KENNEDY Kim Kardashian roasted over'ridiculous' outfit at Gucci show as she sits front row with Anna Wintour and Mariah Carey I was on track to make $1 million... then I quit my job and moved into an off-grid tiny home with no running water or electricity Professional tasters decide best and worst fast food cheeseburger - do you agree? Hamptons cancer cluster: Rates are spiking in summer enclave of New York's wealthy elite... and doctors think they know the tragic reason why Disturbing trove of images woke Los Angeles mayor Karen Bass doesn't want you to see: Filthy truth is so much worse than people think... Taylor Swift dazzles in glittering gown as she and Travis Kelce steal the spotlight at friend's wedding in NYC Golf star becomes instant fan favorite after stopping to smoke a cigarette with crowd in the middle of the PGA Championship: 'Man of the people' New kind of penis enlargement surgery will add inches, claims the doctor set to offer it... but there is a gruesome detail that may make some think twice She was every bit the adoring mother... then a leaked video exposed a'sadistic' secret even cops said'will bring tears to your eyes' I saw a 40-year-old middle-class mom in a psychiatric ward after a single hit of this drug. Her symptoms were terrifying but it's so common now... here's what you must know: DR MAX PEMBERTON Expert reveals the best way to cut the bread - and why you should never leave a'hinge' 'I saw things I can never unsee': Man who snuck into Air India crash morgue reveals what he saw... why it could blow apart the pilot suicide theory... and what happened when we visited the lone survivor Many people have reported near-death experiences, but in some cases, survivors appeared to bring back something far more unsettling than memories. Some survivors claimed they saw and heard things that should have been impossible while they were clinically dead, including conversations in operating rooms and objects located far outside their hospital beds. Several of the most famous cases involved patients whose brains allegedly showed little or no measurable activity at the time of their experiences.

OpenAI has signed deals with fintech startups, tech giants and even Disney, but it's breaking new ground by announcing a world's first partnership with the country of Malta. In a post on its website, OpenAI said that it would provide ChatGPT Plus for one year to every Maltese resident or citizen. Malta is the first country to launch a partnership of this scale because we refuse to let our citizens stay behind in the digital age, Silvio Schembri, Malta's minister for Economy, Enterprise and Strategic Projects, said in a statement. We are putting our people at the very forefront of global change. For the approximately 574,250 residents living in Malta, they'll have to complete a course developed by the University of Malta before launching the ChatGPT Plus subscription, which costs $20 a month in the US.

Inside the cowboy city where Big Tech threatens to steamroll their way of life... as lawmakers begged billionaires to keep building in secret summit talks As dozens of potential rat virus cases are monitored, lessons can be learned from forgotten outbreak that ravaged an American icon... and left a trail of death in its wake California town's woke policy stands in the way of major Costco expansion Top scientist admits universe is'teeming with life'... and reveals what first contact will look like amid Trump's UFO disclosure Cheerful Christian mom is pillar of Florida community and loves going on TV... but she has a childhood secret so evil that she stuttered with shock when confronted with it New York Mets pitcher Clay Holmes' leg is broken by 111mph liner with team set to lose star man for'a long time' Why New York's rich are ditching the Hamptons for this hideaway with affordable mansions and no traffic Michael Jackson's life has been turned into a box office smash - but one ...