As chaotic negotiations over the end of the Iran war continue, US negotiators think they have the framework for a deal in place. Now they just have to sell the president on it. President Donald Trump's negotiators face the arduous task of trying to convince the president that a deal he previously rejected is their best option in Iran . Last month, Trump initially gave his blessing for a so-called "cash for uranium" deal, under which the US would release around $20 billion in frozen funds in exchange for Iran handing over its stockpile of highly enriched uranium, sources familiar with the matter tell WIRED. Trump's negotiators, vice president JD Vance, special envoy Steve Witkoff, and Jared Kushner, Trump's son-in-law, received repeated approvals from the president while they were in Islamabad, giving them confidence a deal was close.

Guido Reichstadter, a 45-year-old anti-war protester, was arrested after camping atop one of D.C.'s tallest bridges for nearly a week to protest the war with Iran and AI.

Russia ignores Ukraine's unilateral ceasefire and attacks kindergarten Volodymyr Zelensky has accused Russia of breaching a unilateral ceasefire announced by Ukraine by launching a wave of drone attacks on several cities. The Ukrainian president said Russia had carried out active hostilities and terrorist shelling, targeting the front line as well as firing dozens of drones and missiles at civilian areas. In the Sumy border region, one woman was killed when a kindergarten was hit on Wednesday morning, local authorities said. No children were present at the time. Earlier this week the two warring sides had announced rival unilateral ceasefires - with no agreement on their terms, length or monitoring.

Now, Activists Are Taking On Elon Musk's SpaceX IPO Activists, a leading labor union, and a big retirement fund are asking challenging questions about what's expected to be the largest-ever stock market debut. Elon Musk's SpaceX is facing protests against its expected initial public offering from some of the same advocacy groups that helped erase $600 billion from Tesla's market cap early last year. SpaceX's IPO is poised to be the largest ever, raising tens of billions of dollars for the Musk-founded company and valuing it above $2 trillion. If all goes as intended come June, the conglomerate that now owns a rocket manufacturer, a social media app, and an AI chatbot developer will instantly rank among the world's top 10 largest publicly-traded companies. On Wednesday, Randi Weingarten, president of the American Federation of Teachers, wrote to the US Securities and Exchange Commission urging it to scrutinize SpaceX's IPO preparations.

To stay or risk the'Road of Death' - Ukrainian civilians trapped in frontline city So, we're stuck here, says Ludmilla, over the phone from the rooftop of a fire-damaged house in southern Ukraine. People are trying their best to survive. Her frontline home city of Oleshky has, according to multiple accounts, been largely cut off from fresh supplies of food or medicine for months. Ludmilla describes being trapped there, and watching it decaying before her eyes. Ukraine's commissioner for human rights has warned of a humanitarian crisis.

We introduce a general framework that extends Bayesian inference by allowing the researcher to explicitly encode confidence in each source of uncertainty within the model. This mechanism provides a new handle for model design and regularisation control. Building on this framework, we develop a general approach for inducing sparsity in statistical models and illustrate its use in linear and logistic regression, as well as in Bayesian neural networks.

We develop graph-based methods for semi-supervised learning based on label propagation on a data similarity graph. When data is abundant or arrive in a stream, the problems of computation and data storage arise for any graph-based method. We propose a fast approximate online algorithm that solves for the harmonic solution on an approximate graph. We show, both empirically and theoretically, that good behavior can be achieved by collapsing nearby points into a set of local representative points that minimize distortion. Moreover, we regularize the harmonic solution to achieve better stability properties. We also present graph-based methods for detecting conditional anomalies and apply them to the identification of unusual clinical actions in hospitals. Our hypothesis is that patient-management actions that are unusual with respect to the past patients may be due to errors and that it is worthwhile to raise an alert if such a condition is encountered. Conditional anomaly detection extends standard unconditional anomaly framework but also faces new problems known as fringe and isolated points. We devise novel nonparametric graph-based methods to tackle these problems. Our methods rely on graph connectivity analysis and soft harmonic solution. Finally, we conduct an extensive human evaluation study of our conditional anomaly methods by 15 experts in critical care.

Urban air quality forecasting is challenging because pollutant concentrations are nonlinear, nonstationary, spatiotemporally dependent, and often affected by anomalous observations caused by traffic congestion, industrial emissions, and seasonal meteorological variability. This study proposes a Graph Convolutional Support Vector Regression (GCSVR) framework for robust spatiotemporal forecasting of urban air pollution. The model combines graph convolutional learning to capture inter-station spatial dependence with support vector regression to model nonlinear temporal dynamics while reducing sensitivity to outlier observations. The proposed framework is evaluated using air quality records from 37 monitoring stations in Delhi and 18 stations in Mumbai, representing inland and coastal metropolitan environments in India. Forecasting performance is assessed across multiple horizons and compared with established temporal and spatiotemporal benchmarks. The results show that GCSVR consistently improves predictive accuracy and maintains stable performance across seasons and outlier-prone pollution episodes. Statistical test further confirms the reliability of the proposed approach across the two cities. Finally, conformal prediction is integrated with GCSVR to generate calibrated prediction intervals, enhancing its practical value for uncertainty-aware air quality monitoring and public health decision-making.

A top Google scientist warned EU antitrust regulators that its proposal requiring the company to share search engine data with rivals risked exposing users' private information. BRUSSELS - A top Google scientist sent a warning to EU antitrust regulators on Tuesday that its proposal requiring the company to share search engine data with rivals such as OpenAI risked exposing users' private information, the sternest rebuke yet in a tussle over Google's lucrative business model. The European Commission, which acts as the EU competition enforcer, has in recent years cracked down on Big Tech via a slew of legislation to ensure that users have more choices and that smaller rivals have room to compete. However, that has triggered the ire of the U.S. government. Sergei Vassilvitskii, with the title of distinguished scientist at Google since 2012 and regarded a leader in his field, will meet EU antitrust officials on Wednesday to voice his concerns and propose a broader approach with better guardrails.

Ukraine strikes multiple sites in Moscow, following Russia's strikes on a Ukrainian gas production facility that killed at least 5 people. This escalation comes after each side announced a ceasefire - but for different days. West Bengal Chief refuses to resign after'dirty' election Hegseth says US'hasn't capitulated on anything' regarding Iran Smotrich says he promised his son'more destruction' in Lebanon Hegseth says US blockade on Iran'gift to the world'