Despite their promise, fair machine learning methods often yield Pareto-inefficient models, in which the performance of certain groups can be improved without degrading that of others. This issue arises frequently in traditional in-processing approaches such as fairness-through-regularization. In contrast, existing Pareto-efficient approaches are biased towards a certain perspective on fairness and fail to adapt to the broad range of fairness metrics studied in the literature. In this paper, we present BADR, a simple framework to recover the optimal Pareto-efficient model for any fairness metric. Our framework recovers its models through a Bilevel Adaptive Rescalarisation procedure. The lower level is a weighted empirical risk minimization task where the weights are a convex combination of the groups, while the upper level optimizes the chosen fairness objective. We equip our framework with two novel large-scale, single-loop algorithms, BADR-GD and BADR-SGD, and establish their convergence guarantees. We release badr, an open-source Python toolbox implementing our framework for a variety of learning tasks and fairness metrics. Finally, we conduct extensive numerical experiments demonstrating the advantages of BADR over existing Pareto-efficient approaches to fairness.

Conformal Test Martingales (CTMs) are a standard method within the Conformal Prediction framework for testing the crucial assumption of data exchangeability by monitoring deviations from uniformity in the p-value sequence. Although exchangeability implies uniform p-values, the converse does not hold. This raises the question of whether a significant break in exchangeability can occur, such that the p-values remain uniform, rendering CTMs blind. We answer this affirmatively, demonstrating the phenomenon of \emph{conformal blindness}. Through explicit construction, for the theoretically ideal ``predictive oracle'' conformity measure (given by the true conditional density), we demonstrate the possibility of an \emph{$A$-cryptic change-point} (where $A$ refers to the conformity measure). Using bivariate Gaussian distributions, we identify a line along which a change in the marginal means does not alter the distribution of the conformity scores, thereby producing perfectly uniform p-values. Simulations confirm that even a massive distribution shift can be perfectly cryptic to the CTM, highlighting a fundamental limitation and emphasising the critical role of the alignment of the conformity measure with potential shifts. By contrasting the predictive oracle with recent results on detection-optimal scores, we emphasise that validity monitoring in safety-critical systems requires careful separation of predictive and diagnostic goals.

Oklahoma teenager William Spencer charged with first-degree murder after allegedly stabbing his brother Nicholas Spencer to death during a video game dispute in Oklahoma City on Sunday.

Breakthroughs, discoveries, and DIY tips sent six days a week. Kangaroos have likely been hopping across the planet for much longer than experts previously believed. Not only that, but the ancestors of today's marsupials landed their leaps while growing larger than their descendents. For thousands of years, the planet's largest hopping animal has remained Australia's red kangaroo (). A male "Big Red" easily reaches over five feet tall, weighs 200 pounds, and travels around 37 mph at a pace of up to six feet per leap.

Why is the US Fed chair criminal probe causing alarm? Inside Story Is the world's rules-based order ruptured? Canadian Prime Minister Mark Carney says system is broken, with world powers employing force. The world's rules-based order is ruptured, Canadian Prime Minister Mark Carney has said, in a speech at the World Economic Forum in Davos, Switzerland that avoided mentioning United States President Donald Trump. While Trump hit back at Carney, the Canadian leader's words have been widely praised and analysed.

Humanoid robots, space travel, the science of aging--Musk was willing to weigh in on all of it at this week's World Economic Forum. But his predictions rarely work out the way he says they will. Elon Musk speaks during the World Economic Forum Annual Meeting in Davos, Switzerland on Thursday. Elon Musk, the richest man on Earth, is very good at making money. His track record of predicting the future is less stellar.

Chinese firms are building battery plants from Europe to North America, promising jobs while prompting local concerns about the environment, politics, and who really benefits. When the rest of WIRED subscribers get their hands on our next print magazine, you, dear readers of Made in China, can proudly say you heard about it here first. The issue is all about China and includes stories about robots, AI boyfriends, a Chinese town that became the crystal capital of the world, and a Chinese DNA database built for family reunions. Like this newsletter, the issue is our attempt to document how deeply Chinese technology now shapes everyday life--no matter where you live in the world. As part of the issue, I reported a story on how Chinese lithium battery companies like CATL, BYD, and Gotion are now building factories on nearly every continent.

Highly valued for their fur, martens were almost hunted to extinction in the late 20th century. Breakthroughs, discoveries, and DIY tips sent six days a week. It's understandable if you've never heard of the coastal marten. These secretive--but adorable--woodland carnivores nearly went extinct . Fortunately, these ferret-sized mammals are making a slow recovery in the forests of the Pacific Northwest.

How to claim Verizon's $20 outage credit There's very little evidence that these things even work. Elon Musk just took the stage at the World Economic Forum in Davos, Switzerland and announced that Tesla's Optimus humanoid robot by the end of next year. Musk is the, but this may be the nuttiest one yet. These are humanoid robots that are supposed to be able to do just about any task a human can do. Musk, as usual, gave himself an out if the robots don't start rolling off the assembly line in 2027, saying that they'll only be released when Tesla is confident that it's very high reliability, very high safety and the range of functionality is also very high.

Predictions that AI bot swarms were a threat to democracy weren't'fanciful', said Michael Wooldridge, professor of the foundations of AI at Oxford University. Predictions that AI bot swarms were a threat to democracy weren't'fanciful', said Michael Wooldridge, professor of the foundations of AI at Oxford University. Experts warn of threat to democracy from'AI bot swarms' infesting social media Political leaders could soon launch swarms of human-imitating AI agents to reshape public opinion in a way that threatens to undermine democracy, a high profile group of experts in AI and online misinformation has warned. The Nobel peace prize-winning free-speech activist Maria Ressa, and leading AI and social science researchers from Berkeley, Harvard, Oxford, Cambridge and Yale are among a global consortium flagging the new "disruptive threat" posed by hard-to-detect, malicious "AI swarms" infesting social media and messaging channels. A would-be autocrat could use such swarms to persuade populations to accept cancelled elections or overturn results, they said, amid predictions the technology could be deployed at scale by the time of the US presidential election in 2028.