Abstract--Recovering latent structure from count data has received considerable attention in network inference, particularly when one seeks both cross-group interactions and within-group similarity patterns in bipartite networks, which is widely used in ecology research. Such networks are often sparse and inherently imperfect in their detection. Existing models mainly focus on interaction recovery, while the induced similarity graphs are much less studied. Moreover, sparsity is often not controlled, and scale is unbalanced, leading to oversparse or poorly rescaled estimates with degrading structural recovery. We impose nonconvex ℓ1/2 regularization on the latent similarity and connectivity structures to promote sparsity within-group similarity and cross-group connectivity with better relative scale. To solve it, we develop an ADMM-based algorithm with adaptive penalization and scale-aware initialization and establish its asymptotic feasibility and KKT stationarity of cluster points under mild regularity conditions. Experiments on synthetic and real-world ecological datasets demonstrate improved recovery of latent factors and similarity/connectivity structure relative to existing baselines. Index Terms--augmented Lagrangian, nonconvex nonsmooth optimization, nonnegative matrix factorization, link prediction, ecological network inference, structured sparse recovery I. INTRODUCTION This setting is inherent in sensing and monitoring applications [3], [4], where observations, such as counts, are obtained via an imperfect sampling process. In this paper, we are interested in ecological interaction networks describing how species associate with locations and how environments shape biodiversity patterns [5], [6].

Peter Molyneux OBE is reflecting upon the future of the UK games industry in his office - and how he could soon be leaving it. The 66-year-old, who over the years has helped create iconic series such as Fable, Black & White and Theme Park, tells me Masters of Albion - his latest project as creative director of 22cans - will also be his final one. He sees it as a return to his roots - a reinvention of the god game - a genre he introduced with Populous in 1989, one where players play as a deity on high, controlling a population's inhabitants as they please. In this new iteration, players are able to build and manage settlements by day, before defending them from attacks at night, with the ability to take control of individual characters at any point. For Molyneux, once voted one of the top game creators of all time, the key idea is freedom - creating systems that respond to player curiosity rather than directing them down a fixed path.

Meta to track workers' clicks and keystrokes to train AI Meta will start tracking the way employees work, including their keystrokes and mouse clicks, to train its artificial intelligence (AI) models. The company, which owns Instagram and Facebook, told workers on Tuesday that a new tool will run on Meta's computers and internal apps, logging their activity to be used as training data for AI technology. A Meta spokesman told the BBC: If we're building agents to help people complete everyday tasks using computers, our models need real examples of how people actually use them. The data is not used for any other purpose, he said, adding that the tool has safeguards in place to protect sensitive content. But one Meta employee, who asked not to be identified, said having their smallest actions on a computer being used to train AI model as workers expect a slew of additional job cuts feels very dystopian.

Why did Trump fire Pam Bondi? Trump's US Fed nominee Warsh vows independence, says he's no'sock puppet' Kevin Warsh, United States President Donald Trump's pick to lead the Federal Reserve, has addressed concerns about his independence pending his appointment to the bank amid fears that Trump could sway his decisions on monetary policy. On Tuesday, Warsh -- who served on the central bank's Board of Governors from 2006 to 2011 -- faced waves of criticism during a confirmation hearing of the Senate Banking Committee where Democrats voiced concerns about the Fed's independence should he be appointed to lead the organisation. "I do not believe the operational independence of monetary policy is particularly threatened when elected officials -- presidents, senators, or members of the House -- state their views on interest rates," Warsh said. "Monetary policy independence is essential. Monetary policymakers must act in the nation's interest . . . Warsh, 56, also called for "regime change" at the US central bank, including a new approach for controlling inflation and a communications overhaul that may discourage his colleagues from saying too much about the direction of monetary policy. Warsh blamed the central bank for an inflation surge after it slashed interest rates to nearly zero in the wake of the COVID-19 pandemic, a move that continues to hurt US households. Concerned by the implications of artificial intelligence for jobs - expected to increase productivity - and prices, he said he would move quickly to see if new data tools could provide better insight on inflation, and would also discourage policymakers from saying too much about where interest rates might be heading. "What the Fed needs are reforms to its frameworks and reforms to its communications," the former Fed governor said. "Too many Fed officials opine about where interest rates should be That is quite unhelpful." Warsh has also long been an advocate for shrinking the Fed's $6.7 trillion balance sheet. In the Tuesday hearing, he said any such plans would take time and must be publicly discussed well in advance. Jai Kedia, a research fellow at the Center for Monetary and Financial Alternatives at the libertarian Cato Institute, told Al Jazeera that there were many "encouraging" signs in Warsh's candidacy. "Warsh is presenting himself as a regime change candidate at a time when the Fed needs serious reform," Kedia noted. "Particularly encouraging was his understanding of the negative effects of QE and his focus on reducing the balance sheet.

OpenAI is facing a criminal investigation in the US over whether its ChatGPT technology played a part in the murder of two people during a mass shooting at Florida State University last year. Florida's Attorney General James Uthmeier said on Tuesday his office had been looking into the use of the artificial intelligence (AI) chatbot by a man who allegedly shot several people at the campus in Tallahassee. Our review has revealed that a criminal investigation is necessary, Uthmeier said. ChatGPT offered significant advice to this shooter before he committed such heinous crimes. An OpenAI spokesperson said: ChatGPT is not responsible for this terrible crime.

Environment Animals Wildlife Endangered Species Earth's largest otters have chocolate bar-sized babies Chester Zoo celebrates the birth of giant otter triplets. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. While they only weigh 7.1 ounces as babies, giant otters can grow to six-feet-long and weigh up to 71 pounds. Breakthroughs, discoveries, and DIY tips sent six days a week. It turns out that giant otter () newborns are actually quite small, weighing just around 7.1 ounces.

Court challenge over Met Police's use of live facial recognition thrown out Privacy campaigners have lost a High Court challenge aimed at limiting the Metropolitan Police's use of live facial recognition technology. Youth worker Shaun Thompson, and Silkie Carlo, director of campaign group Big Brother Watch, brought the claim over concerns that facial recognition could be used arbitrarily or in a discriminatory way. Scotland Yard defended the challenge, telling the court that the policy was lawful. The Met Police will continue to use the technology, with commissioner Sir Mark Rowley calling the ruling an important victory for public safety. One of the claimants, Thompson, was misidentified by live facial recognition technology (LFR).

'This is an apartheid regime' Israeli soldiers and settlers have killed at least 11 Palestinians across Gaza and the occupied West Bank, according to Palestinian officials and local media, in the latest bloodshed to occur during a "ceasefire" announced in October. In Gaza, at least seven Palestinians were killed in a series of Israeli attacks, including a child who died from injuries sustained days earlier, while 21 were reported on Tuesday to have been injured over a 24-hour period. Another Palestinian man was later killed on Tuesday in an Israeli drone attack near the Sheikh Nasser neighbourhood, east of Khan Younis. In northern Gaza, a Palestinian woman was killed when Israeli naval forces shelled tents sheltering displaced families northwest of Beit Lahiya. Verified video obtained by Al Jazeera showed the body of Abdullah Dawas, a child wrapped in white cloth for burial, after he succumbed to injuries 10 days after being shot in the head near al-Fakhoura clinic in northern Gaza's Jabalia refugee camp.

Ashlin McCourt clocks up 60 hours a week working as a civil servant, a waitress and a baker because life's so expensive, she says. The UK unemployment rate stands at 4.9% - however, increasing numbers of those in work are juggling more than one job. While working in multiple jobs and side hustles has long been a needs must for many households to manage the cost of living, there are now a record 1.35 million adults working at least two jobs. It is mostly Gen Z - adults aged up to 29 - driving this poly-employment trend - according to Deputy, a global workforce management platform, which analysed more than 20 million shifts done by over 300,000 UK workers. For 28-year-old Ashlin from Northern Ireland, having more than one job seems normal.

Conformal prediction provides finite-sample, distribution-free coverage under exchangeability, but standard constructions may lack robustness in the presence of outliers or heavy tails. We propose a robust conformal method based on a non-conformity score defined as the half-mass radius around a point, equivalently the distance to its $(\lfloor n/2\rfloor+1)$-nearest neighbour. We show that the resulting conformal regions are marginally valid for any sample size and converge in probability to a robust population central set defined through a distance-to-a-measure functional. Under mild regularity conditions, we establish exponential concentration and tail bounds that quantify the deviation between the empirical conformal region and its population counterpart. These results provide a probabilistic justification for using robust geometric scores in conformal prediction, even for heavy-tailed or multi-modal distributions.