Quantum Support Vector Machines face scalability challenges due to high-dimensional quantum states and hardware limitations. We propose an embedding-aware quantum-classical pipeline combining class-balanced k-means distillation with pretrained Vision Transformer embeddings. Our key finding: ViT embeddings uniquely enable quantum advantage, achieving up to 8.02% accuracy improvements over classical SVMs on Fashion-MNIST and 4.42% on MNIST, while CNN features show performance degradation. Using 16-qubit tensor network simulation via cuTensorNet, we provide the first systematic evidence that quantum kernel advantage depends critically on embedding choice, revealing fundamental synergy between transformer attention and quantum feature spaces. This provides a practical pathway for scalable quantum machine learning that leverages modern neural architectures.

Critical Learning Periods comprehend an important phenomenon involving deep learning, where early epochs play a decisive role in the success of many training recipes, such as data augmentation. Existing works confirm the existence of this phenomenon and provide useful insights. However, the literature lacks efforts to precisely identify when critical periods occur. In this work, we fill this gap by introducing a systematic approach for identifying critical periods during the training of deep neural networks, focusing on eliminating computationally intensive regularization techniques and effectively applying mechanisms for reducing computational costs, such as data pruning. Our method leverages generalization prediction mechanisms to pinpoint critical phases where training recipes yield maximum benefits to the predictive ability of models. By halting resource-intensive recipes beyond these periods, we significantly accelerate the learning phase and achieve reductions in training time, energy consumption, and CO$_2$ emissions. Experiments on standard architectures and benchmarks confirm the effectiveness of our method. Specifically, we achieve significant milestones by reducing the training time of popular architectures by up to 59.67%, leading to a 59.47% decrease in CO$_2$ emissions and a 60% reduction in financial costs, without compromising performance. Our work enhances understanding of training dynamics and paves the way for more sustainable and efficient deep learning practices, particularly in resource-constrained environments. In the era of the race for foundation models, we believe our method emerges as a valuable framework. The repository is available at https://github.com/baunilhamarga/critical-periods

Newsom blasts'pathetic' Democrats for'surrendering' to Trump as'gang of eight' senators join Republicans to end longest government shutdown in US history Olympics set to ban ALL transgender athletes and Imane Khelif'DSD' competitors from female events after'finding scientific evidence of advantages to being born male' The REAL story of how Meghan lost her best friend: They've not spoken in years... but now insiders reveal'aggravation' and tensions that go'deeper than anyone knows' Scientists are baffled to discover mysterious'voids' in the third-largest pyramid of Giza - as scans suggest they could be a secret entrance Jordon Hudson appears to dodge encounter with Bill Belichick's daughter-in-law at UNC game after social media dig PayPal billionaire delivers chilling warning about spread of Communism as eerily prescient comment comes to light in wake of Mamdani's win Has Sydney Sweeney become too toxic for Hollywood? Star suffers box office flop with new film Christy after THAT controversial ad, Zendaya'feud' and backlash over her political views Dark side of Danielle Bernstein: She is America's most hated influencer... but now insiders reveal claims of behavior so outrageous they'kind of respect her' for getting away with it My brother was ALIVE on the operating table as surgeons tried to harvest his organs. Donald Trump launches new broadside at'corrupt' BBC journalists as director-general Tim Davie and news boss both quit in disgrace over doctored video of US President Meghan Markle wealthy pal's bookshop'is reported to council for serving her As Ever wine without a licence' after duchess used it as promotional pop-up Sussexes attended charity gala with Serena Williams before Kris Jenner's birthday party - while Royal Family marked Remembrance Sunday NFL announcer Tony Romo slammed by fans after outrageous'DTF' sexual reference live on air Donald Trump makes stunning flyover for first NFL visit of the season... hours after it emerged he wants $3.7bn new stadium named after him Jay Leno makes touching remark about caring for wife Mavis after 45 years of marriage amid heartbreaking'advanced' dementia diagnosis Barbara Bach captured America's hearts as a Bond girl... see her now after 44 years as a Beatle's wife Humanoid robot moves so smoothly, its inventor is forced to cut it open to prove there's not a person hiding inside READ MORE: Nike launches the world's first powered footwear A humanoid robot has reached new depths of the uncanny valley with its smooth, humanlike movements. Chinese electric vehicle manufacturer, Xpeng, revealed its latest robot dubbed the Xpeng IRON, at an event last week. The bot proved so eerily lifelike that its inventors were forced to cut it open on stage to prove there wasn't a person hiding inside.

Is Trump losing patience with Putin? Will sanctions against Russian oil giants hurt Putin? Is the fall of Pokrovsk, Ukraine's key eastern stronghold, inevitable? Pokrovsk, a key fortress and logistical hub for Ukrainian forces in the eastern region of Donbas, has been under siege for almost two years. But in recent weeks, tens of thousands of Russian soldiers have been storming the town around the clock, taking over the streets where buildings are mostly reduced to bombed-out, deserted ruins. They use reconnaissance drones and satellite images to identify gaps in Ukrainian defences and use tiny groups of soldiers who are attacked and killed in droves by Ukrainian drones .

At seventy-three, the former front man of Talking Heads is still asking questions about what it means to be alive. "When you step onstage, it's a very artificial situation," Byrne said. "To pretend it's not--that isn't being authentic." If you spend enough time wandering around downtown Manhattan, the odds are that you'll eventually encounter the musician David Byrne riding a bicycle. One day this past June, pedalling alongside Byrne from his apartment in Chelsea to the Governors Island ferry, I watched at least a dozen New Yorkers clock his profile, whipping around to squint, softly pinching the arm of their companion and whispering, "Was that . . . By then, Byrne was gone, a tuft of white hair whizzing toward the horizon. Spotting Byrne on two wheels has become a New York City rite of passage, like sussing out the best halal cart in midtown, or dropping something important onto the subway tracks. During the few months that Byrne and I spent together, I never saw him traverse the ...

Stocks from the United States to Japan have risen sharply amid hopes that an end to the longest US government shutdown in history is imminent. US lawmakers on Sunday moved to end a five-week impasse over government funding, a boost for investors unnerved by signs of growing weakness in the US economy and the sky-high evaluations of firms involved in artificial intelligence. The funding package still needs to win final approval in the Senate and then pass the US House of Representatives, after which it would go to US President Donald Trump for his signature - a process expected to take days. Stock markets in the Asia Pacific made large gains on Monday, while futures in the US also rose in advance of stock exchanges reopening. South Korea's benchmark KOSPI led the gains, rising about 3 percent as of 4pm local time (07:00 GMT).

Doctors from Scotland and the US have completed what is thought to be a world-first stroke procedure using a robot. Prof Iris Grunwald, of the University of Dundee, performed the remote thrombectomy - the removal of blood clots after a stroke - on a human cadaver that had been donated to medical science. The professor was at Ninewells Hospital in Dundee, while the body she was operating on while using the machine was across the city at the university. Hours later, Ricardo Hanel - a neurosurgeon in Florida - used the technology to carry out the first transatlantic surgery from his Jacksonville base on a human body in Dundee over 4,000 miles (6,400km) away. The team has called it a potential game changer if it becomes approved for use on patients.

A woman who was plunged into sudden menopause after surgery to remove both ovaries is spearheading efforts to change NHS policy. Kate Dyson, 44, from Hastings, East Sussex, underwent the surgery six months ago after having a subtotal hysterectomy in 2021 to remove her uterus - a procedure which leaves the cervix in place. The mum-of-three says she was completely unprepared for the impact of surgical menopause, which is triggered by both ovaries being removed. Honestly, it was like falling off a hormonal cliff edge, she told BBC Radio Sussex. Within hours of the surgery I was home the same day.

You probably don't give much thought to the device that you're reading this article on, as long as it looks good and keeps working. But the elements that power and run it are the subject of an escalating struggle between the world's two biggest economies - the US and China - with African countries in the eye of the storm. The African continent is rich in critical minerals and metals - like lithium, rare earths, cobalt and tungsten - which are vital to making and running our personal tech. Such materials are also essential for everything from electric vehicles, to AI data centres, and weapon systems. China has long been the biggest player in the global market for critical minerals and metals.

Creating programs to represent board games can be a time-consuming task. Large Language Models (LLMs) arise as appealing tools to expedite this process, given their capacity to efficiently generate code from simple contextual information. In this work, we propose a method to test how capable three LLMs (Claude, DeepSeek and ChatGPT) are at creating code for board games, as well as new variants of existing games.