Photo finishing tuning aims to automate the manual tuning process of the photo finishing pipeline, like Adobe Lightroom or Darktable. Previous works either use zeroth-order optimization, which is slow when the set of parameters increases, or rely on a differentiable proxy of the target finishing pipeline, which is hard to train. To overcome these challenges, we propose a novel goal-conditioned reinforcement learning framework for efficiently tuning parameters using a goal image as a condition. Unlike previous approaches, our tuning framework does not rely on any proxy and treats the photo finishing pipeline as a black box. Utilizing a trained reinforcement learning policy, it can efficiently find the desired set of parameters within just 10 queries, while optimization-based approaches normally take 200 queries. Furthermore, our architecture utilizes a goal image to guide the iterative tuning of pipeline parameters, allowing for flexible conditioning on pixel-aligned target images, style images, or any other visually representable goals. We conduct detailed experiments on photo finishing tuning and photo stylization tuning tasks, demonstrating the advantages of our method.

Our main contribution is a pair of polynomial-time DP algorithms for the task of private GM with an excess error guarantee that scales with the effective diameter of the datapoints. Additionally, we propose an inefficient algorithm based on the inverse smooth sensitivity mechanism, which satisfies the more restrictive notion of pure DP. We complement our results with a lower bound and demonstrate the optimality of our polynomial-time algorithms in terms of sample complexity.

The transformative impact of large language models (LLMs) like LLaMA and GPT on natural language processing is countered by their prohibitive computational demands. Pruning has emerged as a pivotal compression strategy, introducing sparsity to enhance both memory and computational efficiency. Yet, traditional global pruning is impractical for LLMs due to scalability issues, while local pruning, despite its efficiency, leads to suboptimal solutions. Addressing these challenges, we propose SparseLLM, a novel framework that redefines the global pruning process into manageable, coordinated subproblems, allowing for resource-efficient optimization with global optimality. SparseLLM's approach, which conceptualizes LLMs as a chain of modular functions and leverages auxiliary variables for problem decomposition, not only facilitates a pragmatic application on LLMs but also demonstrates significant performance improvements, particularly in high-sparsity regimes, surpassing current state-of-the-art methods.

One of the key challenges in machine learning is to find interpretable representations of learned functions. The Möbius transform is essential for this purpose, as its coefficients correspond to unique importance scores for sets of input variables. This transform is closely related to widely used game-theoretic notions of importance like the Shapley and Bhanzaf value, but it also captures crucial higher-order interactions.

TL;DR: Get a lifetime license to Windows 11 Pro for just 14.97 and unlock a sleek interface, pro-level security, and AI-powered productivity. Need a new laptop but don't have the budget to buy one? We've found the next best thing: updating your operating system. If you've got an old PC that could use an upgrade, a lifetime license to Microsoft Windows 11 Pro is now just 14.97. But you'll want to act fast because this deal ends June 1 at 11:59 p.m. PT.

TL;DR: Give your productivity a big boost with a lifetime license to Microsoft Office Home & Business for Mac 2021, now 69.97 (reg. There's a reason Microsoft Office is still around in 2025 -- these apps really work. They range from classics like Word and Excel, which have been around since the days of chunky desktop computers, to newer additions like Teams and OneNote. Right now, you can get them forever with this lifetime license to Microsoft Office Home & Business for Mac 2021, on sale for 69.97 (reg. Give your Apple computer an upgrade for under 75 with this Microsoft Office Home & Business for Mac 2021 license.

TL;DR: Never run out of things to watch with this lifetime subscription to BitMar Streaming Content-Finder, now just 14.99 (reg. BitMar is a streaming content finder ready to help you discover free entertainment all over the web -- from movies and shows to songs and more -- and right now, a lifetime subscription to this helpful tool is just 14.99 with code BITMAR5 until June 1. If you're sick of wasting hours hunting down things to watch, it's time to swap to BitMar. It's your very own AI-powered free content finder -- it scours the web to find you millions of free movies, TV shows, videos, music, and more. And unlike all the expensive streaming services you pay for monthly, you pay once for BitMar and enjoy it forever.

At Google I/O 2025, the tech company announced a ton of new AI features, and one of the most interesting is a virtual clothing try-on tool. The Google Shopping "Try it on" feature lets users upload a photo of themselves and then virtually try on clothes, basically the IRL version of the Clueless closet millennials have been dreaming about since 1995. Or, as Mashable Shopping Reporter Haley Henschel put it, "Google's latest shopping feature makes Cher Horowitz's computerized closet a reality." Almost as soon as the feature was released, users started trying to "jailbreak" the tool, which is becoming a fun little tradition for tech writers every time a new AI model or tool is released. On Friday, The Atlantic reported that "Google's new AI shopping tool appears eager to give J.D. Vance breasts."

On May 19, President Donald Trump and First Lady Melania Trump beamed to press and allies as they signed the administration's first major piece of tech regulation, the bipartisan Take It Down Act. It was seen as a win for those who have long been calling on the criminalization of NDII, or the nonconsensual distribution of intimate images, and a federal pathway of redress for victims. Cliff Steinhauer, director of information security and engagement at the National Cybersecurity Alliance, explained it may be a needed kick in the pants to a lethargic legislative arena. "I think it's good that they're going to force social media companies to have a process in place to remove content that people ask to be removed," he said. "This is kind of a start; to build the infrastructure to be able to respond to this type of request, and it's a really thin slice of what the issues with AI are going to be."

What started with Microsoft Build, continued with Google I/O, and ended with Anthropic Code with Claude, plus a big hardware interruption from OpenAI, the week has finally come to a close. AI announcements from the developer conferences jockeyed for news dominance this week, but OpenAI managed to make headlines without an event by announcing that it's going to start making AI devices with iPhone designer Jony Ives We'll get to that, plus all the major AI features from Google and Microsoft and details about Anthropic's new models. Take a look at the AI news of the week, then enjoy a well-deserved weekend. On Thursday, Anthropic introduced the next generation of its Claude models: Opus 4 and Sonnet 4. Claude Opus 4 is the bigger, more powerful model, while Sonnet 4 is smaller and nimbler. Anthropic said both models scored higher than their rivals on agentic AI benchmarks and said they're particularly good for coding and reasoning tasks.