PAC
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Related Articles from SNS
SJD-PAC: Accelerating Speculative Jacobi Decoding via Proactive Drafting and Adaptive Continuation
arXiv:2603.18599v2 Announce Type: replace Abstract: Speculative Jacobi Decoding (SJD) offers a draft-model-free approach to accelerate autoregressive text-to-image synthesis. However, the high-entropy nature of visual generation yields low draft-token acceptance rates in complex regions, creating a bottleneck that severely limits overall throughput. To overcome this, we introduce SJD-PAC, an enhanced SJD framework.
Six-year-old girl in Great Ormond Street after rash turns to 'Pac-Man disease'
Six-year-old girl in Great Ormond Street after rash turns to 'Pac-Man disease' Esmae Smith has been in hospital since April as doctors fight to stop the illness A six-year-old girl who developed a rash after hot weather deteriorated quickly and was rushed to Great Ormond Street Hospital. Starr Downs assumed daughter Esmae Smith's rash on her hands and feet was an 'allergic reaction' or a rash from the weather.
PAC-Bayesian Adversarially Robust Generalization for Message Passing Graph Neural Networks: A Sensitivity Analysis
arXiv:2606.06293v1 Announce Type: new Abstract: Whilst the vulnerability of graph neural networks (GNNs) to adversarial attacks poses a critical threat to graph representation learning, the understanding of the robust generalization behavior remains a fundamental challenge in the adversarial setting. Recently, PAC-Bayesian margin-based generalization analysis substantially advances this line of research by providing a flexible and data-dependent analytical framework. However, existing robust...
Trump-backed super PAC to host a $1M-per-person fundraiser the day before the White House UFC fight
The top super PAC backed by President Donald Trump is set to hold a $1 million-per-person fundraiser Saturday, the day before he hosts Ultimate Fighting Championship matches on the White House grounds. The seven-figure fundraising event will take place at Trump’s golf club in the Washington suburbs, in Northern Virginia, according to four people familiar with the matter. Money raised at the fundraiser will benefit MAGA Inc., which has collected $342 million this election cycle and is...
Powerful A.I. Super PACs Duel Over the Midterms: ‘This Is a War’
The artificial intelligence industry has begun spending tens of millions of dollars on elections, routing the money through allied super PACs.
Powerful A.I. Super PACs Duel Over the Midterms: ‘This Is a War’
The artificial intelligence industry has begun spending tens of millions of dollars on elections, routing the money through allied super PACs.
PAC-Bayesian Reinforcement Learning Trains Generalizable Policies
Announce Type: replace Abstract: We derive a novel PAC-Bayesian generalization bound for reinforcement learning that explicitly accounts for Markov dependencies in the data, through the chain's mixing time. This contributes to overcoming challenges in obtaining generalization guarantees for reinforcement learning, where the sequential nature of data breaks the independence assumptions underlying classical bounds. The new bound provides non-vacuous certificates for modern off-policy...
Symmetries in PAC-Bayesian Learning
arXiv:2510.17303v2 Announce Type: replace Abstract: Symmetries are known to improve the empirical performance of machine learning models, yet theoretical guarantees explaining these gains remain limited. Prior work has focused mainly on compact group symmetries and often assumes that the data distribution itself is invariant, an assumption rarely satisfied in real-world applications. In this work, we extend generalization guarantees to the broader setting of non-compact symmetries, such as...
pacSTL: PAC-Bounded Signal Temporal Logic from Data-Driven Reachability Analysis
Announce Type: replace Abstract: Signal Temporal Logic (STL) is an expressive language for specifying behaviors of dynamical systems from continuous signals. However, a limitation of standard STL is its inherently deterministic semantics, which prevents it from accommodating uncertainty. Existing approaches to overcome this limitation are computationally costly and limit real-time capability, requiring repeated trajectory sampling or the redesign of probability distributions over atomic...