Iranian sleeper cells prompt President Donald Trump warning as Canadian opposition lawmakers accuse government of allowing Tehran operatives to remain despite visa cancellations.

Common modifications include:(i)tuning attack parameters (e.g., number ofsteps),(ii)replacing network components to simplify the attack (e.g., removing randomization or non-differentiable components), and(iii) replacing the loss function optimized by the attack.

Things to Do in L.A. Canadian snowbirds are still unhappy with Trump. This is read by an automated voice. Please report any issues or inconsistencies here . Palm Springs relies heavily on Canadian tourists, who are declining to travel to the U.S. or shortening their stays because of Trump. The number of Canadian visitors to California plummeted more than 18% in 2025 compared with the year prior.

Lack of samples per minute or per hour (metrics 1 and 2) are helping to understand 4G networking issues.

While many techniques for detecting these attacks have been proposed, theyareeasily bypassed when theadversary hasfullknowledge of the detection mechanism and adapts the attack strategy accordingly. In this paper,we adopt anovel perspectiveand regard the omnipresence of adversarial perturbations asastrength rather thanaweakness.

Recent progress in the development of voltage indicators [1-8] has brought us closer to a longstanding goal incellular neuroscience: imaging the full spatiotemporal voltageonadendritic tree. These recordings have the potential (pun not intended) to resolve fundamental questions about the computations performed by dendrites -- questions that have remained open for more than a century[9,10].

This allows us to derive an upper bound on the susceptibility of explanations to manipulations.

Wedemonstrate that our visualization provides intuitive, detailed summaries of the learning dynamics beyond simple global measures (i.e., validation loss and accuracy), without the need to access validation data. Furthermore, M-PHATE better captures both the dynamics and community structure of the hidden units as compared to visualization based on standard dimensionality reduction methods (e.g., ISOMAP,t-SNE).

Despite recent provably guaranteed variants, the empirical performance often remains unsatisfactory.

Actor-critic methods, a type of model-free Reinforcement Learning, have beensuccessfully applied to challenging tasks in continuous control, often achievingstate-of-the artperformance.