We study the problem of estimating the effect function for a continuous treatment, which maps each treatment value to a population-averaged outcome. A central challenge in this setting is confounding: treatment assignment often depends on covariates, creating selection bias that makes direct regression of the response on treatment unreliable. To address this issue, we propose a two-stage kernel ridge regression method. In the first stage, we learn a model for the response as a function of both treatment and covariates; in the second stage, we use this model to construct pseudo-outcomes that correct for distribution shift, and then fit a second model to estimate the treatment effect. Although the response varies with both treatment and covariates, the induced effect function obtained by averaging over covariates is typically much simpler, and our estimator adapts to this structure. Furthermore, we introduce a fully data-driven model selection procedure that achieves provable adaptivity to both the unknown degree of overlap and the regularity (eigenvalue decay) of the underlying kernel.

We investigate stochastic combinatorial semi-bandits, where the entire joint distribution of outcomes impacts the complexity of the problem instance (unlike in the standard bandits). Typical distributions considered depend on specific parameter values, whose prior knowledge is required in theory but quite difficult to estimate in practice; an example is the commonly assumed sub-Gaussian family. We alleviate this issue by instead considering a new general family of sub-exponential distributions, which contains bounded and Gaussian ones. We prove a new lower bound on the expected regret on this family, that is parameterized by the unknown covariance matrix of outcomes, a tighter quantity than the sub-Gaussian matrix. We then construct an algorithm that uses covariance estimates, and provide a tight asymptotic analysis of the regret. Finally, we apply and extend our results to the family of sparse outcomes, which has applications in many recommender systems.

Causal representation learning (CRL) aims to identify the underlying latent variables from high-dimensional observations, even when variables are dependent with each other. We study this problem for latent variables that follow a potentially degenerate Gaussian mixture distribution and that are only observed through the transformation via a piecewise affine mixing function. We provide a series of progressively stronger identifiability results for this challenging setting in which the probability density functions are ill-defined because of the potential degeneracy. For identifiability up to permutation and scaling, we leverage a sparsity regularization on the learned representation. Based on our theoretical results, we propose a two-stage method to estimate the latent variables by enforcing sparsity and Gaussianity in the learned representations. Experiments on synthetic and image data highlight our method's effectiveness in recovering the ground-truth latent variables.

Davis, Drusvyatskiy, and Jiang showed that gradient descent with an adaptive stepsize converges locally at a nearly-linear rate for smooth functions that grow at least quartically away from their minimizers. The argument is intricate, relying on monitoring the performance of the algorithm relative to a certain manifold of slow growth -- called the ravine. In this work, we provide a direct Lyapunov-based argument that bypasses these difficulties when the objective is in addition convex and a has a unique minimizer. As a byproduct of the argument, we obtain a more adaptive variant than the original algorithm with encouraging numerical performance.

Science Archaeology Shakespeare's long-lost London home is finally found In the past 100 years, the spot has been an architecture firm, carpet wholesaler, and more. 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. Shakespeare likely spent the majority of his later life in Stratford-upon-Avon. Breakthroughs, discoveries, and DIY tips sent six days a week. By the end of his career, William Shakespeare was a bona fide celebrity boasting multiple homes across England. Historical documents indicate the legendary playwright spent the majority of his later years in the town of his youth, Stratford-upon-Avon, but he also owned property in the Blackfriars precinct.

Intelligent, egoless the artist in Grayson Perry Has Seen the Future. Intelligent, egoless the artist in Grayson Perry Has Seen the Future. From people marrying digital companions to CEOs excited about how people whose jobs are replaced can'adapt', this is terrifying watching. T here is a fun game you can play while watching Grayson Perry Has Seen the Future, the two-part documentary presented by the artist on the subject of artificial intelligence, its uses and its possible ramifications. Gather a group of friends, press play, and see which of you loses your mind first.

The USS Cassin Young is one of the last of the war's Fletcher-class destroyers. 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. The USS Cassin Young is one of four remaining Fletcher-class destroyers still afloat. Breakthroughs, discoveries, and DIY tips sent six days a week. Although its name may not sound immediately familiar, the over 360-foot-long ship's recognizable silhouette remains a hallmark example of World War II imagery.

Researchers hope the experiments will pave the way for people with paralysis to explore virtual worlds or more intuitively control electric wheelchairs in this one. Peter Janssen at KU Leuven in Belgium and colleagues implanted three rhesus macaque ( Macaca mulatta) monkeys with BCIs. Crucially, each animal got three implants, each consisting of 96 electrodes, positioned in the primary motor, dorsal and ventral premotor cortex. The first area is commonly used in BCI research and relates to physical movement, but the latter two are thought to be involved in planning movement in a higher, more abstract way. Electrical signals from the implants were then interpreted by an AI model and used to control VR avatars as the monkeys watched a 3D monitor.

New Scientist recommends Jamie Bartlett's insightful How to Talk to AI I don't use AI chatbots, so you might wonder what use I could make of Jamie Bartlett's book, . Well, this plain-speaking guide makes the compelling case that, despite their popularity, we don't know how to speak to chatbots properly. Few of us have had adequate training on getting the most out of AI - or on how to protect ourselves from it . That's where it can all go very wrong, sending us down misinformation rabbit holes or fostering emotional dependence. Mastering the art of prompting a chatbot is about more than AI, says Bartlett.

The poached ingredients worth $1.3 million were seized in a nationwide hunt. 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. Shark fins remain a prized delicacy despite conservation efforts and education. Breakthroughs, discoveries, and DIY tips sent six days a week. The United States Fish and Wildlife Service (FWS) recently exposed a major international smuggling operation orchestrated across at least three cities around the country.