言栖资讯收录 190110 篇 AI、开发与建站文章，按发布时间排序，支持搜索与按语言筛选。
arXiv:2611.08414v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) is commonly used in both supervised fine-tuning (SFT) and reinforcement learning (R…
arXiv:2611.08409v1 Announce Type: cross Abstract: Uncertainty quantification is crucial in scientific machine learning, where models inform safety-critical task…
arXiv:2611.08182v1 Announce Type: cross Abstract: We identify an intriguing phenomenon when linearly interpolating between permutation-aligned neural networks: …
arXiv:2611.08077v1 Announce Type: cross Abstract: We propose a doubly-robust method to estimate the causal effects of multi-valued treatment regimes on patient …
arXiv:2611.07773v1 Announce Type: cross Abstract: We study learning in zero-sum games with delayed feedback. We introduce Multi-Anchor Optimistic Online Mirror …
arXiv:2611.07536v1 Announce Type: cross Abstract: The joint expectation of functions of potential outcomes $(Y_1,Y_0)$ is a fundamental quantity in causal infer…
arXiv:2611.07399v1 Announce Type: cross Abstract: We study distribution-free uncertainty quantification for a changepoint estimate in an offline setting. We obs…
arXiv:2611.07334v1 Announce Type: cross Abstract: Last-iterate convergence guarantees for stochastic gradient methods have attracted significant attention as pr…
arXiv:2611.07287v1 Announce Type: cross Abstract: High-frequency volatility forecasting typically separates measurement from prediction: intraday observations a…
arXiv:2611.07270v1 Announce Type: cross Abstract: Animals and humans often do not maximize; they act relative to goals (aspiration levels) that are frequently n…
arXiv:2611.07249v1 Announce Type: cross Abstract: This paper examines robustness and causal interpretation of panel estimates using double/debiased machine lear…
arXiv:2611.08358v1 Announce Type: new Abstract: At the edge of stability, the iterates of gradient descent oscillate along the sharp directions of the Hessian. …
arXiv:2611.08252v1 Announce Type: new Abstract: We consider the problem of cross-validation (CV) in time series forecasting, with a focus on global forecasting …
arXiv:2611.08160v1 Announce Type: new Abstract: Attention-based time series forecasters commonly group consecutive observations into patches. Patch length is kn…
arXiv:2611.08113v1 Announce Type: new Abstract: State-space models (SSMs) recover low-dimensional latent dynamics from high-dimensional observations, but latent…
arXiv:2611.07937v1 Announce Type: new Abstract: Functional data analysis provides a framework for studying time-varying associations between covariates and high…
arXiv:2611.07879v1 Announce Type: new Abstract: Estimating causal effects from observational network data requires accounting for both individual treatment and …
arXiv:2611.07209v1 Announce Type: new Abstract: Random features approximate kernel integrals by Monte Carlo, yet only selected frequency-sampling errors affect …
arXiv:2611.07173v1 Announce Type: new Abstract: Shapley values are a central tool for attribution in machine learning. Since their exact computation requires ev…
arXiv:2611.07129v1 Announce Type: new Abstract: Tensor Network (TN) kernel machines accelerate supervised learning by using low-rank TNs to reduce computation a…