Conformal policy learning (CPL) is proposed, a policy learning procedure with a new distribution-free safety guarantee that controls the probability of assigning treatment to an individual who would be harmed relative to control and achieves asymptotically optimal welfare subject to the safety constraint.
In various fields, such as medicine and marketing, accurately predicting individual treatment effects holds significant promise. However, achieving reliable predictions alone is often insufficient for making informed decisions; it is equally important to understand why the treatment effect is higher for some individual...
We propose Low-Rank Quantile Surfaces (LRQS), a bivariate causal model in which, in the causal direction, an unknown monotone transformation of the conditional quantile surface admits a low-rank functional decomposition. LRQS subsumes location-scale noise models and post-nonlinear heteroscedastic noise models, while al...
A derandomization framework for stochastic majority votes is proposed that derives two families of high-probability generalization bounds, covering both data-independent and data-dependent constructions of the ensemble, which naturally lead to a self-bounding learning algorithm optimizing deterministic majority vote gu...
J. Bastian, Benjamin Leblanc, Pascal Germain et al.· 0 citations
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Time-warping estimation is a fundamental problem in signal processing with applications in bioacoustics, radar, and biomedical analysis. This paper introduces a Time-Warping Estimation Trainable (TWET) model for estimating timewarping functions from a single observation. The proposed approach formulates time-warping es...
We develop a certified continuation framework for inference and training in deep equilibrium networks (DEQs), with training posed as interpolation to accuracy $2^{-b}$. For inference, input homotopy selects an equilibrium branch from a supplied start root, and a rounded tracker follows it under quantitative conditionin...
A look-ahead tree-building method that evaluates each candidate split by the prediction error reduction achieved after growing a conventional CART subtree below that split, and a smart look-ahead algorithm that learns downstream split values using node-level features are described.
Andrew Gao, Tian-Li Liu, Rui-Chen Han et al.· 0 citations
It is indicated that when rebalancing is applied during training matters as much as how much rebalancing is applied, which exposes the tension between unbiased optimisation of the empirical loss and fair representation of rare classes.
This paper characterise the optimal split under data-dependent evaluation geometries induced by the fine-tuning problem as a compute-split problem under a two-stage pretrain--fine-tune procedure with fixed total optimisation budget, using regularised least squares trained by gradient descent as a tractable setting.
Alex Buna, Fang-Hui Liu, Patrick Rebeschini· 0 citations
A novel cluster-friendly data presentation framework that integrates the non-Gaussian and non-linear feature dependence of copula models with an ensemble of causal structure discovery methods based on Directed Acyclic Graphs (DAGs).
Heranga K. Rathnasekara, N. Diawara, Manar D. Samad· 0 citations
Coupled Calibration and Learning (CCL) is proposed, an LLM distillation algorithm that couples teacher calibration with student updates through token-level branching, using reward feedback only on source questions.
Hai-Chen Hu, Yu-Heng Zhang, David Simchi-Levi· 0 citations
A ablation study confirms that both quantum and classical components are essential, and results highlight the central role of the feature map in hybrid quantum-classical models.
K. O. Ayena, F. Holweck, Serge Iovleff et al.· International Conference on...· 0 citations
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
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