Saved in:
| Main Authors: | Li, Hua, Jia, Xue, Kang, Yilin, Wong, Wing-Keung |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.24422 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MAKO: Meta-Adaptive Koopman Operators for Learning-based Model Predictive Control of Parametrically Uncertain Nonlinear Systems
by: Han, Minghao, et al.
Published: (2025)
by: Han, Minghao, et al.
Published: (2025)
A Homogenization Approach for Gradient-Dominated Stochastic Optimization
by: Tan, Jiyuan, et al.
Published: (2023)
by: Tan, Jiyuan, et al.
Published: (2023)
A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study
by: Ning, Yilin, et al.
Published: (2022)
by: Ning, Yilin, et al.
Published: (2022)
Audio-Agent: Leveraging LLMs For Audio Generation, Editing and Composition
by: Wang, Zixuan, et al.
Published: (2024)
by: Wang, Zixuan, et al.
Published: (2024)
An Iterative Approach to Topic Modelling
by: Wong, Albert, et al.
Published: (2024)
by: Wong, Albert, et al.
Published: (2024)
Calibrating conditional risk
by: Vasilyev, Andrey, et al.
Published: (2026)
by: Vasilyev, Andrey, et al.
Published: (2026)
SR-PredictAO: Session-based Recommendation with High-Capability Predictor Add-On
by: Wang, Ruida, et al.
Published: (2023)
by: Wang, Ruida, et al.
Published: (2023)
A Fast Method for Lasso and Logistic Lasso
by: Cheng, Siu-Wing, et al.
Published: (2024)
by: Cheng, Siu-Wing, et al.
Published: (2024)
A multi-view contrastive learning framework for spatial embeddings in risk modelling
by: Holvoet, Freek, et al.
Published: (2025)
by: Holvoet, Freek, et al.
Published: (2025)
C3LLM: Conditional Multimodal Content Generation Using Large Language Models
by: Wang, Zixuan, et al.
Published: (2024)
by: Wang, Zixuan, et al.
Published: (2024)
An AI-powered Bayesian generative modeling approach for causal inference in observational studies
by: Liu, Qiao, et al.
Published: (2025)
by: Liu, Qiao, et al.
Published: (2025)
Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation
by: Benitez, J. Antonio Lara, et al.
Published: (2023)
by: Benitez, J. Antonio Lara, et al.
Published: (2023)
Center-Outward q-Dominance: A Sample-Computable Proxy for Strong Stochastic Dominance in Multi-Objective Optimisation
by: van der Laag, Robin, et al.
Published: (2025)
by: van der Laag, Robin, et al.
Published: (2025)
Patient foundation model for risk stratification in low-risk overweight patients
by: Flamholz, Zachary N., et al.
Published: (2026)
by: Flamholz, Zachary N., et al.
Published: (2026)
Likelihood-Free Adaptive Bayesian Inference via Nonparametric Distribution Matching
by: Lu, Wenhui Sophia, et al.
Published: (2025)
by: Lu, Wenhui Sophia, et al.
Published: (2025)
An AI-powered Bayesian Generative Modeling Approach for Arbitrary Conditional Inference
by: Liu, Qiao, et al.
Published: (2026)
by: Liu, Qiao, et al.
Published: (2026)
Teaching Models to Understand (but not Generate) High-risk Data
by: Wang, Ryan, et al.
Published: (2025)
by: Wang, Ryan, et al.
Published: (2025)
Clustering in Deep Stochastic Transformers
by: Fedorov, Lev, et al.
Published: (2026)
by: Fedorov, Lev, et al.
Published: (2026)
Efficient Clustering in Stochastic Bandits
by: Chandran, G Dhinesh, et al.
Published: (2026)
by: Chandran, G Dhinesh, et al.
Published: (2026)
Stochastic Mean-Shift Clustering
by: Lapidot, Itshak, et al.
Published: (2025)
by: Lapidot, Itshak, et al.
Published: (2025)
Learning from M-Tuple Dominant Positive and Unlabeled Data
by: Qin, Jiahe, et al.
Published: (2025)
by: Qin, Jiahe, et al.
Published: (2025)
Optimization of utility-based shortfall risk: A non-asymptotic viewpoint
by: Gupte, Sumedh, et al.
Published: (2023)
by: Gupte, Sumedh, et al.
Published: (2023)
Transformer autoencoder with local attention for sparse and irregular time series with application on risk estimation
by: Rodis, Panteleimon
Published: (2026)
by: Rodis, Panteleimon
Published: (2026)
Risk-sensitive reinforcement learning using expectiles, shortfall risk and optimized certainty equivalent risk
by: Gupte, Sumedh, et al.
Published: (2026)
by: Gupte, Sumedh, et al.
Published: (2026)
Model-driven Stochastic Trace Clustering
by: Peeperkorn, Jari, et al.
Published: (2025)
by: Peeperkorn, Jari, et al.
Published: (2025)
Beyond Expectations: Learning with Stochastic Dominance Made Practical
by: Cen, Shicong, et al.
Published: (2024)
by: Cen, Shicong, et al.
Published: (2024)
Decentralized Stochastic Nonconvex Optimization under the Relaxed Smoothness
by: Luo, Luo, et al.
Published: (2025)
by: Luo, Luo, et al.
Published: (2025)
Scalarisation-based risk concepts for robust multi-objective optimisation
by: Tu, Ben, et al.
Published: (2024)
by: Tu, Ben, et al.
Published: (2024)
DLink: Distilling Layer-wise and Dominant Knowledge from EEG Foundation Models
by: Wang, Jingyuan, et al.
Published: (2026)
by: Wang, Jingyuan, et al.
Published: (2026)
An Exploration-free Method for a Linear Stochastic Bandit Driven by a Linear Gaussian Dynamical System
by: Gornet, Jonathan, et al.
Published: (2025)
by: Gornet, Jonathan, et al.
Published: (2025)
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking
by: Rioux, Gabriel, et al.
Published: (2024)
by: Rioux, Gabriel, et al.
Published: (2024)
Efficient Generative Modeling via Penalized Optimal Transport Network
by: Lu, Wenhui Sophia, et al.
Published: (2024)
by: Lu, Wenhui Sophia, et al.
Published: (2024)
Biased Dueling Bandits with Stochastic Delayed Feedback
by: Yi, Bongsoo, et al.
Published: (2024)
by: Yi, Bongsoo, et al.
Published: (2024)
Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control
by: Chittepu, Yaswanth, et al.
Published: (2026)
by: Chittepu, Yaswanth, et al.
Published: (2026)
Distill Gold from Massive Ores: Bi-level Data Pruning towards Efficient Dataset Distillation
by: Xu, Yue, et al.
Published: (2023)
by: Xu, Yue, et al.
Published: (2023)
A Discrete Perspective Towards the Construction of Sparse Probabilistic Boolean Networks
by: Fok, Christopher H., et al.
Published: (2024)
by: Fok, Christopher H., et al.
Published: (2024)
Coresets for Clustering Under Stochastic Noise
by: Huang, Lingxiao, et al.
Published: (2025)
by: Huang, Lingxiao, et al.
Published: (2025)
Mathematics of statistical sequential decision-making: concentration, risk-awareness and modelling in stochastic bandits, with applications to bariatric surgery
by: Saux, Patrick
Published: (2024)
by: Saux, Patrick
Published: (2024)
Stochastic Minimum-Cost Reach-Avoid Reinforcement Learning
by: Pan, Jingduo, et al.
Published: (2026)
by: Pan, Jingduo, et al.
Published: (2026)
Clustering risk in Non-parametric Hidden Markov and I.I.D. Models
by: Gassiat, Elisabeth, et al.
Published: (2023)
by: Gassiat, Elisabeth, et al.
Published: (2023)
Similar Items
-
MAKO: Meta-Adaptive Koopman Operators for Learning-based Model Predictive Control of Parametrically Uncertain Nonlinear Systems
by: Han, Minghao, et al.
Published: (2025) -
A Homogenization Approach for Gradient-Dominated Stochastic Optimization
by: Tan, Jiyuan, et al.
Published: (2023) -
A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study
by: Ning, Yilin, et al.
Published: (2022) -
Audio-Agent: Leveraging LLMs For Audio Generation, Editing and Composition
by: Wang, Zixuan, et al.
Published: (2024) -
An Iterative Approach to Topic Modelling
by: Wong, Albert, et al.
Published: (2024)