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Direct Preference Optimization (DPO) has become a popular method for fine-tuning large language models (LLMs) due to its stability and simplicity. However, it is also known to be sensitive to noise in the data and prone to overfitting.…

Machine Learning · Computer Science 2025-10-28 Cheol Woo Kim , Shresth Verma , Mauricio Tec , Milind Tambe

A framework for online robust adaptive radiation therapy (ART) is presented. This framework is designed to (i) handle interfractional geometric variations following a probability distribution different from the a priori hypothesis, (ii)…

Medical Physics · Physics 2020-09-09 Michelle Böck

This paper studies Distributionally Robust Optimization (DRO), a fundamental framework for enhancing the robustness and generalization of statistical learning and optimization. An effective ambiguity set for DRO must involve distributions…

Machine Learning · Computer Science 2026-02-10 Jiaqi Wen , Jianyi Yang

New resource mix, e.g., renewable resources, are imposing operational complexities to modern power systems by intensifying uncertainty and variability in the system net load. This issue has motivated independent system operators (ISOs),…

Systems and Control · Electrical Eng. & Systems 2020-12-10 Mohammad Ghaljehei , Mojdeh Khorsand

The number of cancer cases per year is rapidly increasing worldwide. In radiation therapy (RT), radiation from linear accelerators is used to kill malignant tumor cells. Scheduling patients for RT is difficult both due to the numerous…

Optimization and Control · Mathematics 2023-03-21 Sara Frimodig , Per Enqvist , Jan Kronqvist

Integrative analysis of multiple datasets for estimating optimal individualized treatment rules (ITRs) can enhance decision efficiency. A central challenge is posterior shift, wherein the conditional distribution of potential outcomes given…

Machine Learning · Statistics 2026-03-09 Wenhai Cui , Wen Su , Xingqiu Zhao

Model-based design of experiments (MBDOE) is essential for efficient parameter estimation in nonlinear dynamical systems. However, conventional adaptive MBDOE requires costly posterior inference and design optimization between each…

Machine Learning · Statistics 2026-03-25 Arno Strouwen , Sebastian Micluţa-Câmpeanu

We propose a fast beam orientation selection method, based on deep neural networks (DNN), capable of developing a plan comparable to those by the state-of-the-art column generation method. The novelty of Our model lies in its supervised…

Medical Physics · Physics 2019-12-23 Azar Sadeghnejad Barkousaraie , Olalekan Ogunmolu , Steve Jiang , Dan Nguyen

Radiation therapy with carbon ions is a novel technique of cancer radiotherapy, applicable in particular to treating radioresistant tumours at difficult localisations. Therapy planning, where the medical physicist, following the medical…

Medical Physics · Physics 2014-10-07 Leszek Grzanka

Moment-based distributionally robust optimization (DRO) provides an optimization framework to integrate statistical information with traditional optimization approaches. Under this framework, one assumes that the underlying joint…

Optimization and Control · Mathematics 2023-11-01 Shiyi Jiang , Jianqiang Cheng , Kai Pan , Zuo-Jun Max Shen

Temporally modulated pulsed radiotherapy (TMPRT) delivers conventional fraction doses of radiation using temporally separated pulses of low doses (<30 cGy) yielding fraction-effective dose rates of around 6.7 cGy/min with the goal to…

Medical Physics · Physics 2026-01-13 Christian Velten , Adam Bayliss , Jiayi Huang , Wolfgang A. Tomé

In atomic, molecular, and nuclear physics, the method of complex coordinate rotation is a widely used theoretical tool for studying resonant states. Here, we propose a novel implementation of this method based on the gradient optimization…

Atomic Physics · Physics 2020-07-24 Zhi-Da Bai , Zhen-Xiang Zhong , Zong-Chao Yan , Ting-Yun Shi

Microbeam radiation therapy (MRT) utilizes coplanar synchrotron radiation beamlets and is a proposed treatment approach for several tumour diagnoses that currently have poor clinical treatment outcomes, such as gliosarcomas. Prescription…

Radiotherapy treatment planning is a complex and time-intensive process, often impacted by inter-planner variability and subjective decision-making. To address these challenges, we introduce Dose Optimization Language Agent (DOLA), an…

The field of portfolio selection is an active research topic, which combines elements and methodologies from various fields, such as optimization, decision analysis, risk management, data science, forecasting, etc. The modeling and…

Portfolio Management · Quantitative Finance 2020-10-28 A. Georgantas

In this paper knowledge based planning has been revolutionized via a novel mathematical model which converts three dimensional dose distribution (3D3) prediction to a clinical utilizable IMRT treatment plan. Presented model has benefited…

Optimization and Control · Mathematics 2022-06-14 Ali Yousefi , Saeedeh Ketabi , Iraj Abedi

Adaptive therapy is a dynamic cancer treatment protocol that updates (or "adapts") treatment decisions in anticipation of evolving tumor dynamics. This broad term encompasses many possible dynamic treatment protocols of patient-specific…

Radiation therapy is a critical component of cancer treatment. However, the delivery of radiation poses inherent challenges, particularly in minimizing radiation exposure to healthy organs surrounding the tumor site. One significant…

Optimization and Control · Mathematics 2024-01-22 Keshav Kumar K. , NVSL Narasimham

In this letter, we consider the multiple-input multiple-output (MIMO) radar waveform design in the presence of signal-dependent clutters and additive white Gaussian noise. By imposing the constant modulus constraint (CMC) and waveform…

Signal Processing · Electrical Eng. & Systems 2018-05-11 Chenglin Ren , Fan liu , Longfei Zhou , Jianming Zhou , Wu Luo , Shengzhi Yang

Robust topology optimization (RTO), as a class of topology optimization problems, identifies a design with the best average performance while reducing the response sensitivity to input uncertainties, e.g. load uncertainty. Solving RTO is…

Machine Learning · Computer Science 2024-08-22 Rini Jasmine Gladstone , Mohammad Amin Nabian , Vahid Keshavarzzadeh , Hadi Meidani
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