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23 results on '"Yuan, Angela"'

1. Coalescing sets preserving cospectrality of graphs arising from block similarity matrices

Author

Mahamud, Sajid Bin, Butler, Steve, Graff, Hannah, Layman, Nick, Luck, Taylor, Jin, Jiah, Owen, Noah, and Yuan, Angela

Subjects
Mathematics - Combinatorics
Abstract

Coalescing involves gluing one or more rooted graphs onto another graph. Under specific conditions, it is possible to start with cospectral graphs that are coalesced in similar ways that will result in new cospectral graphs. We present a sufficient condition for this based on the block structure of similarity matrices, possibly with additional constraints depending on which type of matrix is being considered. The matrices considered in this paper include the adjacency, Laplacian, signless Laplacian, distance, and generalized distance matrix.

Published
2024

2. Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization

Author

Li, Chris Junchi, Yuan, Angela, Gidel, Gauthier, Gu, Quanquan, and Jordan, Michael I.

Subjects
Mathematics - Optimization and Control, Computer Science - Computer Science and Game Theory, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

We propose a new first-order optimization algorithm -- AcceleratedGradient-OptimisticGradient (AG-OG) Descent Ascent -- for separable convex-concave minimax optimization. The main idea of our algorithm is to carefully leverage the structure of the minimax problem, performing Nesterov acceleration on the individual component and optimistic gradient on the coupling component. Equipped with proper restarting, we show that AG-OG achieves the optimal convergence rate (up to a constant) for a variety of settings, including bilinearly coupled strongly convex-strongly concave minimax optimization (bi-SC-SC), bilinearly coupled convex-strongly concave minimax optimization (bi-C-SC), and bilinear games. We also extend our algorithm to the stochastic setting and achieve the optimal convergence rate in both bi-SC-SC and bi-C-SC settings. AG-OG is the first single-call algorithm with optimal convergence rates in both deterministic and stochastic settings for bilinearly coupled minimax optimization problems., Comment: 44 pages. This version matches the camera-ready that appeared at ICML 2023 under the same title

Published
2022

3. A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning

Author

Chen, Zixiang, Li, Chris Junchi, Yuan, Angela, Gu, Quanquan, and Jordan, Michael I.

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

With the increasing need for handling large state and action spaces, general function approximation has become a key technique in reinforcement learning (RL). In this paper, we propose a general framework that unifies model-based and model-free RL, and an Admissible Bellman Characterization (ABC) class that subsumes nearly all Markov Decision Process (MDP) models in the literature for tractable RL. We propose a novel estimation function with decomposable structural properties for optimization-based exploration and the functional eluder dimension as a complexity measure of the ABC class. Under our framework, a new sample-efficient algorithm namely OPtimization-based ExploRation with Approximation (OPERA) is proposed, achieving regret bounds that match or improve over the best-known results for a variety of MDP models. In particular, for MDPs with low Witness rank, under a slightly stronger assumption, OPERA improves the state-of-the-art sample complexity results by a factor of $dH$. Our framework provides a generic interface to design and analyze new RL models and algorithms.

Published
2022

12. The PROMISING Project: A Pilot Study to Improve Geriatric Care Through a Pharmacist-Led Psychotropic Stewardship Program.

Author

d'Amours, Marie, Ettis, Farah, Ginefri, Lauriane, Lim, Johnny, Lin Poo Yuan, Angela-Sinlan, Fontaine, Jennifer, Wazzan, Dana, Williamson, David, and Dagenais-Beaulé, Vincent

Subjects
PILOT projects, PSYCHIATRIC drugs, EVALUATION of human services programs, SCIENTIFIC observation, HOSPITAL health promotion programs, MEDICATION therapy management, QUALITY assurance, GERIATRIC nursing, DRUG monitoring, DESCRIPTIVE statistics, RESEARCH funding, LONGITUDINAL method
Abstract

Background and objective: Psychotropic medications are frequently prescribed during acute care, even in older patients. They represent a risk for inappropriate long-term use and increase the overall risk of morbidity and mortality in this population. Our project aimed to evaluate the feasibility of a psychotropic medication stewardship program led by pharmacists. Methods: We conducted a prospective, observational pilot study in patients aged 75 years and older, admitted to a surgical unit with at least one active prescription of a psychotropic medication (antipsychotic, benzodiazepine or non-benzodiazepine receptor agonist). Each psychotropic medication was assessed for potential deprescription, and if eligible, a recommendation from the stewardship pharmacist was made to the medical team. Results: Among 183 patients, 93.4% were eligible for a potential deprescription. A total of 298 prescriptions were evaluated by the stewardship pharmacists, of which 57.7% were antipsychotics, 22.8% were benzodiazepines and 19.5% were non-benzodiazepine receptor agonists. Most of the assessed prescriptions were started during current hospitalization (62.7%). The median time required for the intervention per patient was 17 min 30 s. The stewardship pharmacists made 192 suggestions for 258 eligible prescriptions, with 69.8% being deprescription recommendations. Of all the deprescription suggestions, 75.4% were accepted by the medical team and 84.8% of those accepted persisted at discharge. Conclusion: The implementation of a pharmacist-led psychotropic medication stewardship program on surgical units in our hospital is feasible and is a promising approach to improve geriatric care. [ABSTRACT FROM AUTHOR]

Published
2023
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17. Nesterov Meets Optimism: Rate-Optimal Optimistic-Gradient-Based Method for Stochastic Bilinearly-Coupled Minimax Optimization

Author

Li, Chris Junchi, Yuan, Angela, Gidel, Gauthier, and Jordan, Michael I.

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Computer Science and Game Theory, Statistics - Machine Learning, Optimization and Control (math.OC), FOS: Mathematics, Machine Learning (stat.ML), Mathematics - Optimization and Control, Computer Science and Game Theory (cs.GT), Machine Learning (cs.LG)
Abstract

We provide a novel first-order optimization algorithm for bilinearly-coupled strongly-convex-concave minimax optimization called the AcceleratedGradient OptimisticGradient (AG-OG). The main idea of our algorithm is to leverage the structure of the considered minimax problem and operates Nesterov's acceleration on the individual part and optimistic gradient on the coupling part of the objective. We motivate our method by showing that its continuous-time dynamics corresponds to an organic combination of the dynamics of optimistic gradient and of Nesterov's acceleration. By discretizing the dynamics we conclude polynomial convergence behavior in discrete time. Further enhancement of AG-OG with proper restarting allows us to achieve rate-optimal (up to a constant) convergence rates with respect to the conditioning of the coupling and individual parts, which results in the first single-call algorithm achieving improved convergence in the deterministic setting and rate-optimality in the stochastic setting under bilinearly coupled minimax problem sets., Comment: 37 pages

Published
2022
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18. Novel Program Offering Remote, Asynchronous Subspecialist Input in Thoracic Oncology: Early Experience and Insights Gained During the COVID-19 Pandemic

Author

Afsaneh Barzi, Yuan Angela Tan, Howard Jack West, Robert Parsley, Debra Wong, and Todd Sachs

Subjects
Male, medicine.medical_specialty, Lung Neoplasms, Concordance, Psychological intervention, Cohort Studies, Thoracic Oncology, Carcinoma, Non-Small-Cell Lung, medicine, Humans, Medical diagnosis, Lung cancer, Pandemics, Oncology (nursing), business.industry, Health Policy, Medical record, Cancer, COVID-19, Middle Aged, medicine.disease, Oncology, Emergency medicine, Cohort, Female, business
Abstract

PURPOSE: AccessHope is a program developed initially by City of Hope to provide remote subspecialist input on cancer care for patients as a supplemental benefit for specific payers or employers. The leading platform for this work has been an asynchronous model of review of medical records followed by a detailed assessment of past and current management along with discussion of potential future options in a report sent to the local oncologist. This summary describes an early period of development and growth of this service, focusing on cases of lung cancer, particularly during the COVID-19 pandemic. METHODS: Cases were primarily identified by a trigger list of cancer diagnoses that included non–small-cell lung cancer and small-cell lung cancer. After medical records were obtained, a summary narrative was provided to a thoracic oncology specialist who wrote a case review sent to the local physician, followed by a direct discussion with the recipient. We focused on feasibility as measured by case volumes, the rates of concordance between the subspecialist reviewer with the local team, and cost savings from recommended changes, using descriptive statistics. RESULTS: From April 2019 to November 2020, 110 cases were reviewed: 55% male, median age 62.5 years (range, 33-92 years); 82% non–small-cell lung cancer (12% stage I or II, 16% stage III, and 57% stage IV), and 17% small-cell lung cancer (4% limited and 14% extensive). Median turnaround time for report send-out was 5.0 days. The review agreed with local management in 79 (72%) cases and disagreed in 31 (28%) cases; notably, specific additional recommendations were associated with evidence-based anticipated improvements in efficacy in 76 cases (69%) and improvement in potential for cure in 14 cases (13%). Recommendations leading to cost savings were identified in 14 cases (13%), translating to a projected cost savings of $19,062 (USD) per patient for the entire cohort of patient cases reviewed. CONCLUSION: We demonstrate the feasibility of completing a rapid turnaround of cases of lung cancer either patient-initiated for review or prospectively triggered by diagnosis and stage. This program of asynchronous second opinions identified evidence-based management changes affecting current treatment in 28% and potential improvements to improve care in 92% of patients, along with cost savings realized by eliminating low-value interventions.

Published
2021

23. Characterization of Pain Associated With Pelvic Organ Prolapse: Is Surgery the Answer?

Author

Yuan AS, Ferrando CA, and Hickman LC

Abstract

Importance: Data on the incidence of pelvic organ prolapse (POP)-related pain, risk factors for its development, and treatment effects of surgery remain sparse., Objectives: The aims of the study were to evaluate the incidence and characteristics of POP-related pain in patients presenting with POP and assess the outcome of pain after surgery., Study Design: This was a retrospective study of patients presenting for initial evaluation of POP from May 2019 to May 2020. Using a standardized questionnaire, patients were asked "Do you have pain associated with your prolapse (not pressure or fullness)?" and to indicate pain severity and location(s). Patients who underwent surgery were asked postoperatively if their POP-related pain resolved. Patient and perioperative characteristics were obtained from the medical record and used to evaluate relationships between the presence and resolution of POP-related pain., Results: Of the 795 patients who met inclusion criteria, 106 (13.3%) reported POP-related pain. The mean age of all patients was 59.9 years, 38.1% had stage 3 or greater POP, and 52.1% were sexually active. Women with POP-related pain reported a median severity of 5 of 10. The most common pain locations were the vagina (46.6%), lower abdomen (27.4%), and back (9.6%). Fifty-seven women with pain (53.8%) underwent surgery, and 40 (70.2%) reported postoperative pain resolution. Of those who did not have resolution, pain improved or remained stable in severity. No patients reported worsening pain after surgery., Conclusions: Pain is a symptom experienced by more than 1 in 8 women presenting with POP, with 70% reporting resolution of their pain postoperatively., Competing Interests: The authors have declared they have no conflicts of interest., (Copyright © 2023 American Urogynecologic Society. All rights reserved.)

Published
2023
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