Results 71 to 80 of about 12,418,444 (305)
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications
Abstract In this study, we have developed an incremental machine learning (ML) method that efficiently obtains the optimal model when a small number of instances or features are added or removed. This problem holds practical importance in model selection, such as cross-validation (CV) and feature selection.
Hanada, Hiroyuki +3 more
openaire +4 more sources
Nonconvex Robust Low-Rank Matrix Recovery [PDF]
In this paper we study the problem of recovering a low-rank matrix from a number of random linear measurements that are corrupted by outliers taking arbitrary values. We consider a nonsmooth nonconvex formulation of the problem, in which we explicitly enforce the low-rank property of the solution by using a factored representation of the matrix ...
Li, Xiao +3 more
openaire +2 more sources
ABSTRACT Background The Improving Population Outcomes for Renal Tumours of childhood (IMPORT) is a prospective clinical observational study capturing detailed demographic and outcome data on children and young people diagnosed with renal tumours in the United Kingdom and the Republic of Ireland.
Naomi Ssenyonga +56 more
wiley +1 more source
Dynamic modeling of exhaust emission from a 600 MW once-through reheat down-fired boiler
The increasing integration of clean energy sources into the grid has required coal-fired power plants to frequently adjust their output to keep up with demand.
Chen Han +8 more
doaj +1 more source
Correlation Clustering with Low-Rank Matrices
Correlation clustering is a technique for aggregating data based on qualitative information about which pairs of objects are labeled 'similar' or 'dissimilar.' Because the optimization problem is NP-hard, much of the previous literature focuses on ...
Arthur D. +7 more
core +1 more source
Probabilistic Low-Rank Multitask Learning
In this paper, we consider the problem of learning multiple related tasks simultaneously with the goal of improving the generalization performance of individual tasks. The key challenge is to effectively exploit the shared information across multiple tasks as well as preserve the discriminative information for each individual task.
Yu Kong, Ming Shao, Kang Li, Yun Fu
openaire +2 more sources
ABSTRACT Introduction We developed MedSupport, a multilevel medication adherence intervention designed to address root barriers to medication adherence. This study sought to explore the feasibility and acceptability of the MedSupport intervention strategies to support a future full‐scale randomized controlled trial.
Elizabeth G. Bouchard +8 more
wiley +1 more source
ABSTRACT Background/Objectives Osteosarcoma is a radioresistant tumor that may benefit from stereotactic body radiation therapy (SBRT) for locoregional control in metastatic/recurrent disease. We report institutional practice patterns, outcomes, toxicity, and failures in osteosarcoma patients treated with SBRT.
Jenna Kocsis +13 more
wiley +1 more source
Low-rank Matrix Completion using Alternating Minimization
Alternating minimization represents a widely applicable and empirically successful approach for finding low-rank matrices that best fit the given data. For example, for the problem of low-rank matrix completion, this method is believed to be one of the ...
Jain, Prateek +2 more
core +1 more source
Lifestyle Behaviors and Cardiotoxic Treatment Risks in Adult Childhood Cancer Survivors
ABSTRACT Background Higher doses of anthracyclines and heart‐relevant radiotherapy increase cardiovascular disease (CVD) risk. This study assessed CVD and CVD risk factors among adult childhood cancer survivors (CCSs) across cardiotoxic treatment risk groups and examined associations between lifestyle behaviors and treatment risks.
Ruijie Li +6 more
wiley +1 more source

