Results 241 to 250 of about 1,703,727 (282)
Artificial intelligence applications in adaptive radiotherapy-a narrative review. [PDF]
Transl Cancer ResChen ZF +6 more
europepmc +1 more source
Real-Time AI-Based Radiotherapy Planning for Nasopharyngeal Carcinoma: Development and Validation. [PDF]
Cyborg Bionic SystWang G +18 more
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
An online clustering algorithm
2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011This paper presents a new online clustering algorithm called SAFN which is used to learn continuously evolving clusters from non-stationary data. The SAFN uses a fast adaptive learning procedure to take into account variations over time. In non-stationary and multi-class environment, the SAFN learning procedure consists of five main stages: creation ...
Kan Li, Fenglan Yao, Ruipeng Liu
openaire +1 more source
ACM Computing Surveys, 2016
In online scenarios requests arrive over time, and each request must be serviced in an irrevocable manner before the next request arrives. Online algorithms with advice is an area of research where one attempts to measure how much knowledge of future requests is necessary to achieve a given performance level, as defined by the competitive ratio.
Joan Boyar +4 more
openaire +2 more sources
In online scenarios requests arrive over time, and each request must be serviced in an irrevocable manner before the next request arrives. Online algorithms with advice is an area of research where one attempts to measure how much knowledge of future requests is necessary to achieve a given performance level, as defined by the competitive ratio.
Joan Boyar +4 more
openaire +2 more sources
Online Pairwise Learning Algorithms
Neural Computation, 2016Pairwise learning usually refers to a learning task that involves a loss function depending on pairs of examples, among which the most notable ones are bipartite ranking, metric learning, and AUC maximization. In this letter we study an online algorithm for pairwise learning with a least-square loss function in an unconstrained setting of a reproducing
Yiming Ying, Ding-Xuan Zhou
openaire +2 more sources
Mathematical Programming, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +3 more sources
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +3 more sources
2023
Online algorithms are a rich area of research with widespread applications in scheduling, combinatorial optimization, and resource allocation problems. This lucid textbook provides an easy but rigorous introduction to online algorithms for graduate and senior undergraduate students.
openaire +1 more source
Online algorithms are a rich area of research with widespread applications in scheduling, combinatorial optimization, and resource allocation problems. This lucid textbook provides an easy but rigorous introduction to online algorithms for graduate and senior undergraduate students.
openaire +1 more source
Online Co-regularized Algorithms
2012We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks and a real world natural language processing dataset.
Tom de Ruijter +2 more
openaire +3 more sources
Equilibria of Online Scheduling Algorithms
Proceedings of the AAAI Conference on Artificial Intelligence, 2013We describe a model for competitive online scheduling algorithms. Two servers, each with a single observable queue, compete for customers. Upon arrival, each customer strategically chooses the queue with minimal expected wait time. Each scheduler wishes to maximize its number of customers, and can strategically select which scheduling ...
Itai Ashlagi +2 more
openaire +1 more source