13 papers · ranked by Valyu relevance
Raaghav Ramani, Steve Shkoller
We develop a fast-running smooth adaptive meshing (SAM) algorithm for dynamic curvilinear mesh generation, which is based on a fast solution strategy of the time-dependent Monge-Ampère (MA) equation, det ∇ψ(x, t) = G○ψ(x, t). The novelty of our approach is a new so-called perturbation formulation of MA, which…
Tommaso Costa, Donato Liloia, Franco Cauda, Peter Fox + 3 more
Activation likelihood estimation (ALE) is among the most used algorithms to perform neuroimaging meta-analysis. Since its first implementation, several thresholding procedures had been proposed, all referred to the frequentist framework, returning a rejection criterion for the null hypothesis according to the critical…
Ran Wang, Weiquan Huang, Junyu Wu, Chen Chen + 3 more
To address the rapid population diversity loss and premature convergence of the Artificial Lemming Algorithm (ALA) in complex optimization problems, this paper proposes an Improved Artificial Lemming Algorithm (IALA) with multi-strategy enhancements inspired by lemming behavior. First, a non-uniform mutation operator…
Tommaso Costa, Donato Liloia, Franco Cauda, Peter T. Fox + 3 more
'Francesca Dalla Mutta' 'Sergio Duca' 'Jordi Manuello'] Activation likelihood estimation (ALE) is among the most used algorithms to perform neuroimaging meta-analysis. Since its first implementation, several thresholding procedures had been proposed, all referred to the frequentist framework, returning a rejection…
Chitu Okoli
Accumulated Local Effects (ALE) is a model-agnostic approach for global explanations of the results of black-box machine learning (ML) algorithms. There are at least three challenges with conducting statistical inference based on ALE: ensuring the reliability of ALE analyses, especially in the context of small…
Lennart Frahm, Theodore D. Satterthwaite, Peter T. Fox, Robert Langner + 1 more
Activation likelihood estimation (ALE) meta-analysis has been applied to structural neuroimaging data since long, but up to now, any systematic assessment of the algorithm’s behavior, power and sensitivity has been based on simulations using functional neuroimaging databases as their foundation. Here, we aimed to…
Hani Z. Girgis
Tools for accurately clustering biological sequences are among the most important tools in computational biology. Two pioneering tools for clustering sequences are CD-HIT and UCLUST, both of which are fast and consume reasonable amounts of memory; however, there is a big room for improvement in terms of cluster…
Yuki Imajuku, Horie, Kohki, Yoichi Iwata + 4 more
How well do AI systems perform in algorithm engineering for hard optimization problems in domains such as package-delivery routing, crew scheduling, factory production planning, and power-grid balancing? We introduce ALE-Bench, a new benchmark for evaluating AI systems on score-based algorithmic programming contests.…
Lennart Frahm, Kaustubh R. Patil, Theodore D. Satterthwaite, Peter T. Fox + 2 more
Activation Likelihood Estimation (ALE) employs voxel- or cluster-level family-wise error (vFWE or cFWE) correction or threshold-free cluster enhancement (TFCE) to counter false positives due to multiple comparisons. These corrections utilize Monte-Carlo simulations to approximate a null distribution of spatial…
Payam Ghiaci, Paula Jouhten, Nikolay Martyushenko, Helena Roca-Mesa + 10 more
Adaptive Laboratory Evolution (ALE) of microbes can improve the efficiency of sustainable industrial processes important to the global economy, but chance and genetic background effects often lead to suboptimal outcomes. Here we report an ALE platform to circumvent these flaws through parallelized clonal evolution at…
Yunhao Yang, Andrew B. Whinston
This paper gives a detailed review of reinforcement learning in combinatorial optimization, introduces the history of combinatorial optimization starting in the 1960s, and compares it with the reinforcement learning algorithms in recent years. We explicitly look at a famous combinatorial problem known as the Traveling…
Kengo Shibata, Bahaaeddin Attaallah, Xin-You Tai, William Trender + 5 more
Title: Summary Background Autoimmune limbic encephalitis (ALE) is a neurological disease characterised by inflammation of the limbic regions of the brain, mediated by pathogenic autoantibodies. Because cognitive deficits persist following acute treatment of ALE, the accurate assessment of long-term cognitive outcomes…
Yuyong Tan, Jianfeng Wang, Bin Wang, Yongquan Zhou
The intelligent optimization algorithm has become a key tool in complex and intertwined engineering and science fields. However, with the increasing complexity of the problem and the rapid expansion of the data scale, the performance of the algorithm has been challenged unprecedentedly. The artificial lemming algorithm…