Results 51 to 60 of about 246,254 (290)
Clinical applications of machine learning algorithms: beyond the black box
To maximise the clinical benefits of machine learning algorithms, we need to rethink our approach to explanation, argue David Watson and ...
David Watson +6 more
semanticscholar +1 more source
A Review of Population-Based Metaheuristics for Large-Scale Black-Box Global Optimization—Part I
Scalability of optimization algorithms is a major challenge in coping with the ever-growing size of optimization problems in a wide range of application areas from high-dimensional machine learning to complex large-scale engineering problems.
M. Omidvar, Xiaodong Li, Xin Yao
semanticscholar +1 more source
Opening up the Black Box of Sensor Processing Algorithms through New Visualizations
Vehicles and platforms with multiple sensors connect people in multiple roles with different responsibilities to scenes of interest. For many of these human–sensor systems there are a variety of algorithms that transform, select, and filter the sensor ...
Alexander M. Morison, David D. Woods
doaj +1 more source
Black-Box Algorithms for Sampling from Continuous Distributions
For generating non-uniform random variates, black-box algorithms are powerful tools that allow drawing samples from large classes of distri- butions. We give an overview of the design principles of such methods and show that they have advantages compared to specialized algorithms even for standard distributions, e.g., the marginal generation times are ...
Hörmann, Wolfgang, Leydold, Josef
openaire +5 more sources
Structural insights and therapeutic targets in Acinetobacter baumannii capsule biosynthesis
Hypervirulent KL49 A. baumannii's capsular polysaccharide contains the nonulosonic acid 8‐epi‐Leg5,7Ac2, synthesized by epimerization via ElaA, ElaB, and ElaC. Crystal structures of ElaA, ElaB, and ElaC reveal their role in CMP‐Leg5,7Ac2 synthesis and regioselective C8 epimerization.
Woo Cheol Lee +7 more
wiley +1 more source
Adversarial examples generated by perturbing raw data with carefully designed, imperceptible noise have emerged as a primary security threat to artificial intelligence systems.
Zhijian Chen +3 more
doaj +1 more source
Black-Box Randomized Reductions in Algorithmic Mechanism Design [PDF]
We give the first black-box reduction from approximation algorithms to truthful approximation mechanisms for a non-trivial class of multi-parameter problems. Specifically, we prove that every welfare-maximization problem that admits a fully polynomial-time approximation scheme (FPTAS) and can be encoded as a packing problem also admits a truthful-in ...
Shaddin Dughmi, Tim Roughgarden
openaire +1 more source
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems
Performance complementarity of solvers available to tackle black-box optimization problems gives rise to the important task of algorithm selection (AS). Automated AS approaches can help replace tedious and labor-intensive manual selection, and have already shown promising performance in various optimization domains.
Kostovska, Ana +5 more
openaire +5 more sources
Peripheral lysosomes recruit PLEKHG3 to focal adhesions and restrain protrusion dynamics
Proximity‐dependent labeling at the LAMTOR complex revealed the Rho GEF PLEKHG3 as a lysosome‐proximal protein directing the study toward the influence of lysosome positioning on actin dynamics and cell motility. We show that PLEKHG3 colocalizes with lysosomes at focal adhesion sites and observe that forced peripheral dispersion of lysosomes hinders ...
Rainer Ettelt +8 more
wiley +1 more source
Trusting AI made decisions in healthcare by making them explainable
Objectives In solving the trust issues surrounding machine learning algorithms whose reasoning cannot be understood, advancements can be made toward the integration of machine learning algorithms into mHealth applications.
Bojan Žlahtič +6 more
doaj +1 more source

