Results 1 to 10 of about 322,722 (107)
Genetic Epidemiology, 2016 Developments in genome‐wide association studies and the increasing availability of summary genetic association data have made application of Mendelian randomization relatively straightforward.
J. Bowden +3 more
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Local Texture Estimator for Implicit Representation Function [PDF]
Computer Vision and Pattern Recognition, 2021 Recent works with an implicit neural function shed light on representing images in arbitrary resolution. However, a standalone multi-layer perceptron shows limited performance in learning high-frequency components.
Jaewon Lee, Kyong Hwan Jin
semanticscholar +1 more source
VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator [PDF]
IEEE Transactions on robotics, 2017 One camera and one low-cost inertial measurement unit (IMU) form a monocular visual-inertial system (VINS), which is the minimum sensor suite (in size, weight, and power) for the metric six degrees-of-freedom (DOF) state estimation.
Tong Qin, Peiliang Li, S. Shen
semanticscholar +1 more source
Multiobjective Tree-Structured Parzen Estimator
Journal of Artificial Intelligence Research, 2022 Practitioners often encounter challenging real-world problems that involve a simultaneous optimization of multiple objectives in a complex search space. To address these problems, we propose a practical multiobjective Bayesian optimization algorithm.
Yoshihiko Ozaki +4 more
semanticscholar +1 more source
Multiobjective tree-structured parzen estimator for computationally expensive optimization problems
Annual Conference on Genetic and Evolutionary Computation, 2020 Practitioners often encounter computationally expensive multiobjective optimization problems to be solved in a variety of real-world applications. On the purpose of challenging these problems, we propose a new surrogate-based multiobjective optimization ...
Yoshihiko Ozaki +3 more
semanticscholar +1 more source
Learning the MMSE Channel Estimator [PDF]
IEEE Transactions on Signal Processing, 2017 We present a method for estimating conditionally Gaussian random vectors with random covariance matrices, which uses techniques from the field of machine learning.
David Neumann, Thomas Wiese, W. Utschick
semanticscholar +1 more source
The Triple Difference Estimator
Social Science Research Network, 2020 Triple difference has become a widely used estimator in empirical work. A close reading of articles in top economics journals reveals that the use of the estimator to a large extent rests on intuition.
A. Olden, Jarle Møen
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A Simple Sampler for the Horseshoe Estimator [PDF]
IEEE Signal Processing Letters, 2015 In this note we derive a simple Bayesian sampler for linear regression with the horseshoe hierarchy. A new interpretation of the horseshoe model is presented, and extensions to logistic regression and alternative hierarchies, such as horseshoe+, are ...
E. Makalic, D. Schmidt
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The Horseshoe+ Estimator of Ultra-Sparse Signals [PDF]
, 2015 We propose a new prior for ultra-sparse signal detection that we term the "horseshoe+ prior." The horseshoe+ prior is a natural extension of the horseshoe prior that has achieved success in the estimation and detection of sparse signals and has been ...
A. Bhadra +3 more
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Modified ridge‐type estimator to combat multicollinearity: Application to chemical data
Journal of Chemometrics, 2019 The Linear regression model is one of the most widely used models in different fields of study. The most popularly used estimation technique is the ordinary least squares estimator.
A. Lukman +3 more
semanticscholar +1 more source