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GraphScope Flex: LEGO-like Graph Computing Stack
Furthermore, GraphScope Flex accomplishes up to a 2, 400X performance gain in real-world applications, demonstrating its proficiency across a wide range of graph computing scenarios with increased effectiveness.
Distributed, Parallel, and Cluster Computing Databases
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization
In many real-world scenarios, decision makers seek to efficiently optimize multiple competing objectives in a sample-efficient fashion.
HiFrames: High Performance Data Frames in a Scripting Language
Data frames in scripting languages are essential abstractions for processing structured data.
Distributed, Parallel, and Cluster Computing
DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network
To this end, a novel framework termed Mathematical Architecture Design for Deep CNN (DeepMAD) is proposed to design high-performance CNN models in a principled way.
Ranked #1 on
Neural Architecture Search
on ImageNet
Manipulator Differential Kinematics: Part 2: Acceleration and Advanced Applications
This is the second and final article on the tutorial on manipulator differential kinematics.
Robotics
Certifiably Globally Optimal Extrinsic Calibration from Per-Sensor Egomotion
We present a certifiably globally optimal algorithm for determining the extrinsic calibration between two sensors that are capable of producing independent egomotion estimates.
Robotics
P6: A Declarative Language for Integrating Machine Learning in Visual Analytics
We present P6, a declarative language for building high performance visual analytics systems through its support for specifying and integrating machine learning and interactive visualization methods.
Exact and Approximation Algorithms for Sparse PCA
Sparse PCA (SPCA) is a fundamental model in machine learning and data analytics, which has witnessed a variety of application areas such as finance, manufacturing, biology, healthcare.
The application of adaptive minimum match k-nearest neighbors to identify at-risk students in health professions education
AMMKNN generates a predicted PANCE score for each student, one year before they are scheduled to take the exam.
Numerical Analysis of the Causal Action Principle in Low Dimensions
Discrete Dirac spheres are introduced as candidates for minimizers for large $m$ in the cases $n=1, f=2$ and $n=2, f=4$.
Mathematical Physics Numerical Analysis Mathematical Physics Numerical Analysis
