Search Results
Neural Architecture Search using Property Guided Synthesis
To enable this approach, we also propose a novel efficient synthesis procedure, which accepts a set of promising program properties, and returns a satisfying neural architecture.
Benchmarking optimization algorithms for auto-tuning GPU kernels
However, the discrete, and non-convex nature of the search space creates a challenging optimization problem.
Distributed, Parallel, and Cluster Computing Graphics Performance
Meta-Optimizing Semantic Evolutionary Search
I present MOSES (meta-optimizing semantic evolutionary search), a new probabilistic modeling (estimation of distribution) approach to program evolution.
Automated Unit Test Generation for Python
(2) What is the influence of incomplete type information and dynamic typing on the problem of automated test generation?
Software Engineering
Deep Learning in Neural Networks: An Overview
In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning.
MTFuzz: Fuzzing with a Multi-Task Neural Network
The compact embedding can be used to guide the mutation process effectively by focusing most of the mutations on the parts of the embedding where the gradient is high.
Software Engineering
IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics
An R programming interface is provided for users preferring to have a finer control over the implemented functionalities.
Interaction-Transformation Evolutionary Algorithm for Symbolic Regression
The Interaction-Transformation (IT) is a new representation for Symbolic Regression that restricts the search space into simpler, but expressive, function forms.
A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros
However, defective levels with illegal patterns may be generated due to the violation of constraints for level design.
Automatically Proving Mathematical Theorems with Evolutionary Algorithms and Proof Assistants
Mathematical theorems are human knowledge able to be accumulated in the form of symbolic representation, and proving theorems has been considered intelligent behavior.
