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Found 5 papers, 2 papers with code
Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs
Our study investigates that a specific range of variable assignment rates (coverage) yields high-quality feasible solutions, where we suggest optimizing the coverage bridges the gap between the learning and MIP objectives.
Evaluating Out-of-Distribution Detectors Through Adversarial Generation of Outliers
A reliable evaluation method is essential for building a robust out-of-distribution (OOD) detector.
JORLDY: a fully customizable open source framework for reinforcement learning
Recently, Reinforcement Learning (RL) has been actively researched in both academic and industrial fields.
Adversarial Distributions Against Out-of-Distribution Detectors
As an outlier may deviate from the training distribution in unexpected ways, an ideal OOD detector should be able to detect all types of outliers.
A Statistical Manifold Framework for Point Cloud Data
The only requirement on the part of the user is the choice of a meaningful underlying probability distribution, which is more intuitive and natural to make than what is required in existing ad hoc formulations.
