most citedParallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives

4 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Hierarchical Visual Categories Modeling: A Joint Representation Learning and Density Estimation Framework for Out-of-Distribution Detection

Jinglun Li, Xinyu Zhou, Pinxue Guo +4

Detecting out-of-distribution inputs for visual recognition models has become critical in safe deep learning. This paper proposes a novel hierarchical visual category modeling sche…

physics.ao-ph2024

Parametric Sensitivities of a Wind-driven Baroclinic Ocean Using Neural Surrogates

Yixuan Sun, Elizabeth Cucuzzella, Steven Brus +6

Numerical models of the ocean and ice sheets are crucial for understanding and simulating the impact of greenhouse gases on the global climate. Oceanic processes affect phenomena s…

cs.LG2024

Streamlining Ocean Dynamics Modeling with Fourier Neural Operators: A Multiobjective Hyperparameter and Architecture Optimization Approach

Yixuan Sun, Ololade Sowunmi, Romain Egele +3

Training an effective deep learning model to learn ocean processes involves careful choices of various hyperparameters. We leverage the advanced search algorithms for multiobjectiv…

physics.ao-ph2023

Surrogate Neural Networks to Estimate Parametric Sensitivity of Ocean Models

Yixuan Sun, Elizabeth Cucuzzella, Steven Brus +5

Modeling is crucial to understanding the effect of greenhouse gases, warming, and ice sheet melting on the ocean. At the same time, ocean processes affect phenomena such as hurrica…

cs.LG20234 cited

Parallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives

Romain Egele, Tyler Chang, Yixuan Sun +2

Machine learning (ML) methods offer a wide range of configurable hyperparameters that have a significant influence on their performance. While accuracy is a commonly used performan…