Papers
53 papers found
ABLATOR: Robust Horizontal-Scaling of Machine Learning Ablation Experiments
Iordanis Fostiropoulos, Laurent Itti
AlphaD3M: An Open-Source AutoML Library for Multiple ML Tasks
Roque Lopez, Raoni Lourenco, Remi Rampin et al.
AutoGluon–TimeSeries: AutoML for Probabilistic Time Series Forecasting
Oleksandr Shchur, Ali Caner Turkmen, Nick Erickson et al.
AutoRL Hyperparameter Landscapes
Aditya Mohan, Carolin Benjamins, Konrad Wienecke et al.
Balanced Mixture of Supernets for Learning the CNN Pooling Architecture
Mehraveh Javan Roshtkhari, Matthew Toews, Marco Pedersoli
Better Practices for Domain Adaptation
Linus Ericsson, Da Li, Timothy Hospedales
CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure
Lennart Oswald Purucker, Joeran Beel
Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection
Yihang Shen, Carl Kingsford
Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference
Chi Wang, Xueqing Liu, Ahmed Hassan Awadallah
Exploiting Network Compressibility and Topology in Zero-Cost NAS
Lichuan Xiang, Rosco Hunter, Minghao Xu et al.
Learning Activation Functions for Sparse Neural Networks
Mohammad Loni, Aditya Mohan, Mehdi Asadi et al.
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts
Diederick Vermetten, Furong Ye, Thomas Bäck et al.
MEOW - Multi-Objective Evolutionary Weapon Detection
Daniel Dimanov, Colin Singleton, Shahin Rostami et al.
Meta-Learning for Fast Model Recommendation in Unsupervised Multivariate Time Series Anomaly Detection
Jose Manuel Navarro, Alexis Huet, Dario Rossi
Multi-Predict: Few Shot Predictors For Efficient Neural Architecture Search
Yash Akhauri, Mohamed S Abdelfattah
Neural Architecture Search for Visual Anomaly Segmentation
Tommie Kerssies, Joaquin Vanschoren
“No Free Lunch” in Neural Architectures? A Joint Analysis of Expressivity, Convergence, and Generalization
Wuyang Chen, Wei Huang, Zhangyang Wang
Optimal Resource Allocation for Early Stopping-based Neural Architecture Search Methods
Marcel Aach, Eray Inanc, Rakesh Sarma et al.
Poisson Process for Bayesian Optimization
Xiaoxing Wang, Jiaxing Li, Chao Xue et al.
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization
Ana Kostovska, Gjorgjina Cenikj, Diederick Vermetten et al.
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML
Lennart Oswald Purucker, Lennart Schneider, Marie Anastacio et al.
Searching for Fairer Machine Learning Ensembles
Michael Feffer, Martin Hirzel, Samuel C Hoffman et al.
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
Carolin Benjamins, Elena Raponi, Anja Jankovic et al.
Symbolic Explanations for Hyperparameter Optimization
Sarah Segel, Helena Graf, Alexander Tornede et al.
A Tree-Structured Multi-Task Model Recommender
Lijun Zhang, Xiao Liu, Hui Guan