Browse > Methodology > AutoML > Hyperparameter Optimization

Hyperparameter Optimization

78 papers with code · Methodology
Subtask of AutoML

Leaderboards

No evaluation results yet. Help compare methods by submit evaluation metrics.

Latest papers with code

Extreme Algorithm Selection With Dyadic Feature Representation

29 Jan 2020alexandertornede/extreme_algorithm_selection

Algorithm selection (AS) deals with selecting an algorithm from a fixed set of candidate algorithms most suitable for a specific instance of an algorithmic problem, e. g., choosing solvers for SAT problems.

HYPERPARAMETER OPTIMIZATION META-LEARNING

0
29 Jan 2020

Scalable Hyperparameter Optimization with Lazy Gaussian Processes

https://ieeexplore.ieee.org/document/8950672 2020 cc-hpc-itwm/HPO_LazyGPR

Reducing its computational complexity from cubic to quadratic allows an efficient strong scaling of Bayesian Optimization while outperforming the previous approach regarding optimization accuracy.

GAUSSIAN PROCESSES HYPERPARAMETER OPTIMIZATION

7
16 Jan 2020

Scalable Hyperparameter Optimization with Lazy Gaussian Processes

https://ieeexplore.ieee.org/document/8950672 2020 cc-hpc-itwm/HPO_LazyGPR

Most machine learning methods require careful selection of hyper-parameters in order to train a high performing model with good generalization abilities.

GAUSSIAN PROCESSES HYPERPARAMETER OPTIMIZATION

7
09 Jan 2020

Meta-Surrogate Benchmarking for Hyperparameter Optimization

NeurIPS 2019 amzn/emukit

Despite the recent progress in hyperparameter optimization (HPO), available benchmarks that resemble real-world scenarios consist of a few and very large problem instances that are expensive to solve.

HYPERPARAMETER OPTIMIZATION

189
01 Dec 2019

Enabling hyperparameter optimization in sequential autoencoders for spiking neural data

NeurIPS 2019 snel-repo/lfads-cd

Our results should greatly extend the applicability of SAEs in extracting latent dynamics from sparse, multidimensional data, such as neural population spiking activity.

HYPERPARAMETER OPTIMIZATION

1
01 Dec 2019

Single Headed Attention RNN: Stop Thinking With Your Head

26 Nov 2019saattrupdan/scholarly

The leading approaches in language modeling are all obsessed with TV shows of my youth - namely Transformers and Sesame Street.

HYPERPARAMETER OPTIMIZATION LANGUAGE MODELLING

3
26 Nov 2019

FLO: Fast and Lightweight Hyperparameter Optimization for AutoML

12 Nov 2019Shmuelnaaman/Fast_Lightweight_Hyperparameter-Optimization-

FLO has a strong anytime performance and significantly outperforms Bayesian Optimization and random search for hyperparameter tuning on a large open source AutoML Benchmark.

HYPERPARAMETER OPTIMIZATION

1
12 Nov 2019

Auptimizer -- an Extensible, Open-Source Framework for Hyperparameter Tuning

6 Nov 2019LGE-ARC-AdvancedAI/auptimizer

Tuning machine learning models at scale, especially finding the right hyperparameter values, can be difficult and time-consuming.

HYPERPARAMETER OPTIMIZATION NEURAL ARCHITECTURE SEARCH

135
06 Nov 2019

Sym-parameterized Dynamic Inference for Mixed-Domain Image Translation

ICCV 2019 TimeLighter/pytorch-sym-parameter

Recent advances in image-to-image translation have led to some ways to generate multiple domain images through a single network.

HYPERPARAMETER OPTIMIZATION IMAGE-TO-IMAGE TRANSLATION

9
27 Oct 2019

Prior specification via prior predictive matching: Poisson matrix factorization and beyond

27 Oct 2019tkusmierczyk/bayesian_hyperparameters_matching

Hyperparameter optimization for machine learning models is typically carried out by some sort of cross-validation procedure or global optimization, both of which require running the learning algorithm numerous times.

HYPERPARAMETER OPTIMIZATION

1
27 Oct 2019