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Practical Bayesian Optimization of Machine Learning Algorithms

Practical Bayesian Optimization of Machine Learning Algorithms

Jasper Snoek
Hugo Larochelle
Ryan P. Adams
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Papers citing "Practical Bayesian Optimization of Machine Learning Algorithms"

47 / 47 papers shown
Title
BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL
BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL
Yu-Heng Hung
Kai-Jie Lin
Yu-Heng Lin
Chien-Yi Wang
Cheng Sun
Ping-Chun Hsieh
26
0
0
28 May 2025
OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization
OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization
Meher Bhaskar Madiraju
Meher Sai Preetam Madiraju
67
0
0
25 May 2025
Bayesian Optimization for Enhanced Language Models: Optimizing Acquisition Functions
Bayesian Optimization for Enhanced Language Models: Optimizing Acquisition Functions
Zishuo Bao
Yibo Liu
Changyutao Qiu
88
0
0
22 May 2025
Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints
Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints
Peter Röseler
Oliver Schaudt
Helmut Berg
Christian Bauckhage
Matthias Koch
100
0
0
09 May 2025
Decentralized Collective World Model for Emergent Communication and Coordination
Decentralized Collective World Model for Emergent Communication and Coordination
Kentaro Nomura
Tatsuya Aoki
Tadahiro Taniguchi
Takato Horii
86
1
0
04 Apr 2025
Tuning-Free Structured Sparse PCA via Deep Unfolding Networks
Tuning-Free Structured Sparse PCA via Deep Unfolding Networks
Long Chen
Xianchao Xiu
360
0
0
28 Feb 2025
TSKANMixer: Kolmogorov-Arnold Networks with MLP-Mixer Model for Time Series Forecasting
TSKANMixer: Kolmogorov-Arnold Networks with MLP-Mixer Model for Time Series Forecasting
Young-Chae Hong
Bei Xiao
Yangho Chen
AI4TS
88
1
0
25 Feb 2025
NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance
NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance
Raphael T. Husistein
Markus Reiher
Marco Eckhoff
190
1
0
20 Feb 2025
Bayesian Optimization by Kernel Regression and Density-based Exploration
Bayesian Optimization by Kernel Regression and Density-based Exploration
Tansheng Zhu
Hongyu Zhou
Ke Jin
Xusheng Xu
Qiufan Yuan
Lijie Ji
330
0
0
10 Feb 2025
Adaptive Learning-based Model Predictive Control Strategy for Drift Vehicles
Adaptive Learning-based Model Predictive Control Strategy for Drift Vehicles
Bei Zhou
Cheng Hu
Jun Zeng
Zhouheng Li
Johannes Betz
Lei Xie
Hongye Su
96
2
0
07 Feb 2025
B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning
B-FPGM: Lightweight Face Detection via Bayesian-Optimized Soft FPGM Pruning
Nikolaos Kaparinos
Vasileios Mezaris
CVBM
93
0
0
28 Jan 2025
Co-Learning Bayesian Optimization
Co-Learning Bayesian Optimization
Zhendong Guo
Yew-Soon Ong
Tiantian He
Haitao Liu
117
2
0
23 Jan 2025
Deep Learning-Based Identification of Inconsistent Method Names: How Far Are We?
Deep Learning-Based Identification of Inconsistent Method Names: How Far Are We?
Taiming Wang
Yuxia Zhang
Lin Jiang
Yi Tang
Guangjie Li
Hui Liu
137
1
0
22 Jan 2025
Information-theoretic Bayesian Optimization: Survey and Tutorial
Information-theoretic Bayesian Optimization: Survey and Tutorial
Eduardo C. Garrido-Merchán
111
1
0
22 Jan 2025
Multi-Objective Hyperparameter Selection via Hypothesis Testing on Reliability Graphs
Multi-Objective Hyperparameter Selection via Hypothesis Testing on Reliability Graphs
Amirmohammad Farzaneh
Osvaldo Simeone
280
0
0
22 Jan 2025
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index
Qian Xie
Raul Astudillo
P. Frazier
Ziv Scully
Alexander Terenin
132
2
0
17 Jan 2025
Persistent Homology for Structural Characterization in Disordered Systems
Persistent Homology for Structural Characterization in Disordered Systems
An Wang
Li Zou
93
1
0
21 Nov 2024
Residual Deep Gaussian Processes on Manifolds
Residual Deep Gaussian Processes on Manifolds
Kacper Wyrwal
Andreas Krause
Viacheslav Borovitskiy
BDL
76
0
0
31 Oct 2024
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
Taiwo A. Adebiyi
Bach Do
Ruda Zhang
152
2
0
29 Oct 2024
Sequential Large Language Model-Based Hyper-parameter Optimization
Sequential Large Language Model-Based Hyper-parameter Optimization
Kanan Mahammadli
Seyda Ertekin
117
5
0
27 Oct 2024
AgentForge: A Flexible Low-Code Platform for Reinforcement Learning Agent Design
AgentForge: A Flexible Low-Code Platform for Reinforcement Learning Agent Design
Francisco Erivaldo Fernandes Junior
Antti Oulasvirta
354
0
0
25 Oct 2024
Cliqueformer: Model-Based Optimization with Structured Transformers
Cliqueformer: Model-Based Optimization with Structured Transformers
J. Kuba
Pieter Abbeel
Sergey Levine
OffRL
AI4CE
91
2
0
17 Oct 2024
Adaptive Active Inference Agents for Heterogeneous and Lifelong Federated Learning
Adaptive Active Inference Agents for Heterogeneous and Lifelong Federated Learning
Anastasiya Danilenka
Alireza Furutanpey
Víctor Casamayor Pujol
Boris Sedlak
Anna Lackinger
M. Ganzha
M. Paprzycki
Schahram Dustdar
72
1
0
09 Oct 2024
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
Xinxing Shi
Thomas Baldwin-McDonald
Mauricio A. Álvarez
91
0
0
01 Jul 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization
Jacob O. Tørring
Carl Hvarfner
Luigi Nardi
Magnus Sjalander
78
1
0
24 Jun 2024
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
J. Lin
Shreyas Padhy
Bruno Mlodozeniec
Javier Antorán
José Miguel Hernández-Lobato
57
2
0
28 May 2024
VIEW: Visual Imitation Learning with Waypoints
VIEW: Visual Imitation Learning with Waypoints
Ananth Jonnavittula
Sagar Parekh
Dylan P. Losey
SSL
100
10
0
27 Apr 2024
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
Dawei Zhan
64
5
0
18 Apr 2024
Global Safe Sequential Learning via Efficient Knowledge Transfer
Global Safe Sequential Learning via Efficient Knowledge Transfer
Cen-You Li
Olaf Duennbier
Marc Toussaint
Barbara Rakitsch
Christoph Zimmer
70
2
0
22 Feb 2024
Explainable Bayesian Optimization
Explainable Bayesian Optimization
Tanmay Chakraborty
Christin Seifert
Christian Wirth
107
5
0
24 Jan 2024
Multi-Stage Optimized Machine Learning Framework for Network Intrusion Detection
Multi-Stage Optimized Machine Learning Framework for Network Intrusion Detection
MohammadNoor Injadat
Abdallah Moubayed
Ali Bou Nassif
Abdallah Shami
32
164
0
09 Aug 2020
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning
Sijia Liu
Pin-Yu Chen
B. Kailkhura
Gaoyuan Zhang
A. Hero III
P. Varshney
59
228
0
11 Jun 2020
Model-Size Reduction for Reservoir Computing by Concatenating Internal States Through Time
Model-Size Reduction for Reservoir Computing by Concatenating Internal States Through Time
Yusuke Sakemi
K. Morino
T. Leleu
Kazuyuki Aihara
46
20
0
11 Jun 2020
Adaptation Strategies for Automated Machine Learning on Evolving Data
Adaptation Strategies for Automated Machine Learning on Evolving Data
B. Celik
Joaquin Vanschoren
38
54
0
09 Jun 2020
Building a COVID-19 Vulnerability Index
Building a COVID-19 Vulnerability Index
David DeCaprio
J. Gartner
Thadeus Burgess
Kristian Garcia
Sarthak Kothari
S. Sayed
C. McCall
41
144
0
16 Mar 2020
QTIP: Quick simulation-based adaptation of Traffic model per Incident Parameters
QTIP: Quick simulation-based adaptation of Traffic model per Incident Parameters
Inon Peled
R. Kamalakar
Carlos Lima Azevedo
Francisco Câmara Pereira
31
4
0
09 Mar 2020
Corruption-Tolerant Gaussian Process Bandit Optimization
Corruption-Tolerant Gaussian Process Bandit Optimization
Ilija Bogunovic
Andreas Krause
Jonathan Scarlett
56
52
0
04 Mar 2020
An effective algorithm for hyperparameter optimization of neural networks
An effective algorithm for hyperparameter optimization of neural networks
G. I. Diaz
Achille Fokoue
G. Nannicini
Horst Samulowitz
34
156
0
23 May 2017
A novel algorithmic approach to Bayesian Logic Regression
A novel algorithmic approach to Bayesian Logic Regression
A. Hubin
G. Storvik
F. Frommlet
48
16
0
22 May 2017
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
Luigi Acerbi
Wei Ji
41
219
0
11 May 2017
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria
Marko Jarvenpaa
Michael U. Gutmann
Aki Vehtari
Pekka Marttinen
113
41
0
20 Oct 2016
Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction
Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction
Weinan Zhang
Tianming Du
Jun Wang
AI4CE
38
492
0
11 Jan 2016
The Role of Context Types and Dimensionality in Learning Word Embeddings
The Role of Context Types and Dimensionality in Learning Word Embeddings
Oren Melamud
David McClosky
Siddharth Patwardhan
Joey Tianyi Zhou
70
123
0
05 Jan 2016
Multi-column Deep Neural Networks for Image Classification
Multi-column Deep Neural Networks for Image Classification
D. Ciresan
U. Meier
Jürgen Schmidhuber
106
3,935
0
13 Feb 2012
Convergence rates of efficient global optimization algorithms
Convergence rates of efficient global optimization algorithms
Adam D. Bull
92
641
0
18 Jan 2011
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
E. Brochu
Vlad M. Cora
Nando de Freitas
GP
111
2,437
0
12 Dec 2010
Slice sampling covariance hyperparameters of latent Gaussian models
Slice sampling covariance hyperparameters of latent Gaussian models
Iain Murray
Ryan P. Adams
92
232
0
04 Jun 2010