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Global optimization of Lipschitz functions

7 March 2017

Papers citing "Global optimization of Lipschitz functions"

47 / 47 papers shown

Title
Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants Fares Fourati Salma Kharrat Vaneet Aggarwal Mohamed-Slim Alouini 118 0 0 06 Feb 2025
Boosting Soft Q-Learning by Bounding Jacob Adamczyk Volodymyr Makarenko Stas Tiomkin Rahul V. Kulkarni OffRL 73 2 0 26 Jun 2024
Task Facet Learning: A Structured Approach to Prompt Optimization Gurusha Juneja Gautam Jajoo Nagarajan Natarajan Hua Li Jian Jiao Amit Sharma 105 10 0 15 Jun 2024
Beyond Trend Following: Deep Learning for Market Trend Prediction Fernando Berzal Alberto Garcia 80 0 0 10 Jun 2024
On Safety in Safe Bayesian Optimization Christian Fiedler Johanna Menn Lukas Kreisköther Sebastian Trimpe 79 11 0 19 Mar 2024
Parameter-Free Algorithms for Performative Regret Minimization under Decision-Dependent Distributions Sungwoo Park Junyeop Kwon Byeongnoh Kim Suhyun Chae Jeeyong Lee Dabeen Lee 85 0 0 23 Feb 2024
Stein Boltzmann Sampling: A Variational Approach for Global Optimization Gaetan Serré Argyris Kalogeratos Nicolas Vayatis OT 82 1 0 07 Feb 2024
Wave Physics-informed Matrix Factorizations Harsha Vardhan Tetali J. Harley B. Haeffele 79 1 0 21 Dec 2023
A unified weighting framework for evaluating nearest neighbour classification O. Lenz Henri Bollaert Chris Cornelis 46 2 0 28 Nov 2023
Lipschitz Interpolation: Non-parametric Convergence under Bounded Stochastic Noise J. Huang Stephen J. Roberts Jan-Peter Calliess 28 0 0 10 Oct 2023
Max-Sliced Mutual Information Dor Tsur Ziv Goldfeld Kristjan Greenewald 72 10 0 28 Sep 2023
Robustness Analysis of Continuous-Depth Models with Lagrangian Techniques Sophie A. Neubauer Radu Grosu 62 0 0 23 Aug 2023
Certified Multi-Fidelity Zeroth-Order Optimization Étienne de Montbrun Sébastien Gerchinovitz 88 1 0 02 Aug 2023
Efficient Lipschitzian Global Optimization of Hölder Continuous Multivariate Functions Kaan Gokcesu Hakan Gokcesu 28 0 0 24 Mar 2023
Multi-task neural networks by learned contextual inputs Anders T. Sandnes B. Grimstad O. Kolbjørnsen 51 2 0 01 Mar 2023
Global Optimization with Parametric Function Approximation Chong Liu Yu Wang 76 7 0 16 Nov 2022
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances Sloan Nietert Ritwik Sadhu Ziv Goldfeld Kengo Kato 89 40 0 17 Oct 2022
$1D$ to $nD$ : A Meta Algorithm for Multivariate Global Optimization via Univariate Optimizers Kaan Gokcesu Hakan Gokcesu 102 0 0 06 Sep 2022
Efficient Minimax Optimal Global Optimization of Lipschitz Continuous Multivariate Functions Kaan Gokcesu Hakan Gokcesu 44 3 0 06 Jun 2022
Combining Lipschitz and RBF Surrogate Models for High-dimensional Computationally Expensive Problems J. Kůdela R. Matousek 51 32 0 29 Apr 2022
Comparative analysis of machine learning methods for active flow control F. Pino Lorenzo Schena Jean Rabault M. A. Mendez 107 44 0 23 Feb 2022
Low Regret Binary Sampling Method for Efficient Global Optimization of Univariate Functions Kaan Gokcesu Hakan Gokcesu 51 11 0 18 Jan 2022
Cumulative Regret Analysis of the Piyavskii--Shubert Algorithm and Its Variants for Global Optimization Kaan Gokcesu Hakan Gokcesu 79 11 0 24 Aug 2021
Power of human-algorithm collaboration in solving combinatorial optimization problems Tapani Toivonen 47 1 0 25 Jul 2021
Wave-Informed Matrix Factorization with Global Optimality Guarantees Harsha Vardhan Tetali J. Harley B. Haeffele 62 1 0 19 Jul 2021
High-Dimensional Simulation Optimization via Brownian Fields and Sparse Grids Liang Ding Rui Tuo Xiaowei Zhang 71 3 0 19 Jul 2021
GoTube: Scalable Stochastic Verification of Continuous-Depth Models Sophie Gruenbacher Mathias Lechner Ramin Hasani Daniela Rus T. Henzinger S. Smolka Radu Grosu 68 17 0 18 Jul 2021
Query Attack by Multi-Identity Surrogates Sizhe Chen Zhehao Huang Qinghua Tao Xiaolin Huang AAML 86 4 0 31 May 2021
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure Samuel Kim Peter Y. Lu Charlotte Loh Jamie Smith Jasper Snoek M. Soljavcić BDL AI4CE 395 17 0 23 Apr 2021
Training Deep Neural Networks via Branch-and-Bound Yuanwei Wu Ziming Zhang Guanghui Wang ODL 57 0 0 05 Apr 2021
Discrepancy-Based Active Learning for Domain Adaptation Antoine de Mathelin Francois Deheeger Mathilde Mougeot Nicolas Vayatis 107 24 0 05 Mar 2021
Optimised one-class classification performance O. Lenz Daniel Peralta Chris Cornelis 55 4 0 04 Feb 2021
Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates François Bachoc Tommaso Cesari Sébastien Gerchinovitz 73 10 0 03 Feb 2021
On The Verification of Neural ODEs with Stochastic Guarantees Sophie Gruenbacher Ramin Hasani Mathias Lechner J. Cyranka S. Smolka Radu Grosu 115 34 0 16 Dec 2020
Continuum-Armed Bandits: A Function Space Perspective Shashank Singh 82 10 0 15 Oct 2020
Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits A. Akhavan Massimiliano Pontil Alexandre B. Tsybakov 71 41 0 14 Jun 2020
Regret analysis of the Piyavskii-Shubert algorithm for global Lipschitz optimization Clément Bouttier Tommaso Cesari Mélanie Ducoffe Sébastien Gerchinovitz 61 15 0 06 Feb 2020
FRaZ: A Generic High-Fidelity Fixed-Ratio Lossy Compression Framework for Scientific Floating-point Data Robert Underwood Sheng Di Jon C. Calhoun Franck Cappello 35 38 0 17 Jan 2020
Global optimization using Sobol indices Alexandre Janon 32 1 0 12 Jun 2019
Graduated Optimization of Black-Box Functions Weijia Shao C. Geißler F. Sivrikaya 56 2 0 04 Jun 2019
Derivative-Free Global Optimization Algorithms: Bayesian Method and Lipschitzian Approaches Jiawei Zhang 32 1 0 19 Apr 2019
A Framework of Transfer Learning in Object Detection for Embedded Systems Ioannis Athanasiadis Panagiotis G. Mousouliotis L. Petrou ObjD 49 14 0 12 Nov 2018
Combining Bayesian Optimization and Lipschitz Optimization Mohamed Osama Ahmed Sharan Vaswani Mark Schmidt 61 22 0 10 Oct 2018
A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption Peter L. Bartlett Victor Gabillon Michal Valko 50 33 0 01 Oct 2018
Predictive Local Smoothness for Stochastic Gradient Methods Jun Yu Li Hongfu Liu Bineng Zhong Yue Wu Y. Fu ODL 41 1 0 23 May 2018
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates Yining Wang Sivaraman Balakrishnan Aarti Singh 67 25 0 22 Mar 2018
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning Ziming Zhang Yuanwei Wu Guanghui Wang ODL 65 28 0 19 Nov 2017