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05/27/2023
Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs
A concept-based classifier can explain the decision process of a deep le...
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04/07/2023
CMA-ES with Learning Rate Adaptation: Can CMA-ES with Default Population Size Solve Multimodal and Noisy Problems?
The covariance matrix adaptation evolution strategy (CMA-ES) is one of t...
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03/28/2023
Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min–Max Optimization and its Application to Berthing Control Tasks
In this study, we consider a continuous min–max optimization problem min...
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01/31/2023
Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning
We investigate policy transfer using image-to-semantics translation to m...
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12/13/2022
Collision probability reduction method for tracking control in automatic docking / berthing using reinforcement learning
Automation of berthing maneuvers in shipping is a pressing issue as the ...
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11/29/2022
Adaptive Scenario Subset Selection for Worst-Case Optimization and its Application to Well Placement Optimization
In this study, we consider simulation-based worst-case optimization prob...
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11/07/2022
Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification
In the field of reinforcement learning, because of the high cost and ris...
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09/26/2022
Convergence rate of the (1+1)-evolution strategy on locally strongly convex functions with lipschitz continuous gradient and their monotonic transformations
Evolution strategy (ES) is one of promising classes of algorithms for bl...
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09/22/2022
CAMRI Loss: Improving Recall of a Specific Class without Sacrificing Accuracy
In real-world applications of multi-class classification models, misclas...
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04/06/2022
Black-Box Min–Max Continuous Optimization Using CMA-ES with Worst-case Ranking Approximation
In this study, we investigate the problem of min-max continuous optimiza...
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04/06/2022
Monotone Improvement of Information-Geometric Optimization Algorithms with a Surrogate Function
A surrogate function is often employed to reduce the number of objective...
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03/29/2022
A Two-phase Framework with a Bézier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization
This paper proposes a two-phase framework with a Bézier simplex-based in...
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09/09/2021
Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation
We aim to explain a black-box classifier with the form: `data X is class...
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05/25/2021
Saddle Point Optimization with Approximate Minimization Oracle and its Application to Robust Berthing Control
We propose an approach to saddle point optimization relying only on an o...
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04/13/2021
Level Generation for Angry Birds with Sequential VAE and Latent Variable Evolution
Video game level generation based on machine learning (ML), in particula...
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03/29/2021
Saddle Point Optimization with Approximate Minimization Oracle
A major approach to saddle point optimization min_xmax_y f(x, y) is a gr...
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03/02/2021
Convergence Rate of the (1+1)-Evolution Strategy with Success-Based Step-Size Adaptation on Convex Quadratic Functions
The (1+1)-evolution strategy (ES) with success-based step-size adaptatio...
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12/13/2020
Warm Starting CMA-ES for Hyperparameter Optimization
Hyperparameter optimization (HPO), formulated as black-box optimization ...
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12/11/2020
AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment
Neural architecture search (NAS) is an approach for automatically design...
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09/18/2020
Global Linear Convergence of Evolution Strategies on More Than Smooth Strongly Convex Functions
Evolution strategies (ESs) are zero-order stochastic black-box optimizat...
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08/24/2020
Statistically Significant Pattern Mining with Ordinal Utility
Statistically significant patterns mining (SSPM) is an essential and cha...
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11/20/2019
Generate (non-software) Bugs to Fool Classifiers
In adversarial attacks intended to confound deep learning models, most s...
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05/21/2019
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
High sensitivity of neural architecture search (NAS) methods against the...
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05/14/2019
Diagonal Acceleration for Covariance Matrix Adaptation Evolution Strategies
We introduce an acceleration for covariance matrix adaptation evolution ...
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11/02/2018
Ranking Based Linear Constraint Handling Method with Adaptive Penalty
A novel linear constraint handling technique for the covariance matrix a...
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09/18/2018
Parameterless Stochastic Natural Gradient Method for Discrete Optimization and its Application to Hyper-Parameter Optimization for Neural Network
Black box discrete optimization (BBDO) appears in wide range of engineer...
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05/31/2018
Sample Reuse via Importance Sampling in Information Geometric Optimization
In this paper we propose a technique to reduce the number of function ev...
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02/09/2018
Drift Theory in Continuous Search Spaces: Expected Hitting Time of the (1+1)-ES with 1/5 Success Rule
This paper explores the use of the standard approach for proving runtime...
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01/23/2018
Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling
Deep neural networks (DNNs) are powerful machine learning models and hav...
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06/07/2017
Fast Eigen Decomposition for Low-Rank Matrix Approximation
In this paper we present an efficient algorithm to compute the eigen dec...
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11/16/2012
Objective Improvement in Information-Geometric Optimization
Information-Geometric Optimization (IGO) is a unified framework of stoch...
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06/21/2012
Convergence of the Continuous Time Trajectories of Isotropic Evolution Strategies on Monotonic C^2-composite Functions
The Information-Geometric Optimization (IGO) has been introduced as a un...
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06/04/2012
Theoretical foundation for CMA-ES from information geometric perspective
This paper explores the theoretical basis of the covariance matrix adapt...
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04/18/2012