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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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04/17/2023
Heterogeneous Domain Adaptation with Positive and Unlabeled Data
Heterogeneous unsupervised domain adaptation (HUDA) is the most challeng...
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04/02/2023
Instance-level Trojan Attacks on Visual Question Answering via Adversarial Learning in Neuron Activation Space
Malicious perturbations embedded in input data, known as Trojan attacks,...
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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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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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06/23/2022
Minimax Optimal Fair Regression under Linear Model
We investigate the minimax optimal error of a fair regression problem un...
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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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03/22/2022
Semi-Targeted Model Poisoning Attack on Federated Learning via Backward Error Analysis
Model poisoning attacks on federated learning (FL) intrude in the entire...
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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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08/20/2021
Application of Adversarial Examples to Physical ECG Signals
This work aims to assess the reality and feasibility of the adversarial ...
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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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03/02/2021
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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12/11/2020
AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment
Neural architecture search (NAS) is an approach for automatically design...
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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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08/22/2020
Seasonal-adjustment Based Feature Selection Method for Large-scale Search Engine Logs
Search engine logs have a great potential in tracking and predicting out...
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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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05/27/2019
Locally Differentially Private Minimum Finding
We investigate a problem of finding the minimum, in which each user has ...
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01/18/2019
Robust Watermarking of Neural Network with Exponential Weighting
Deep learning has been achieving top performance in many tasks. Since tr...
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11/28/2018
Minimax Optimal Additive Functional Estimation with Discrete Distribution
This paper addresses a problem of estimating an additive functional give...
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11/28/2018
General-to-Detailed GAN for Infrequent Class Medical Images
Deep learning has significant potential for medical imaging. However, si...
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10/28/2018
Robust Audio Adversarial Example for a Physical Attack
The success of deep learning in recent years has raised concerns about a...
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03/01/2018
Interval-based Prediction Uncertainty Bound Computation in Learning with Missing Values
The problem of machine learning with missing values is common in many ar...
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01/12/2018
Minimax Optimal Additive Functional Estimation with Discrete Distribution: Slow Divergence Speed Case
This paper addresses an estimation problem of an additive functional of ...
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10/20/2017
Differentially Private Empirical Risk Minimization with Input Perturbation
We propose a novel framework for the differentially private ERM, input p...
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06/06/2017
Recommendation with k-anonymized Ratings
Recommender systems are widely used to predict personalized preferences ...
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06/01/2016
Efficiently Bounding Optimal Solutions after Small Data Modification in Large-Scale Empirical Risk Minimization
We study large-scale classification problems in changing environments wh...
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02/15/2016
Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization
Privacy concern has been increasingly important in many machine learning...
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11/06/2015
Neutralized Empirical Risk Minimization with Generalization Neutrality Bound
Currently, machine learning plays an important role in the lives and ind...
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06/25/2015