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08/27/2023
Neural Influence Estimator: Towards Real-time Solutions to Influence Blocking Maximization
Real-time solutions to the influence blocking maximization (IBM) problem...
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06/26/2023
Data-Driven Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications
The multiple-choice knapsack problem (MCKP) is a classic NP-hard combina...
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06/20/2023
Statistical Tests for Replacing Human Decision Makers with Algorithms
This paper proposes a statistical framework with which artificial intell...
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06/19/2023
Perturbation-Based Two-Stage Multi-Domain Active Learning
In multi-domain learning (MDL) scenarios, high labeling effort is requir...
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05/18/2023
Large Language Models can be Guided to Evade AI-Generated Text Detection
Large Language Models (LLMs) have demonstrated exceptional performance i...
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05/04/2023
Multi-Domain Learning From Insufficient Annotations
Multi-domain learning (MDL) refers to simultaneously constructing a mode...
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03/12/2023
MetaUE: Model-based Meta-learning for Underwater Image Enhancement
The challenges in recovering underwater images are the presence of diver...
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02/06/2023
Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend
Word-level textual adversarial attacks have achieved striking performanc...
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01/31/2023
Enabling surrogate-assisted evolutionary reinforcement learning via policy embedding
Evolutionary Reinforcement Learning (ERL) that applying Evolutionary Alg...
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11/23/2022
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles
Attack Ensemble (AE), which combines multiple attacks together, provides...
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09/22/2022
How Good Is Neural Combinatorial Optimization?
Traditional solvers for tackling combinatorial optimization (CO) problem...
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08/18/2022
Disentangled Contrastive Learning for Social Recommendation
Social recommendations utilize social relations to enhance the represent...
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08/01/2022
GANDSE: Generative Adversarial Network based Design Space Exploration for Neural Network Accelerator Design
With the popularity of deep learning, the hardware implementation platfo...
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06/11/2022
Defending Adversarial Examples by Negative Correlation Ensemble
The security issues in DNNs, such as adversarial examples, have attracte...
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06/04/2022
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack
Deep neural networks are vulnerable to adversarial examples, even in the...
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04/10/2022
Near-Optimal Trajectory Design and Restoration Areas Allocation for UAV-Enabled Grassland Restoration
Grassland restoration is a critical means to safeguard grassland ecologi...
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12/23/2021
Training Quantized Deep Neural Networks via Cooperative Coevolution
This work considers a challenging Deep Neural Network (DNN) quantization...
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11/02/2021
HydraText: Multi-objective Optimization for Adversarial Textual Attack
The field of adversarial textual attack has significantly grown over the...
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09/06/2021
Efficient Combinatorial Optimization for Word-level Adversarial Textual Attack
Over the past few years, various word-level textual attack approaches ha...
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08/20/2021
Deep Sequence Modeling: Development and Applications in Asset Pricing
We predict asset returns and measure risk premia using a prominent techn...
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08/05/2021
Active Reinforcement Learning over MDPs
The past decade has seen the rapid development of Reinforcement Learning...
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06/25/2021
Multi-Domain Active Learning: A Comparative Study
Building classifiers on multiple domains is a practical problem in the r...
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05/30/2021
Robust Dynamic Network Embedding via Ensembles
Dynamic Network Embedding (DNE) has recently attracted considerable atte...
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04/20/2021
Multi-objective Evolutionary Algorithms are Generally Good: Maximizing Monotone Submodular Functions over Sequences
Evolutionary algorithms (EAs) are general-purpose optimization algorithm...
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01/20/2021
A New Knowledge Gradient-based Method for Constrained Bayesian Optimization
Black-box problems are common in real life like structural design, drug ...
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12/28/2020
A Survey on Neural Network Interpretability
Along with the great success of deep neural networks, there is also grow...
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11/12/2020
Memetic Search for Vehicle Routing with Simultaneous Pickup-Delivery and Time Windows
The vehicle routing problem with simultaneous pickup-delivery and time w...
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10/15/2020
Interpreting Deep Learning Model Using Rule-based Method
Deep learning models are favored in many research and industry areas and...
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09/08/2020
Evolutionary Reinforcement Learning via Cooperative Coevolutionary Negatively Correlated Search
Evolutionary algorithms (EAs) have been successfully applied to optimize...
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08/05/2020
GloDyNE: Global Topology Preserving Dynamic Network Embedding
Learning low-dimensional topological representation of a network in dyna...
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07/01/2020
Few-shots Parameter Tuning via Co-evolution
Generalization, i.e., the ability of addressing problem instances that a...
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11/19/2019
On Performance Estimation in Automatic Algorithm Configuration
Over the last decade, research on automated parameter tuning, often refe...
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10/16/2019
Negatively Correlated Search as a Parallel Exploration Search Strategy
Parallel exploration is a key to a successful search. The recently propo...
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07/31/2019
Competitive Co-evolution for Dynamic Constrained Optimisation
Dynamic constrained optimisation problems (DCOPs) widely exist in the re...
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07/27/2019
DynWalks: Global Topology and Recent Changes Awareness Dynamic Network Embedding
Learning topological representation of a network in dynamic environments...
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06/17/2019
Running Time Analysis of the (1+1)-EA for Robust Linear Optimization
Evolutionary algorithms (EAs) have found many successful real-world appl...
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05/05/2019
Decision Making with Machine Learning and ROC Curves
The Receiver Operating Characteristic (ROC) curve is a representation of...
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02/03/2019
Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions
Stochastic gradient descent (SGD) is a popular and efficient method with...
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12/06/2018
A Parallel Divide-and-Conquer based Evolutionary Algorithm for Large-scale Optimization
Large-scale optimization problems that involve thousands of decision var...
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11/28/2018
Attributed Network Embedding for Incomplete Structure Information
An attributed network enriches a pure network by encoding a part of wide...
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10/16/2018
Maximizing Monotone DR-submodular Continuous Functions by Derivative-free Optimization
In this paper, we study the problem of monotone (weakly) DR-submodular c...
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10/11/2018
Analysis of Noisy Evolutionary Optimization When Sampling Fails
In noisy evolutionary optimization, sampling is a common strategy to dea...
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04/17/2018
Automatic Construction of Parallel Portfolios via Explicit Instance Grouping
Simultaneously utilizing several complementary solvers is a simple yet e...
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11/20/2017
Maximizing Non-monotone/Non-submodular Functions by Multi-objective Evolutionary Algorithms
Evolutionary algorithms (EAs) are a kind of nature-inspired general-purp...
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11/02/2017
Running Time Analysis of the (1+1)-EA for OneMax and LeadingOnes under Bit-wise Noise
In many real-world optimization problems, the objective function evaluat...
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08/03/2017
Preselection via Classification: A Case Study on Evolutionary Multiobjective Optimization
In evolutionary algorithms, a preselection operator aims to select the p...
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06/12/2017
Evolutionary Multitasking for Single-objective Continuous Optimization: Benchmark Problems, Performance Metric, and Baseline Results
In this report, we suggest nine test problems for multi-task single-obje...
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03/29/2017
Experience-based Optimization: A Coevolutionary Approach
This paper studies improving solvers based on their past solving experie...
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03/18/2017
An Adaptive Framework to Tune the Coordinate Systems in Evolutionary Algorithms
In the evolutionary computation research community, the performance of m...
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03/11/2016