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08/29/2023
Unleashing the Potential of Spiking Neural Networks for Sequential Modeling with Contextual Embedding
The human brain exhibits remarkable abilities in integrating temporally ...
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08/25/2023
TC-LIF: A Two-Compartment Spiking Neuron Model for Long-term Sequential Modelling
The identification of sensory cues associated with potential opportuniti...
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07/14/2023
Long Short-term Memory with Two-Compartment Spiking Neuron
The identification of sensory cues associated with potential opportuniti...
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05/26/2023
A Hybrid Neural Coding Approach for Pattern Recognition with Spiking Neural Networks
The biological neural systems evolved to adapt to ecological environment...
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04/17/2023
A Scalable Test Problem Generator for Sequential Transfer Optimization
Sequential transfer optimization (STO), which aims to improve optimizati...
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04/08/2023
A Recommender System Approach for Very Large-scale Multiobjective Optimization
We define very large multi-objective optimization problems to be multiob...
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01/29/2023
EvoX: A Distributed GPU-accelerated Library towards Scalable Evolutionary Computation
During the past decades, evolutionary computation (EC) has demonstrated ...
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12/28/2022
Differentiable Search of Accurate and Robust Architectures
Deep neural networks (DNNs) are found to be vulnerable to adversarial at...
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12/17/2022
An Evolutionary Multitasking Algorithm with Multiple Filtering for High-Dimensional Feature Selection
Recently, evolutionary multitasking (EMT) has been successfully used in ...
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08/08/2022
Neural Architecture Search as Multiobjective Optimization Benchmarks: Problem Formulation and Performance Assessment
The ongoing advancements in network architecture design have led to rema...
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07/03/2022
Architecture Augmentation for Performance Predictor Based on Graph Isomorphism
Neural Architecture Search (NAS) can automatically design architectures ...
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06/23/2022
A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization
Recent decades have witnessed remarkable advancements in multiobjective ...
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05/20/2022
Balancing Exploration and Exploitation for Solving Large-scale Multiobjective Optimization via Attention Mechanism
Large-scale multiobjective optimization problems (LSMOPs) refer to optim...
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10/15/2021
Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve Optimization
Evolutionary transfer multiobjective optimization (ETMO) has been becomi...
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07/16/2021
Solving Large-Scale Multi-Objective Optimization via Probabilistic Prediction Model
The main feature of large-scale multi-objective optimization problems (L...
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05/22/2021
Principled Design of Translation, Scale, and Rotation Invariant Variation Operators for Metaheuristics
In the past three decades, a large number of metaheuristics have been pr...
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02/23/2021
Multi-Space Evolutionary Search for Large-Scale Optimization
In recent years, to improve the evolutionary algorithms used to solve op...
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01/08/2021
Manifold Interpolation for Large-Scale Multi-Objective Optimization via Generative Adversarial Networks
Large-scale multiobjective optimization problems (LSMOPs) are characteri...
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12/24/2020
Evolutionary Gait Transfer of Multi-Legged Robots in Complex Terrains
Robot gait optimization is the task of generating an optimal control tra...
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08/31/2020
BiLO-CPDP: Bi-Level Programming for Automated Model Discovery in Cross-Project Defect Prediction
Cross-Project Defect Prediction (CPDP), which borrows data from similar ...
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07/02/2020
Progressive Tandem Learning for Pattern Recognition with Deep Spiking Neural Networks
Spiking neural networks (SNNs) have shown clear advantages over traditio...
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05/11/2020
Synaptic Learning with Augmented Spikes
Traditional neuron models use analog values for information representati...
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05/05/2020
Constructing Accurate and Efficient Deep Spiking Neural Networks with Double-threshold and Augmented Schemes
Spiking neural networks (SNNs) are considered as a potential candidate t...
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05/02/2020
Towards Efficient Processing and Learning with Spikes: New Approaches for Multi-Spike Learning
Spikes are the currency in central nervous systems for information trans...
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02/08/2020
Understanding the Automated Parameter Optimization on Transfer Learning for CPDP: An Empirical Study
Data-driven defect prediction has become increasingly important in softw...
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11/19/2019
Deep Spiking Neural Networks for Large Vocabulary Automatic Speech Recognition
Artificial neural networks (ANN) have become the mainstream acoustic mod...
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10/20/2019
Online Bagging for Anytime Transfer Learning
Transfer learning techniques have been widely used in the reality that i...
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10/19/2019
Evolutionary Dynamic Multi-objective Optimization Via Regression Transfer Learning
Dynamic multi-objective optimization problems (DMOPs) remain a challenge...
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10/19/2019
Solving Dynamic Multi-objective Optimization Problems Using Incremental Support Vector Machine
The main feature of the Dynamic Multi-objective Optimization Problems (D...
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10/19/2019
Solving dynamic multi-objective optimization problems via support vector machine
Dynamic Multi-objective Optimization Problems (DMOPs) refer to optimizat...
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10/11/2019
Evolutionary Multi-Objective Optimization Driven by Generative Adversarial Networks (GANs)
Recently, more and more works have proposed to drive evolutionary algori...
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07/10/2019
Evolutionary Multi-Objective Optimization Driven by Generative Adversarial Networks
Recently, more and more works have proposed to drive evolutionary algori...
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07/02/2019
A Hybrid Learning Rule for Efficient and Rapid Inference with Spiking Neural Networks
The emerging neuromorphic computing (NC) architectures have shown compel...
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07/02/2019
A Tandem Learning Rule for Efficient and Rapid Inference on Deep Spiking Neural Networks
Emerging neuromorphic computing (NC) architectures have shown compelling...
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02/04/2019
Robust Environmental Sound Recognition with Sparse Key-point Encoding and Efficient Multi-spike Learning
The capability for environmental sound recognition (ESR) can determine t...
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01/30/2019
Which Surrogate Works for Empirical Performance Modelling? A Case Study with Differential Evolution
It is not uncommon that meta-heuristic algorithms contain some intrinsic...
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04/30/2018
A Multi-State Diagnosis and Prognosis Framework with Feature Learning for Tool Condition Monitoring
In this paper, a multi-state diagnosis and prognosis (MDP) framework is ...
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04/28/2018
A Cost-Sensitive Deep Belief Network for Imbalanced Classification
Imbalanced data with a skewed class distribution are common in many real...
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06/08/2017