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Found 13 papers, 0 papers with code
VEnvision3D: A Synthetic Perception Dataset for 3D Multi-Task Model Research
Therefore, such a unique attribute can assist in exploring the potential for the multi-task model and even the foundation model without separate training methods.
Fin-QD: A Computational Design Framework for Soft Grippers: Integrating MAP-Elites and High-fidelity FEM
This work first discusses a significantly large design space (28 design parameters) for a finger-based soft gripper, including the rarely-explored design space of finger arrangement that is converted to various configurations to arrange individual soft fingers.
A Study of Fitness Gains in Evolving Finite State Machines
Among the wide variety of evolutionary computing models, Finite State Machines (FSMs) have several attractions for fundamental research.
Prior Information based Decomposition and Reconstruction Learning for Micro-Expression Recognition
To solve this issue, driven by the prior information that the category of ME can be inferred by the relationship between the actions of facial different components, this work designs a novel model that can conform to this prior information and learn ME movement features in an interpretable way.
Graph Representation Learning
Micro Expression Recognition
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Evolutionary Time-Use Optimization for Improving Children's Health Outcomes
We then investigate the performance of evolutionary algorithms to optimize time use for four individual health outcomes with hypothetical children with different day structures.
Evolutionary Algorithms for Limiting the Effect of Uncertainty for the Knapsack Problem with Stochastic Profits
We examine simple evolutionary algorithms and the use of heavy tail mutation and a problem-specific crossover operator for optimizing uncertain profits.
Heuristic Strategies for Solving Complex Interacting Large-Scale Stockpile Blending Problems
Besides, we introduce a multi-component fitness function for solving the large-scale stockpile blending problem which can maximize the volume of metal over the plan and maintain the balance between stockpiles according to the usage of metal.
Runtime Analysis of RLS and the (1+1) EA for the Chance-constrained Knapsack Problem with Correlated Uniform Weights
We perform runtime analysis of a randomized search algorithm (RSA) and a basic evolutionary algorithm (EA) for the chance-constrained knapsack problem with correlated uniform weights.
Heuristic Strategies for Solving Complex Interacting Stockpile Blending Problem with Chance Constraints
In this paper, we consider the uncertainty in material grades and introduce chance constraints that are used to ensure the constraints with high confidence.
Specific Single- and Multi-Objective Evolutionary Algorithms for the Chance-Constrained Knapsack Problem
We use this model in combination with the problem-specific crossover operator in multi-objective evolutionary algorithms to solve the problem.
Evolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives
In this paper, we consider the dynamic chance-constrained knapsack problem where the weight of each item is stochastic, the capacity constraint changes dynamically over time, and the objective is to maximize the total profit subject to the probability that total weight exceeds the capacity.
Agile Domain Adaptation
Because of the distribution shifts, different target samples have distinct degrees of difficulty in adaptation.
Evolutionary Algorithms for the Chance-Constrained Knapsack Problem
In the experiment section, we evaluate and compare the deterministic approaches and evolutionary algorithms on a wide range of instances.
