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03/24/2023
Learning from Few Demonstrations with Frame-Weighted Motion Generation
Learning from Demonstration (LfD) aims to encode versatile skills from h...
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02/06/2021
Learning adaptive differential evolution algorithm from optimization experiences by policy gradient
Differential evolution is one of the most prestigious population-based s...
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11/03/2020
Amortized Variational Deep Q Network
Efficient exploration is one of the most important issues in deep reinfo...
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06/06/2020
Graph Neural Network Encoding for Community Detection in Attribute Networks
In this paper, we first propose a graph neural network encoding method f...
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03/10/2020
Learning to be Global Optimizer
The advancement of artificial intelligence has cast a new light on the d...
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03/04/2020
On Hyper-parameter Tuning for Stochastic Optimization Algorithms
This paper proposes the first-ever algorithmic framework for tuning hype...
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03/02/2020
Adaptive Structural Hyper-Parameter Configuration by Q-Learning
Tuning hyper-parameters for evolutionary algorithms is an important issu...
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11/12/2019
Multi-Objectivizing Sum-of-the-Parts Combinatorial Optimization Problems by Random Objective Decomposition
Multi-objectivization is a term used to describe strategies developed fo...
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11/12/2019
Novel Multi-Objectivization Approaches for the Sum-of-the-Parts Combinatorial Optimization Problems
Multi-objectivization is a term used to describe strategies developed fo...
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09/17/2019
Learning to Search for MIMO Detection
This paper proposes a novel learning to learn method, called learning to...
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05/14/2019
Homotopic Convex Transformation: A New Method to Smooth the Landscape of the Traveling Salesman Problem
This paper proposes a novel landscape smoothing method for the symmetric...
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12/11/2018
From Adaptive Kernel Density Estimation to Sparse Mixture Models
We introduce a balloon estimator in a generalized expectation-maximizati...
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06/16/2016