
LID 2020: The Learning from Imperfect Data Challenge Results
Learning from imperfect data becomes an issue in many industrial applica...
read it

DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors
Human activity recognition (HAR) in ubiquitous computing has been beginn...
read it

Realtime Human Activity Recognition Using Conditionally Parametrized Convolutions on Mobile and Wearable Devices
Recently, deep learning has represented an important research trend in h...
read it

MemoryAugmented Relation Network for FewShot Learning
Metricbased fewshot learning methods concentrate on learning transfera...
read it

Efficient convolutional neural networks with smaller filters for human activity recognition using wearable sensors
Recently, human activity recognition (HAR) has been beginning to adopt d...
read it

Incorporating Multiple Cluster Centers for MultiLabel Learning
Multilabel learning deals with the problem that each instance is associ...
read it

Sequential Weakly Labeled MultiActivity Recognition and Location on Wearable Sensors using Recurrent Attention Network
With the popularity and development of the wearable devices such as smar...
read it

Exploitation and Exploration Analysis of Elitist Evolutionary Algorithms: A Case Study
Known as two cornerstones of problem solving by search, exploitation and...
read it

Conditionally Learn to Pay Attention for Sequential Visual Task
Sequential visual task usually requires to pay attention to its current ...
read it

Unlimited Budget Analysis of Randomised Search Heuristics
Performance analysis of all kinds of randomised search heuristics is a r...
read it

Estimating Approximation Errors of Elitist Evolutionary Algorithms
When EAs are unlikely to locate precise global optimal solutions with sa...
read it

Attentionbased Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors
Unlike images or videos data which can be easily labeled by human being,...
read it

Average Convergence Rate of Evolutionary Algorithms II: Continuous Optimization
A good convergence metric must satisfy two requirements: feasible in cal...
read it

A Theoretical Framework of Approximation Error Analysis of Evolutionary Algorithms
In the empirical study of evolutionary algorithms, the solution quality ...
read it

A Blended Deep Learning Approach for Predicting User Intended Actions
User intended actions are widely seen in many areas. Forecasting these a...
read it

Multiobjective Optimization Differential Evolution Enhanced with Principle Component Analysis for Constrained Optimization
Multiobjective optimization evolutionary algorithms have been successful...
read it

New Methods of Studying Valley Fitness Landscapes
The word "valley" is a popular term used in intuitively describing fitne...
read it

An Analytic Expression of Relative Approximation Error for a Class of Evolutionary Algorithms
An important question in evolutionary computation is how good solutions ...
read it

Multiobjective Differential Evolution with Helper Functions for Constrained Optimization
Solving constrained optimization problems by multiobjective evolutionar...
read it

Average Convergence Rate of Evolutionary Algorithms
In evolutionary optimization, it is important to understand how fast evo...
read it

Analysis of Solution Quality of a Multiobjective Optimizationbased Evolutionary Algorithm for Knapsack Problem
Multiobjective optimisation is regarded as one of the most promising wa...
read it

Adaptive Stochastic Gradient Descent on the Grassmannian for Robust LowRank Subspace Recovery and Clustering
In this paper, we present GASG21 (Grassmannian Adaptive Stochastic Gradi...
read it

Performance Analysis on Evolutionary Algorithms for the Minimum Label Spanning Tree Problem
Some experimental investigations have shown that evolutionary algorithms...
read it

A Theoretical Assessment of Solution Quality in Evolutionary Algorithms for the Knapsack Problem
Evolutionary algorithms are well suited for solving the knapsack problem...
read it

A Novel Genetic Algorithm using Helper Objectives for the 01 Knapsack Problem
The 01 knapsack problem is a wellknown combinatorial optimisation prob...
read it

A Unified Markov Chain Approach to Analysing Randomised Search Heuristics
The convergence, convergence rate and expected hitting time play fundame...
read it

Average Drift Analysis and Population Scalability
This paper aims to study how the population size affects the computation...
read it

Iterative Grassmannian Optimization for Robust Image Alignment
Robust highdimensional data processing has witnessed an exciting develo...
read it

Geiringer Theorems: From Population Genetics to Computational Intelligence, Memory Evolutive Systems and Hebbian Learning
The classical Geiringer theorem addresses the limiting frequency of occu...
read it

A Further Generalization of the FinitePopulation Geiringerlike Theorem for POMDPs to Allow Recombination Over Arbitrary Set Covers
A popular current research trend deals with expanding the MonteCarlo tr...
read it

Combining Drift Analysis and Generalized Schema Theory to Design Efficient Hybrid and/or Mixed Strategy EAs
Hybrid and mixed strategy EAs have become rather popular for tackling va...
read it

Mixed Strategy May Outperform Pure Strategy: An Initial Study
In pure strategy metaheuristics, only one search strategy is applied fo...
read it

A hybrid artificial immune system and Self Organising Map for network intrusion detection
Network intrusion detection is the problem of detecting unauthorised use...
read it

On the Easiest and Hardest Fitness Functions
The hardness of fitness functions is an important research topic in the ...
read it

A Polynomial Time Approximation Scheme for a Single Machine Scheduling Problem Using a Hybrid Evolutionary Algorithm
Nowadays hybrid evolutionary algorithms, i.e, heuristic search algorithm...
read it

Pure Strategy or Mixed Strategy?
Mixed strategy EAs aim to integrate several mutation operators into a si...
read it

Online Robust Subspace Tracking from Partial Information
This paper presents GRASTA (Grassmannian Robust Adaptive Subspace Tracki...
read it

Novel Analysis of Population Scalability in Evolutionary Algorithms
Populationbased evolutionary algorithms (EAs) have been widely applied ...
read it

Toward an automaton Constraint for Local Search
We explore the idea of using finite automata to implement new constraint...
read it