
Improving Entity Linking through Semantic Reinforced Entity Embeddings
Entity embeddings, which represent different aspects of each entity with...
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Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overview
Object pose detection and tracking has recently attracted increasing att...
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SVTNet: A Super LightWeight Network for Large Scale Place Recognition using Sparse Voxel Transformers
Point cloudbased large scale place recognition is fundamental for many ...
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Revisiting Deep Local Descriptor for Improved FewShot Classification
Fewshot classification studies the problem of quickly adapting a deep l...
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LID 2020: The Learning from Imperfect Data Challenge Results
Learning from imperfect data becomes an issue in many industrial applica...
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DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors
Human activity recognition (HAR) in ubiquitous computing has been beginn...
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Realtime Human Activity Recognition Using Conditionally Parametrized Convolutions on Mobile and Wearable Devices
Recently, deep learning has represented an important research trend in h...
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MemoryAugmented Relation Network for FewShot Learning
Metricbased fewshot learning methods concentrate on learning transfera...
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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...
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Incorporating Multiple Cluster Centers for MultiLabel Learning
Multilabel learning deals with the problem that each instance is associ...
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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...
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Exploitation and Exploration Analysis of Elitist Evolutionary Algorithms: A Case Study
Known as two cornerstones of problem solving by search, exploitation and...
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Conditionally Learn to Pay Attention for Sequential Visual Task
Sequential visual task usually requires to pay attention to its current ...
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Unlimited Budget Analysis of Randomised Search Heuristics
Performance analysis of all kinds of randomised search heuristics is a r...
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Estimating Approximation Errors of Elitist Evolutionary Algorithms
When EAs are unlikely to locate precise global optimal solutions with sa...
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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,...
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Average Convergence Rate of Evolutionary Algorithms II: Continuous Optimization
A good convergence metric must satisfy two requirements: feasible in cal...
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A Theoretical Framework of Approximation Error Analysis of Evolutionary Algorithms
In the empirical study of evolutionary algorithms, the solution quality ...
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A Blended Deep Learning Approach for Predicting User Intended Actions
User intended actions are widely seen in many areas. Forecasting these a...
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Multiobjective Optimization Differential Evolution Enhanced with Principle Component Analysis for Constrained Optimization
Multiobjective optimization evolutionary algorithms have been successful...
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New Methods of Studying Valley Fitness Landscapes
The word "valley" is a popular term used in intuitively describing fitne...
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An Analytic Expression of Relative Approximation Error for a Class of Evolutionary Algorithms
An important question in evolutionary computation is how good solutions ...
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Multiobjective Differential Evolution with Helper Functions for Constrained Optimization
Solving constrained optimization problems by multiobjective evolutionar...
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Average Convergence Rate of Evolutionary Algorithms
In evolutionary optimization, it is important to understand how fast evo...
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Analysis of Solution Quality of a Multiobjective Optimizationbased Evolutionary Algorithm for Knapsack Problem
Multiobjective optimisation is regarded as one of the most promising wa...
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Adaptive Stochastic Gradient Descent on the Grassmannian for Robust LowRank Subspace Recovery and Clustering
In this paper, we present GASG21 (Grassmannian Adaptive Stochastic Gradi...
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Performance Analysis on Evolutionary Algorithms for the Minimum Label Spanning Tree Problem
Some experimental investigations have shown that evolutionary algorithms...
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A Theoretical Assessment of Solution Quality in Evolutionary Algorithms for the Knapsack Problem
Evolutionary algorithms are well suited for solving the knapsack problem...
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A Novel Genetic Algorithm using Helper Objectives for the 01 Knapsack Problem
The 01 knapsack problem is a wellknown combinatorial optimisation prob...
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A Unified Markov Chain Approach to Analysing Randomised Search Heuristics
The convergence, convergence rate and expected hitting time play fundame...
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Average Drift Analysis and Population Scalability
This paper aims to study how the population size affects the computation...
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Iterative Grassmannian Optimization for Robust Image Alignment
Robust highdimensional data processing has witnessed an exciting develo...
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Geiringer Theorems: From Population Genetics to Computational Intelligence, Memory Evolutive Systems and Hebbian Learning
The classical Geiringer theorem addresses the limiting frequency of occu...
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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...
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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...
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Mixed Strategy May Outperform Pure Strategy: An Initial Study
In pure strategy metaheuristics, only one search strategy is applied fo...
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A hybrid artificial immune system and Self Organising Map for network intrusion detection
Network intrusion detection is the problem of detecting unauthorised use...
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On the Easiest and Hardest Fitness Functions
The hardness of fitness functions is an important research topic in the ...
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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...
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Pure Strategy or Mixed Strategy?
Mixed strategy EAs aim to integrate several mutation operators into a si...
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Online Robust Subspace Tracking from Partial Information
This paper presents GRASTA (Grassmannian Robust Adaptive Subspace Tracki...
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Novel Analysis of Population Scalability in Evolutionary Algorithms
Populationbased evolutionary algorithms (EAs) have been widely applied ...
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Toward an automaton Constraint for Local Search
We explore the idea of using finite automata to implement new constraint...
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