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Learning Vehicle Routing Problems using Policy Optimisation
Deep reinforcement learning (DRL) has been used to learn effective heuri...
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Divide and Learn: A Divide and Conquer Approach for Predict+Optimize
The predict+optimize problem combines machine learning ofproblem coeffic...
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Representing and Denoising Wearable ECG Recordings
Modern wearable devices are embedded with a range of noninvasive biomark...
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Learning to Optimise General TSP Instances
The Travelling Salesman Problem (TSP) is a classical combinatorial optim...
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Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors
This paper investigates the Cyber-Physical behavior of users in a large ...
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MurTree: Optimal Classification Trees via Dynamic Programming and Search
Decision tree learning is a widely used approach in machine learning, fa...
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Less is More: Rejecting Unreliable Reviews for Product Question Answering
Promptly and accurately answering questions on products is important for...
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An Ambient-Physical System to Infer Concentration in Open-plan Workplace
One of the core challenges in open-plan workspaces is to ensure a good l...
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Flight Delay Prediction using Airport Situational Awareness Map
The prediction of flight delays plays a significantly important role for...
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Alternative Blockmodelling
Many approaches have been proposed to discover clusters within networks....
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Approximating Optimisation Solutions for Travelling Officer Problem with Customised Deep Learning Network
Deep learning has been extended to a number of new domains with critical...
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A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
Inference for population genetics models is hindered by computationally ...
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Ground Truth Bias in External Cluster Validity Indices
It has been noticed that some external CVIs exhibit a preferential bias ...
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