Papers BIG-bench Machine Learning
“BIG-bench Machine Learning” 태그가 달린 논문 10,033편 · 필터 해제
(1,1)-Cluster Editing is Polynomial-time Solvable
A graph $H$ is a clique graph if $H$ is a vertex-disjoin union of cliques. Abu-Khzam (2017) introduced the $(a,d)$-{Cluster Editing} problem, where for fixed natural numbers $a,d$, given a graph $G$ and vertex-weights $a…
BIG-bench Machine LearningAnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks
AnalogVNN, a simulation framework built on PyTorch which can simulate the effects of optoelectronic noise, limited precision, and signal normalization present in photonic neural network accelerators. We use this framewor…
BIG-bench Machine LearningGPUHyperparameter OptimizationManagementDiscover the Mysteries of the Maya: Selected Contributions from the Machine Learning Challenge & The Discovery Challenge Workshop at ECML PKDD 2021
The volume contains selected contributions from the Machine Learning Challenge "Discover the Mysteries of the Maya", presented at the Discovery Challenge Track of The European Conference on Machine Learning and Principle…
BIG-bench Machine LearningImage SegmentationSemantic SegmentationTailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity
Expected risk minimization (ERM) is at the core of many machine learning systems. This means that the risk inherent in a loss distribution is summarized using a single number - its average. In this paper, we propose a ge…
BIG-bench Machine LearningSensitivityExplanation of Machine Learning Models of Colon Cancer Using SHAP Considering Interaction Effects
When using machine learning techniques in decision-making processes, the interpretability of the models is important. Shapley additive explanation (SHAP) is one of the most promising interpretation methods for machine le…
BIG-bench Machine LearningDecision MakingMachine Learning and Bioinformatics for Diagnosis Analysis of Obesity Spectrum Disorders
Globally, the number of obese patients has doubled due to sedentary lifestyles and improper dieting. The tremendous increase altered human genetics, and health. According to the world health organization, Life expectancy…
BIG-bench Machine LearningA Lightweight Machine Learning Pipeline for LiDAR-simulation
Virtual testing is a crucial task to ensure safety in autonomous driving, and sensor simulation is an important task in this domain. Most current LiDAR simulations are very simplistic and are mainly used to perform initi…
Autonomous DrivingBIG-bench Machine LearningImage-to-Image TranslationEvolutionary bagging for ensemble learning
Ensemble learning has gained success in machine learning with major advantages over other learning methods. Bagging is a prominent ensemble learning method that creates subgroups of data, known as bags, that are trained …
BIG-bench Machine LearningDiversityEnsemble LearningEvolutionary AlgorithmsPrivacy-Preserving Chaotic Extreme Learning Machine with Fully Homomorphic Encryption
The Machine Learning and Deep Learning Models require a lot of data for the training process, and in some scenarios, there might be some sensitive data, such as customer information involved, which the organizations migh…
BIG-bench Machine LearningDeep LearningPrivacy PreservingNeural network accelerator for quantum control
Efficient quantum control is necessary for practical quantum computing implementations with current technologies. Conventional algorithms for determining optimal control parameters are computationally expensive, largely …
BIG-bench Machine LearningActive Learning on a Programmable Photonic Quantum Processor
Training a quantum machine learning model generally requires a large labeled dataset, which incurs high labeling and computational costs. To reduce such costs, a selective training strategy, called active learning (AL), …
Active LearningBIG-bench Machine LearningQuantum Machine LearningMachine learning optimization of Majorana hybrid nanowires
As the complexity of quantum systems such as quantum bit arrays increases, efforts to automate expensive tuning are increasingly worthwhile. We investigate machine learning based tuning of gate arrays using the CMA-ES al…
BIG-bench Machine LearningIntegrated Sensing and Communication for 6G: Ten Key Machine Learning Roles
Integrating sensing and communication is a defining theme for future wireless systems. This is motivated by the promising performance gains, especially as they assist each other, and by the better utilization of the wire…
BIG-bench Machine LearningIntegrated sensing and communicationDesign of secure and robust cognitive system for malware detection
Machine learning based malware detection techniques rely on grayscale images of malware and tends to classify malware based on the distribution of textures in graycale images. Albeit the advancement and promising results…
Adversarial AttackBIG-bench Machine LearningMalware DetectionUnravelling Interlanguage Facts via Explainable Machine Learning
Native language identification (NLI) is the task of training (via supervised machine learning) a classifier that guesses the native language of the author of a text. This task has been extensively researched in the last …
BIG-bench Machine LearningLanguage IdentificationNative Language IdentificationMaking a Spiking Net Work: Robust brain-like unsupervised machine learning
The surge in interest in Artificial Intelligence (AI) over the past decade has been driven almost exclusively by advances in Artificial Neural Networks (ANNs). While ANNs set state-of-the-art performance for many previou…
BIG-bench Machine LearningWhat can we Learn by Predicting Accuracy?
This paper seeks to answer the following question: \textit{"What can we learn by predicting accuracy?"}. Indeed, classification is one of the most popular tasks in machine learning, and many loss functions have been deve…
BIG-bench Machine LearningLearning TheorySymbolic RegressionFlood Prediction Using Machine Learning Models
Floods are one of nature's most catastrophic calamities which cause irreversible and immense damage to human life, agriculture, infrastructure and socio-economic system. Several studies on flood catastrophe management an…
BIG-bench Machine LearningManagementPredictionDeep Reinforcement Learning for Multi-Agent Interaction
The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Towards this goal, the Autonomous Agents Re…
BIG-bench Machine LearningCausal InferenceDeep Reinforcement LearningMulti-agent Reinforcement Learning+4No Pattern, No Recognition: a Survey about Reproducibility and Distortion Issues of Text Clustering and Topic Modeling
Extracting knowledge from unlabeled texts using machine learning algorithms can be complex. Document categorization and information retrieval are two applications that may benefit from unsupervised learning (e.g., text c…
BIG-bench Machine LearningClusteringInformation RetrievalRetrieval+2