Using ARIMA to Predict the Expansion of Subscriber Data Consumption
arXiv:2404.15095v1 Announce Type: new Abstract: This study discusses how insights retrieved from subscriber data can impact decision-making in telecommunications, focusing on predictive modeling using...
View ArticleHyperparameter Optimization Can Even be Harmful in Off-Policy Learning and...
arXiv:2404.15084v1 Announce Type: new Abstract: There has been a growing interest in off-policy evaluation in the literature such as recommender systems and personalized medicine. We have so far seen...
View ArticleFormal Verification of Graph Convolutional Networks with Uncertain Node...
arXiv:2404.15065v1 Announce Type: new Abstract: Graph neural networks are becoming increasingly popular in the field of machine learning due to their unique ability to process data structured in...
View ArticleDeep Multi-View Channel-Wise Spatio-Temporal Network for Traffic Flow Prediction
arXiv:2404.15034v1 Announce Type: new Abstract: Accurately forecasting traffic flows is critically important to many real applications including public safety and intelligent transportation systems....
View ArticleExplainable LightGBM Approach for Predicting Myocardial Infarction Mortality
arXiv:2404.15029v1 Announce Type: new Abstract: Myocardial Infarction is a main cause of mortality globally, and accurate risk prediction is crucial for improving patient outcomes. Machine Learning...
View ArticleConformal Predictive Systems Under Covariate Shift
arXiv:2404.15018v1 Announce Type: new Abstract: Conformal Predictive Systems (CPS) offer a versatile framework for constructing predictive distributions, allowing for calibrated inference and...
View Article$\texttt{MiniMol}$: A Parameter-Efficient Foundation Model for Molecular...
arXiv:2404.14986v1 Announce Type: new Abstract: In biological tasks, data is rarely plentiful as it is generated from hard-to-gather measurements. Therefore, pre-training foundation models on large...
View ArticleSymbolic Integration Algorithm Selection with Machine Learning: LSTMs vs Tree...
arXiv:2404.14973v1 Announce Type: new Abstract: Computer Algebra Systems (e.g. Maple) are used in research, education, and industrial settings. One of their key functionalities is symbolic integration,...
View ArticleIntegrating Heterogeneous Gene Expression Data through Knowledge Graphs for...
arXiv:2404.14970v1 Announce Type: new Abstract: Diabetes is a worldwide health issue affecting millions of people. Machine learning methods have shown promising results in improving diabetes...
View ArticleCache-Aware Reinforcement Learning in Large-Scale Recommender Systems
arXiv:2404.14961v1 Announce Type: new Abstract: Modern large-scale recommender systems are built upon computation-intensive infrastructure and usually suffer from a huge difference in traffic between...
View ArticleDynamic pricing with Bayesian updates from online reviews
arXiv:2404.14953v1 Announce Type: new Abstract: When launching new products, firms face uncertainty about market reception. Online reviews provide valuable information not only to consumers but also to...
View ArticleDelayed Bottlenecking: Alleviating Forgetting in Pre-trained Graph Neural...
arXiv:2404.14941v1 Announce Type: new Abstract: Pre-training GNNs to extract transferable knowledge and apply it to downstream tasks has become the de facto standard of graph representation learning....
View ArticleFin-Fed-OD: Federated Outlier Detection on Financial Tabular Data
arXiv:2404.14933v1 Announce Type: new Abstract: Anomaly detection in real-world scenarios poses challenges due to dynamic and often unknown anomaly distributions, requiring robust methods that operate...
View ArticleGraph Machine Learning in the Era of Large Language Models (LLMs)
arXiv:2404.14928v1 Announce Type: new Abstract: Graphs play an important role in representing complex relationships in various domains like social networks, knowledge graphs, and molecular discovery....
View ArticleMultiSTOP: Solving Functional Equations with Reinforcement Learning
arXiv:2404.14909v1 Announce Type: new Abstract: We develop MultiSTOP, a Reinforcement Learning framework for solving functional equations in physics. This new methodology produces actual numerical...
View ArticleGCEPNet: Graph Convolution-Enhanced Expectation Propagation for Massive MIMO...
arXiv:2404.14886v1 Announce Type: new Abstract: Massive MIMO (multiple-input multiple-output) detection is an important topic in wireless communication and various machine learning based methods have...
View ArticleRegularized Gauss-Newton for Optimizing Overparameterized Neural Networks
arXiv:2404.14875v1 Announce Type: new Abstract: The generalized Gauss-Newton (GGN) optimization method incorporates curvature estimates into its solution steps, and provides a good approximation to the...
View ArticleThe Geometry of the Set of Equivalent Linear Neural Networks
arXiv:2404.14855v1 Announce Type: new Abstract: We characterize the geometry and topology of the set of all weight vectors for which a linear neural network computes the same linear transformation $W$....
View ArticleRevisiting Neural Networks for Continual Learning: An Architectural Perspective
arXiv:2404.14829v1 Announce Type: new Abstract: Efforts to overcome catastrophic forgetting have primarily centered around developing more effective Continual Learning (CL) methods. In contrast, less...
View ArticleTime-aware Heterogeneous Graph Transformer with Adaptive Attention Merging...
arXiv:2404.14815v1 Announce Type: new Abstract: The widespread application of Electronic Health Records (EHR) data in the medical field has led to early successes in disease risk prediction using deep...
View ArticleIntegrating Mamba and Transformer for Long-Short Range Time Series Forecasting
arXiv:2404.14757v1 Announce Type: new Abstract: Time series forecasting is an important problem and plays a key role in a variety of applications including weather forecasting, stock market, and...
View ArticleSkip the Benchmark: Generating System-Level High-Level Synthesis Data using...
arXiv:2404.14754v1 Announce Type: new Abstract: High-Level Synthesis (HLS) Design Space Exploration (DSE) is a widely accepted approach for efficiently exploring Pareto-optimal and optimal hardware...
View ArticleSemantic Cells: Evolutional Process to Acquire Sense Diversity of Items
arXiv:2404.14749v1 Announce Type: new Abstract: Previous models for learning the semantic vectors of items and their groups, such as words, sentences, nodes, and graphs, using distributed...
View ArticleA Customer Level Fraudulent Activity Detection Benchmark for Enhancing...
arXiv:2404.14746v1 Announce Type: new Abstract: In the field of fraud detection, the availability of comprehensive and privacy-compliant datasets is crucial for advancing machine learning research and...
View ArticleNovel Topological Machine Learning Methodology for Stream-of-Quality Modeling...
arXiv:2404.14728v1 Announce Type: new Abstract: This paper presents a topological analytics approach within the 5-level Cyber-Physical Systems (CPS) architecture for the Stream-of-Quality assessment in...
View ArticleDynamically Anchored Prompting for Task-Imbalanced Continual Learning
arXiv:2404.14721v1 Announce Type: new Abstract: Existing continual learning literature relies heavily on a strong assumption that tasks arrive with a balanced data stream, which is often unrealistic in...
View ArticleDeep neural networks for choice analysis: Enhancing behavioral regularity...
arXiv:2404.14701v1 Announce Type: new Abstract: Deep neural networks (DNNs) frequently present behaviorally irregular patterns, significantly limiting their practical potentials and theoretical...
View ArticleInterpretable Prediction and Feature Selection for Survival Analysis
arXiv:2404.14689v1 Announce Type: new Abstract: Survival analysis is widely used as a technique to model time-to-event data when some data is censored, particularly in healthcare for predicting future...
View ArticleFMint: Bridging Human Designed and Data Pretrained Models for Differential...
arXiv:2404.14688v1 Announce Type: new Abstract: Human-designed algorithms have long been fundamental in solving a variety of scientific and engineering challenges. Recently, data-driven deep learning...
View ArticleHOIN: High-Order Implicit Neural Representations
arXiv:2404.14674v1 Announce Type: new Abstract: Implicit neural representations (INR) suffer from worsening spectral bias, which results in overly smooth solutions to the inverse problem. To deal with...
View ArticleEmploying Layerwised Unsupervised Learning to Lessen Data and Loss...
arXiv:2404.14664v1 Announce Type: new Abstract: Recent deep learning models such as ChatGPT utilizing the back-propagation algorithm have exhibited remarkable performance. However, the disparity...
View ArticleNExT: Teaching Large Language Models to Reason about Code Execution
arXiv:2404.14662v1 Announce Type: new Abstract: A fundamental skill among human developers is the ability to understand and reason about program execution. As an example, a programmer can mentally...
View ArticleUncertainty Quantification on Graph Learning: A Survey
arXiv:2404.14642v1 Announce Type: new Abstract: Graphical models, including Graph Neural Networks (GNNs) and Probabilistic Graphical Models (PGMs), have demonstrated their exceptional capabilities...
View ArticleDigital Twins for forecasting and decision optimisation with machine...
arXiv:2404.14635v1 Announce Type: new Abstract: Prediction and optimisation are two widely used techniques that have found many applications in solving real-world problems. While prediction is...
View ArticleFairness Incentives in Response to Unfair Dynamic Pricing
arXiv:2404.14620v1 Announce Type: new Abstract: The use of dynamic pricing by profit-maximizing firms gives rise to demand fairness concerns, measured by discrepancies in consumer groups' demand...
View ArticleHybrid LLM: Cost-Efficient and Quality-Aware Query Routing
arXiv:2404.14618v1 Announce Type: new Abstract: Large language models (LLMs) excel in most NLP tasks but also require expensive cloud servers for deployment due to their size, while smaller models that...
View ArticleBrain-Inspired Continual Learning-Robust Feature Distillation and...
arXiv:2404.14588v1 Announce Type: new Abstract: Artificial intelligence (AI) and neuroscience share a rich history, with advancements in neuroscience shaping the development of AI systems capable of...
View ArticleGeneralizing Multi-Step Inverse Models for Representation Learning to...
arXiv:2404.14552v1 Announce Type: new Abstract: Discovering an informative, or agent-centric, state representation that encodes only the relevant information while discarding the irrelevant is a key...
View ArticleEdge-Assisted ML-Aided Uncertainty-Aware Vehicle Collision Avoidance at Urban...
arXiv:2404.14523v1 Announce Type: new Abstract: Intersection crossing represents one of the most dangerous sections of the road infrastructure and Connected Vehicles (CVs) can serve as a revolutionary...
View ArticleTowards smallers, faster decoder-only transformers: Architectural variants...
arXiv:2404.14462v1 Announce Type: new Abstract: Research on Large Language Models (LLMs) has recently seen exponential growth, largely focused on transformer-based architectures, as introduced by [1]...
View ArticleGraph Coloring Using Heat Diffusion
arXiv:2404.14457v1 Announce Type: new Abstract: Graph coloring is a problem with varied applications in industry and science such as scheduling, resource allocation, and circuit design. The purpose of...
View ArticleMultifidelity Surrogate Models: A New Data Fusion Perspective
arXiv:2404.14456v1 Announce Type: new Abstract: Multifidelity surrogate modelling combines data of varying accuracy and cost from different sources. It strategically uses low-fidelity models for rapid...
View ArticleA Neuro-Symbolic Explainer for Rare Events: A Case Study on Predictive...
arXiv:2404.14455v1 Announce Type: new Abstract: Predictive Maintenance applications are increasingly complex, with interactions between many components. Black box models are popular approaches based on...
View ArticleGenerative Subspace Adversarial Active Learning for Outlier Detection in...
arXiv:2404.14451v1 Announce Type: new Abstract: Outlier detection in high-dimensional tabular data is an important task in data mining, essential for many downstream tasks and applications. Existing...
View ArticleA Novel A.I Enhanced Reservoir Characterization with a Combined Mixture of...
arXiv:2404.14447v1 Announce Type: new Abstract: We have developed an advanced workflow for reservoir characterization, effectively addressing the challenges of reservoir history matching through a...
View ArticleA Multi-Faceted Evaluation Framework for Assessing Synthetic Data Generated...
arXiv:2404.14445v1 Announce Type: new Abstract: The rapid advancements in generative AI and large language models (LLMs) have opened up new avenues for producing synthetic data, particularly in the...
View ArticlePractical Battery Health Monitoring using Uncertainty-Aware Bayesian Neural...
arXiv:2404.14444v1 Announce Type: new Abstract: Battery health monitoring and prediction are critically important in the era of electric mobility with a huge impact on safety, sustainability, and...
View ArticleUnified ODE Analysis of Smooth Q-Learning Algorithms
arXiv:2404.14442v1 Announce Type: new Abstract: Convergence of Q-learning has been the focus of extensive research over the past several decades. Recently, an asymptotic convergence analysis for...
View ArticleInvestigating Resource-efficient Neutron/Gamma Classification ML Models...
arXiv:2404.14436v1 Announce Type: new Abstract: There has been considerable interest and resulting progress in implementing machine learning (ML) models in hardware over the last several years from the...
View ArticleKATO: Knowledge Alignment and Transfer for Transistor Sizing of Different...
arXiv:2404.14433v1 Announce Type: new Abstract: Automatic transistor sizing in circuit design continues to be a formidable challenge. Despite that Bayesian optimization (BO) has achieved significant...
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