yusuke1997/dblp-id-title huggingface dataset:
Brain Morphometry Differences Across Sexes Revealed Through Explainable Artificial Intelligence: A Human Connectome Project Young Adult Study
A Differential Evolution Algorithm to Develop Strategies for the Iterated Prisoner's Dilemma
Variable Selection and Outlier Detection in Regularized Survival Models: Application to Melanoma Gene Expression Data
A Comparison of SVM Against Pre-trained Language Models (PLMs) for Text Classification Tasks
Improved Migrating Birds Optimization Algorithm to Solve Hybrid Flowshop Scheduling Problem with Lot-Streaming of Random Breakdown
Outlier Detection in Cox Proportional Hazards Models Based on the Concordance c-Index
Performance Evaluation of Local Surrogate Models in Bilevel Optimization
GRAN Is Superior to GraphRNN: Node Orderings, Kernel- and Graph Embeddings-Based Metrics for Graph Generators
Capturing Self Fulfilling Beliefs in a Rare Event: Local Outlier Factor
A Customer Relationship Management Case Study Based on Banking Data
SoC-Based Pattern Recognition Systems for Non Destructive Testing
Harnessing Graph Neural Networks for Pattern Classification in Heterogeneous Event Graphs
Conceptual Analysis of Big Data Using Ontologies and EER
LSTM Noise Robustness: A Case Study for Heavy Vehicles
PlattForm: Parallel Spoken Corpus of Middle West German Dialects with Web-Based Interface
A General Approach for Risk Controlled Trading Based on Machine Learning and Statistical Arbitrage
Using the GDELT Dataset to Analyse the Italian Sovereign Bond Market
BowTie - A Deep Learning Feedforward Neural Network for Sentiment Analysis
Transfer Learning for the Cognitive Staging Prediction in Alzheimer's Disease
Dissecting FLOPs Along Input Dimensions for GreenAI Cost Estimations
Uniformly Most-Reliable Graphs and Antiholes
Topological Properties of Mouse Neuronal Populations in Fluorescence Microscopy Images
A Practical Approach for Vehicle Speed Estimation in Smart Cities
LS-PON: A Prediction-Based Local Search for Neural Architecture Search
The Induction Problem: A Machine Learning Vindication Argument
Machine Learning, Optimization, and Data Science - 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22-25, 2024, Revised Selected Papers, Part I
Heuristic Search in LegalTech: Dynamic Allocation of Legal Cases to Legal Staff
Address Classification in E-Commerce Logistics Using Federated Learning
A Krill Herd Algorithm for the Multiobjective Energy Reduction Multi-Depot Vehicle Routing Problem
Visual Perception of Mixed Homogeneous Textures in Flying Pigeons
Multi-task Learning by Pareto Optimality
Enhanced Association Rules and Python
CMAC: Clustering Class Association Rules to Form a Compact and Meaningful Associative Classifier
Dual Convergence Estimates for a Family of Greedy Algorithms in Banach Spaces
Designing Combinational Circuits Using a Multi-objective Cartesian Genetic Programming with Adaptive Population Size
FoodViz: Visualization of Food Entities Linked Across Different Standards
State Representation Learning from Demonstration
A Modelica-Based Simulation Method for Black-Box Optimal Control Problems with Level-Set Dynamic Programming
Evaluating the Dispatching Policies for a Regional Network of Emergency Departments Exploiting Health Care Big Data
Enhancing Arrhythmia Detection Using an Ensemble of Transformer Models for Heartbeat Classification
Leveraging LLM-Powered Systems to Accelerate Mycobacterium Tuberculosis Research Step One: From Documents to the Vectorstore
An Optimization Method for Accurate Nonparametric Regressions on Stiefel Manifolds
Hyperparameter Optimization for Driving Strategies Based on Reinforcement Learning
Approximate Dynamic Programming with Combined Policy Functions for Solving Multi-stage Nurse Rostering Problem
Improved Filter-Based Feature Selection Using Correlation and Clustering Techniques
A Systems Biology Approach for Unsupervised Clustering of High-Dimensional Data
Ensemble Clustering for Boundary Detection in High-Dimensional Data
N-Gram Representation for Web Service Description Classification
Determining Principal Component Cardinality Through the Principle of Minimum Description Length
A Transfer Machine Learning Matching Algorithm for Source and Target (TL-MAST)
Revisiting Neurological Aspects of Relevance: An EEG Study
Driving Subscriptions Through User Behavior Modeling and Prediction at Bloomberg Media
Unsupervisedly Learned Representations - Should the Quest Be Over?
Reward Shaping for Job Shop Scheduling
Refining Partial Invalidations for Indexed Algebraic Dynamic Programming
Left/Right Brain, Human Motor Control and the Implications for Robotics
Exploring Digital Health Trends in the Headlines via Knowledge Graph Analysis
An Enhanced Infra-Chromatic Bound for the Maximum Clique Problem
User-Like Bots for Cognitive Automation: A Survey
Towards an Interpretable Functional Image-Based Classifier: Dimensionality Reduction of High-Density Diffuse Optical Tomography Data
Effects of Random Seeds on the Accuracy of Convolutional Neural Networks
Inferring Pathological Metabolic Patterns in Breast Cancer Tissue from Genome-Scale Models
Reinforcement Learning for Playing WrapSlide
Learning More Expressive Joint Distributions in Multimodal Variational Methods
Adaptive Zeroth-Order Optimisation of Nonconvex Composite Objectives
Machine Learning in a Policy Support System for Smart Tourism Management
Generative Fourier-Based Auto-encoders: Preliminary Results
A Bayesian-Optimized Convolutional Neural Network to Decode Reach-to-Grasp from Macaque Dorsomedial Visual Stream
A Scalable Biclustering Method for Heterogeneous Medical Data
Estimating Completeness of Consensus Models: Geometrical and Distributional Approaches
Learn to Move Through a Combination of Policy Gradient Algorithms: DDPG, D4PG, and TD3
Data-Based Forest Management with Uncertainties and Multiple Objectives
A Nash Equilibrium Approach to Metabolic Network Analysis
A Benchmark for Real-Time Anomaly Detection Algorithms Applied in Industry 4.0
A Learning-Based Mathematical Programming Formulation for the Automatic Configuration of Optimization Solvers
Leverage Mathematics' Capability to Compress and Generalize as Application of ML Embedding Extraction from LLMs and Its Adaptation in the Automotive Space
Zero-Shot Fashion Products Clustering on Social Image Streams
A New Distributed and Decentralized Stochastic Optimization Algorithm with Applications in Big Data Analytics
Conformal Prediction for Uncertainty Quantification in Brain Age Estimation Using Random Forests Quantile Regression on MRI Features of the HCP Young Adult
Advanced Metamodeling Techniques Applied to Multidimensional Applications with Piecewise Responses
Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space
Exploring Explainable Machine Learning for Enhanced Ship Performance Monitoring
A Parallel Framework for Multi-Population Cultural Algorithm and Its Applications in TSP
Machine Learning for the Evaluation of the Nephrops norvegicus Population
Optimal Design and Implementation of an Open-Source Emulation Platform for User-Centric Shared E-mobility Services
On Ensemble Learning for Mental Workload Classification
Combinatorial Reliability-Based Optimization of Nonlinear Finite Element Model Using an Artificial Neural Network-Based Approximation
Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines
FWin Transformer for Dengue Prediction Under Climate and Ocean Influence
Deep Autonomous Agents Comparison for Self-driving Cars
Intra-feature Random Forest Clustering
An Application of Machine Learning to Study Utilities Expenses in the Brazilian Navy
Learning Graph Configuration Spaces with Graph Embedding in Engineering Domains
Restaurant Health Inspections and Crime Statistics Predict the Real Estate Market in New York City
Driver Maneuvers Inference Through Machine Learning
Multi-scale Heat Kernel Graph Network for Graph Classification
Fast and Accurate Steepest-Descent Consistency-Constrained Algorithms for Feature Selection
Simple Learning with a Teacher via Biased Regularized Least Squares
On Bayesian Search for the Feasible Space Under Computationally Expensive Constraints
GRASP Heuristics for the Stochastic Weighted Graph Fragmentation Problem
Thinking Fast and Slow in AI: The Role of Metacognition
Feature Selection via Co-regularized Sparse-Group Lasso
Load Forecasting in District Heating Networks: Model Comparison on a Real-World Case Study
Inference of Abstraction for Human-Like Logical Reasoning
Anomaly Detection in Smart Grid Network Using FC-Based Blockchain Model and Linear SVM
Effect of the Dynamic Topology on the Performance of PSO-2S Algorithm for Continuous Optimization
Multi-parameter Regression of Photovoltaic Systems using Selection of Variables with the Method: Recursive Feature Elimination for Ridge, Lasso and Bayes
Can Differential Evolution Be an Efficient Engine to Optimize Neural Networks?
A Computational Framework for Identifying Salient Moments in Motion Capture Data
Subject Recognition Using Wrist-Worn Triaxial Accelerometer Data
Fast Hyperparameter Tuning for Support Vector Machines with Stochastic Gradient Descent
Can Complexity Measures and Instance Hardness Measures Reflect the Actual Complexity of Microarray Data?
Path Weights Analyses in a Shallow Neural Network to Reach Explainable Artificial Intelligence (XAI) of fMRI Data
Incoherent Submatrix Selection via Approximate Independence Sets in Scalar Product Graphs
Establishment of Optimal Control Strategy of Building-Integrated Photovoltaic Blind Slat Angle by Considering Interior Illuminance and Electricity Generation
Trading-off Data Fit and Complexity in Training Gaussian Processes with Multiple Kernels
Active Learning for Capturing Human Decision Policies in a Data Frugal Context
Ensemble Kalman Filter Optimizing Deep Neural Networks: An Alternative Approach to Non-performing Gradient Descent
Automatic Creation of a Large and Polished Training Set for Sentiment Analysis on Twitter
Long Short-Term Memory Networks for Earthquake Detection in Venezuelan Regions
Steplength and Mini-batch Size Selection in Stochastic Gradient Methods
SQG-Differential Evolution for Difficult Optimization Problems under a Tight Function Evaluation Budget
Covering Arrays to Support the Process of Feature Selection in the Random Forest Classifier
An Unsupervised Learning Classifier with Competitive Error Performance
A FastMap-Based Framework for Efficiently Computing Top-K Projected Centrality
A Heuristic Based on Fuzzy Inference Systems for Multiobjective IMRT Treatment Planning
A Generalized Quadratic Loss for SVM and Deep Neural Networks
Improving Portfolio Performance Using a Novel Method for Predicting Financial Regimes
Experiments on Properties of Hidden Structures of Sparse Neural Networks
Brain Structural Saliency over the Ages
Geolocation Risk Scores for Credit Scoring Models
On Graph Learning with Neural Networks
A Hybrid Steady-State Genetic Algorithm for the Minimum Conflict Spanning Tree Problem
Optimally Weighted Ensembles for Efficient Multi-objective Optimization
A Simple and Effective Lagrangian-Based Combinatorial Algorithm for S ^3 3 VMs
Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models
Compact Artificial Neural Network Models for Predicting Protein Residue - RNA Base Binding
Semantic Segmentation of Neuronal Bodies in Fluorescence Microscopy Using a 2D+3D CNN Training Strategy with Sparsely Annotated Data
Solving Mixed Influence Diagrams by Reinforcement Learning
Vital Prognosis of Patients in Intensive Care Units Using an Ensemble of Bayesian Classifiers
Robust Kernelized Bayesian Matrix Factorization for Video Background/Foreground Separation
A Nonparametric Pooling Operator Capable of Texture Extraction
Leveraging Graph Networks and Generative Adversarial Networks for Controllable Trajectory Predictions
Modification of the k-MXT Algorithm and Its Application to the Geotagged Data Clustering
Structural and Functional Representativity of GANs for Data Generation in Sequential Decision Making
Comparing Hidden Markov Models and Long Short Term Memory Neural Networks for Learning Action Representations
pH-RL: A Personalization Architecture to Bring Reinforcement Learning to Health Practice
Forecasting the IBEX-35 Stock Index Using Deep Learning and News Emotions
On Tree-Based Methods for Similarity Learning
Role of Punctuation in Semantic Mapping Between Brain and Transformer Models
MCGRAN: Multi-conditional Graph Generation for Neural Architecture Search
A Data Mining Tool for Water Uses Classification Based on Multiple Classifier Systems
Algorithms that Get Old: The Case of Generative Deep Neural Networks
Machine Learning, Optimization, and Data Science - 6th International Conference, LOD 2020, Siena, Italy, July 19-23, 2020, Revised Selected Papers, Part II
A Quantitative Analysis on Required Network Bandwidth for Large-Scale Parallel Machine Learning
A Framework for Multi-fidelity Modeling in Global Optimization Approaches
Monte Carlo Optimization of Liver Machine Perfusion Temperature Policies
Pattern Detection in Abnormal District Heating Data
An Attention-Based Representation Distillation Baseline for Multi-label Continual Learning
A Differential Evolution Algorithm to Semivectorial Bilevel Problems
BioHIPI: Biomedical Hadoop Image Processing Interface
Age and Gender Classification of Tweets Using Convolutional Neural Networks
Using Hessians as a Regularization Technique
Improving Traditional Dual Ascent Algorithm for the Uncapacitated Multiple Allocation Hub Location Problem: A RAMP Approach
Forecasting Natural Gas Flows in Large Networks
A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios
Predicting Worst-Case Execution Times During Multi-criterial Function Inlining
Machine Learning, Optimization, and Big Data - Second International Workshop, MOD 2016, Volterra, Italy, August 26-29, 2016, Revised Selected Papers
Thresholding Procedure via Barzilai-Borwein Rules for the Steplength Selection in Stochastic Gradient Methods
Learning Beam Search: Utilizing Machine Learning to Guide Beam Search for Solving Combinatorial Optimization Problems
Batch Bayesian Quadrature with Batch Updating Using Future Uncertainty Sampling
Heuristic for Site-Dependent Truck and Trailer Routing Problem with Soft and Hard Time Windows and Split Deliveries
Expressive and Intuitive Models for Automated Context Representation Learning in Credit-Card Fraud Detection
Understanding Sleep Dynamics Gathered from Wearable Devices with Explainable Recurrent Neural Networks
Learning with Discrete Least Squares on Multivariate Polynomial Spaces Using Evaluations at Random or Low-Discrepancy Point Sets
TREAT: Automated Construction and Maintenance of Probabilistic Knowledge Bases from Logs (Extended Abstract)
Analysis of Heavy Vehicles Rollover with Artificial Intelligence Techniques
A Unified Approach to Anomaly Detection
Parameterized Structured Pruning for Deep Neural Networks
Novel Reconstruction Errors for Saliency Detection in Hyperspectral Images
Boosted Embeddings for Time-Series Forecasting
Dynamic Programming with Approximation Function for Nurse Scheduling
SoftCut: A Fully Differentiable Relaxed Graph Cut Approach for Deep Learning Image Segmentation
On the Role of Activation Functions in EEG-to-Text Decoder
Machine Learning, Optimization, and Data Science - 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers
A Machine Learning Approach to Daily Capacity Planning in E-Commerce Logistics
A k-mer Based Sequence Similarity for Pangenomic Analyses
Epicentral Region Estimation Using Convolutional Neural Networks
Quantifying Local Energy Demand Through Pollution Analysis
Pooling Graph Convolutional Networks for Structural Performance Prediction
Dynamic Multi-Objective Optimization with jMetal and Spark: A Case Study
Active Learning Approach for Safe Process Parameter Tuning
Alternating Mixed-Integer Programming and Neural Network Training for Approximating Stochastic Two-Stage Problems
Application of Multi-agent Reinforcement Learning to the Dynamic Scheduling Problem in Manufacturing Systems
Differentiating the Multipoint Expected Improvement for Optimal Batch Design
Data Clustering by Particle Swarm Optimization with the Focal Particles
Mixing Consistent Deep Clustering
Assessing the Impact of Government Policies on Covid-19 Spread: A Machine Learning Approach
Towards Understanding Neuroscience of Realisation of Information Need in Light of Relevance and Satisfaction Judgement
Deep Learning Model of Two-Phase Fluid Transport Through Fractured Media: A Real-World Case Study
Brain-Inspired Spike Timing Model of Dynamic Visual Information Perception and Decision Making with STDP and Reinforcement Learning
Improving Clinical Subjects Clustering by Learning and Optimizing Feature Weights
Machine Learning, Optimization, and Data Science - 7th International Conference, LOD 2021, Grasmere, UK, October 4-8, 2021, Revised Selected Papers, Part I
Evolutionary Construction of Convolutional Neural Networks
Fast ABC with Joint Generative Modelling and Subset Simulation
Optimal Risk Scores for Continuous Predictors
Optimizing the Location of Helicopter Emergency Medical Service Operating Sites
Robust Generative Restricted Kernel Machines Using Weighted Conjugate Feature Duality
A New Approach to Early Warning Systems for Small European Banks
Coking Coal Railway Transportation Forecasting Using Ensembles of ElasticNet, LightGBM, and Facebook Prophet
Randomized Iterative Methods for Matrix Approximation
A Two-Country Study of Default Risk Prediction Using Bayesian Machine-Learning
Building Knowledge Base for the Domain of Economic Mobility of Older Workers
Can Big Data Help to Predict Conditional Stock Market Volatility? An Application to Brexit
Synthetic Time Series for Anomaly Detection in Cloud Microservices
Grid-Based Contraction Clustering in a Peer-to-Peer Network
Deep Reinforcement Learning for Optimal Energy Management of Multi-energy Smart Grids
Deep 3D Convolution Neural Network for Alzheimer's Detection
Between Accurate Prediction and Poor Decision Making: The AI/ML Gap
Neural Correlates of Satisfaction of an Information Need
Activity Imputation of Shared e-Bikes Travels in Urban Areas
Importance Weighting of Diagnostic Trouble Codes for Anomaly Detection
Scaling Up Quasi-newton Algorithms: Communication Efficient Distributed SR1
A Proximal Algorithm for Network Slimming
Expressive Graph Informer Networks
Can You Tell? SSNet - A Biologically-Inspired Neural Network Framework for Sentiment Classifiers
U-FLEX: Unsupervised Feature Learning with Evolutionary eXploration
Machine Learning, Optimization, and Data Science - 5th International Conference, LOD 2019, Siena, Italy, September 10-13, 2019, Proceedings
Path-Weights and Layer-Wise Relevance Propagation for Explainability of ANNs with fMRI Data
Artificial Intelligence and Cyber Security
An Evolutionary Approach to Feature Selection and Classification
Machine Learning Approaches for Predicting Crystal Systems: A Brief Review and a Case Study
New Optimization Approaches in Malware Traffic Analysis
Bilevel Optimization by Conditional Bayesian Optimization
A Machine Learning Approach for Source Code Similarity via Graph-Focused Features
Beyond Iterative Tuning: Zero-Shot Hyperparameter Optimisation for Decision Trees
Surrogate Modeling for Stochastic Assessment of Engineering Structures
Classification and Survival Prediction in Diffuse Large B-Cell Lymphoma by Gene Expression Profiling
Optimization of Neural Network Training with ELM Based on the Iterative Hybridization of Differential Evolution with Local Search and Restarts
Sparse Perturbations for Improved Convergence in Stochastic Zeroth-Order Optimization
SKIE-SRL: Structured Key Information Extraction from Business Documents Using Statistical Relational Learning
Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMs
LIA: A Label-Independent Algorithm for Feature Selection for Supervised Learning
Analyzing Communication Broadcasting in the Digital Space
ENGinnSAND: A Reference Dataset for Monocular Depth Prediction of Line Structures
A Noisy-Labels Approach to Detecting Uncompetitive Auctions
Machine Learning for Big Data Analysis in Drug Design
Optimal Scenario-Tree Selection for Multistage Stochastic Programming
Adversarial Perturbations for Evolutionary Optimization
Malicious Website Detection Through Deep Learning Algorithms
Modeling Primacy, Recency, and Cued Recall in Serial Memory Task Using On-Center Off-Surround Recurrent Neural Network
Machine Learning, Optimization, and Data Science - 8th International Workshop, LOD 2022, Certosa di Pontignano, Italy, September 19-22, 2022, Revised Selected Papers, Part II
On Channel Selection for EEG-Based Mental Workload Classification
Federated Learning of Deep Neural Decision Forests
Chronologically Guided Deep Network for Remaining Useful Life Estimation
Image-Based Fashion Product Recommendation with Deep Learning
Cultural Ant Colony Optimization on GPUs for Travelling Salesman Problem
Machine Learning, Optimization, and Data Science - 9th International Conference, LOD 2023, Grasmere, UK, September 22-26, 2023, Revised Selected Papers, Part I
Online Semi-supervised Learning from Evolving Data Streams with Meta-features and Deep Reinforcement Learning
A Radically New Theory of How the Brain Represents and Computes with Probabilities
Limits of Transfer Learning
A Game Theoretic Flavoured Decision Tree for Classification
Learning Consistent Tree-Augmented Dynamic Bayesian Networks
Adapting to Complexity: Deep Learnable Architecture for Protein-protein Interaction Predictions
Hierarchical Decentralized Deep Reinforcement Learning Architecture for a Simulated Four-Legged Agent
Directed Acyclic Graph Reconstruction Leveraging Prior Partial Ordering Information
An Efficient Many-Core Implementation for Semi-Supervised Support Vector Machines
Wasserstein Embeddings for Nonnegative Matrix Factorization
Deep Active Learning with Concept Drifts for Detection of Mercury's Bow Shock and Magnetopause Crossings
Matrix Completion for the Prediction of Yearly Country and Industry-Level CO 2 Emissions
Enforcing Hard State-Dependent Action Bounds on Deep Reinforcement Learning Policies
Assessing Accuracy of Ensemble Learning for Facial Expression Recognition with CNNs
A Clonal Selection Algorithm for Multiobjective Energy Reduction Multi-Depot Vehicle Routing Problem
Black Box Algorithm Selection by Convolutional Neural Network
Strategic Workforce Planning with Deep Reinforcement Learning
Human-Centric Machine Learning Approach for Injection Mold Design: Towards Automated Ejector Pin Placement
Clarifying the Fog: Evaluating and Enhancing User Comprehension of Android Data Safety Documents
Projective Approximation Based Quasi-Newton Methods
Automatic Tuning of Algorithms Through Sensitivity Minimization
REFINE: Representation Learning from Diffusion Events
Variance Loss in Variational Autoencoders
Leap: Inductive Link Prediction via Learnable Topology Augmentation
Intelligent Robotic Process Automation for Supplier Document Management on E-Procurement Platforms
Bandits and Recommender Systems
Speeding Up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks
Does Catastrophic Forgetting Negatively Affect Financial Predictions?
Adaptive Targeting in Online Advertisement: Models Based on Relative Influence of Factors
Skin Lesion Diagnosis with Imbalanced ECOC Ensembles
Robust PCA for Anomaly Detection and Data Imputation in Seasonal Time Series
Benchmarking Deep Learning Models for Driver Distraction Detection
Mesoscale Events Classification in Sea Surface Temperature Imagery
Radiotherapy Treatment Planning: An Integrated Optimization and Reinforcement Learning Approach
SMBOX: A Scalable and Efficient Method for Sequential Model-Based Parameter Optimization
Relationship Estimation Metrics for Binary SoC Data
Perceptrons Under Verifiable Random Data Corruption
Modelling Chaotic Time Series Using Recursive Deep Self-organising Neural Networks
Rapidly Computing Approximate Graph Convex Hulls via FastMap
Learning Optimal Decision Lists as a Metaheuristic Search for Diagnosis of Parkinson's Disease