yusuke1997/dblp-id-title huggingface dataset:
Research Paper: Alternatives to Project-specific Consent for Access to Personal Information for Health Research: What Is the Opinion of the Canadian Public?
Data quality assessment in healthcare: a 365-day chart review of inpatients' health records at a Nigerian tertiary hospital
Effect of health information technology (HIT)-based discharge transition interventions on patient readmissions and emergency room visits: a systematic review
A framework for the oversight and local deployment of safe and high-quality prediction models
Consideration of bias in data sources and digital services to advance health equity
Research Paper: Machine Learning for an Expert System to Predict Preterm Birth Risk
Comparing Medline citations using modified N-grams
Ability of pharmacy clinical decision-support software to alert users about clinically important drug-drug interactions
The OneFlorida Data Trust: a centralized, translational research data infrastructure of statewide scope
Development of an optical character recognition pipeline for handwritten form fields from an electronic health record
Viewpoint: The Interactions Between Clinical Informatics and Bioinformatics: A Case Study
Position Paper: A Consensus Action Agenda for Achieving the National Health Information Infrastructure
Identifying and prioritizing benefits and risks of using privacy-enhancing software through participatory design: a nominal group technique study with patients living with chronic conditions
Artificial intelligence for optimizing recruitment and retention in clinical trials: a scoping review
A digital health profile & maturity assessment toolkit: cocreation and testing in the Pacific Islands
Editorial Comments: Using Commercial Knowledge Bases for Clinical Decision Support: Opportunities, Hurdles, and Recommendations
Evaluation of computer-generated reminders to improve CD4 laboratory monitoring in sub-Saharan Africa: a prospective comparative study
Research Paper: Measuring the Effects of Reminders for Outpatient Influenza Immunizations at the Point of Clinical Opportunity
Mobile health devices: will patients actually use them?
Viewpoint Paper: e-Prescribing, Efficiency, Quality: Lessons from the Computerization of UK Family Practice
Application of Information Technology: The Asthma Kiosk: A Patient-centered Technology for Collaborative Decision Support in the Emergency Department
Getting the foot out of the pelvis: modeling problems affecting use of SNOMED CT hierarchies in practical applications
Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces
Research Paper: Association Rules and Data Mining in Hospital Infection Control and Public Health Surveillance
Impact of a clinical decision support system on antibiotic prescribing for acute respiratory infections in primary care: quasi-experimental trial
Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing
Automatic extraction of social determinants of health from medical notes of chronic lower back pain patients
Research Paper: Forecasting Emergency Department Crowding: A Prospective, Real-time Evaluation
Application of natural language processing techniques to identify off-label drug usage from various online health communities
Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification
Problems with the problem list: challenges of transparency in an era of patient curation
Challenges and lessons learned in promoting adoption of standardized local public health service delivery data through the application of the Public Health Activities and Services Tracking model
Impact of integrated graphical display on expert and novice diagnostic performance in critical care
Multimodal integration of longitudinal noninvasive diagnostics for survival prediction in immunotherapy using deep learning
Pharmacogenomics in the pocket of every patient? A prototype based on quick response codes
Using statistical and machine learning to help institutions detect suspicious access to electronic health records
A vector space model approach to identify genetically related diseases
Synthesis of Research Paper: A Consensus Statement on Considerations for a Successful CPOE Implementation
Fast and Exact Warping of Time Series Using Adaptive Segmental Approximations
Editorial survey: swarm intelligence for data mining
Compatible natural gradient policy search
Extended UCB Policies for Multi-armed Bandit Problems
Multi-output learning via spectral filtering
Identification of biological transition systems using meta-interpreted logic programs
TEXPLORE: real-time sample-efficient reinforcement learning for robots
Flattening and Saturation: Two Representation Changes for Generalization
Rollout sampling approximate policy iteration
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations
Spatial entropy as an inductive bias for vision transformers
Uncover the balanced geometry in long-tailed contrastive language-image pretraining
Efficient Weingarten map and curvature estimation on manifolds
Domain adversarial neural networks for domain generalization: when it works and how to improve
Aligning music audio with symbolic scores using a hybrid graphical model
Discovering Significant Patterns
Collaborative filtering with information-rich and information-sparse entities
Nuclear discrepancy for single-shot batch active learning
Heat transfer flow of non-Newtonian eyring-powell fluid with mixed convection heterogeneous and homogeneous reactions using linear regression based machine learning approach
Subjectively interesting alternative clusterings
Induction as Consequence Finding
Fast learning of relational kernels
Evaluating large language models for user stance detection on X (Twitter)
Multi-agent reinforcement learning for fast-timescale demand response of residential loads
Generalized exploration in policy search
Learning programs with magic values
Sparse probit linear mixed model
Advice to Machine Learning Authors
Inference over radiative transfer models using variational and expectation maximization methods
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare
Introduction: special issue of selected papers of ACML 2013
Semi-parametric Bayes regression with network-valued covariates
Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach
Learning Concepts from Sensor Data of a Mobile Robot
ReDMan: reliable dexterous manipulation with safe reinforcement learning
Guest editors introduction: special issue on inductive logic programming
Efficient private SCO for heavy-tailed data via averaged clipping
Linear Concepts and Hidden Variables
Time varying undirected graphs
Hardness Results for Learning First-Order Representations and Programming by Demonstration
On Learning Gene Regulatory Networks Under the Boolean Network Model
Data-guided model combination by decomposition and aggregation
A Reply to Towell's Book Review of Neural Network Perception for Mobile Robot Guidance
Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
On some graph-based two-sample tests for high dimension, low sample size data
A Multistrategy Approach to Classifier Learning from Time Series
Fedflow: a personalized federated learning framework for passenger flow prediction
Best-effort inductive logic programming via fine-grained cost-based hypothesis generation - The inspire system at the inductive logic programming competition
Enhanced route planning with calibrated uncertainty set
Anytime learning of anycost classifiers
Learning figures with the Hausdorff metric by fractals - towards computable binary classification
Feature Generation Using General Constructor Functions
Inductive transfer for learning Bayesian networks
On the use of stochastic local search techniques to revise first-order logic theories from examples
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
EchoRAG: a framework for enhancing language models with graph-RAG and in-context learning
Planning in hybrid relational MDPs
Bagging Predictors
Plane-based object categorisation using relational learning
Optimal policy trees
Tune and mix: learning to rank using ensembles of calibrated multi-class classifiers
Combining Statistical Language Models via the Latent Maximum Entropy Principle
Online semi-supervised learning of composite event rules by combining structure and mass-based predicate similarity
Variance reduction in feature hashing using MLE and control variate method
The class imbalance problem in deep learning
Discrete Sequence Prediction and Its Applications
Embedding to reference t-SNE space addresses batch effects in single-cell classification
Learning at the Knowledge Level
Support-Vector Networks
A bad arm existence checking problem: How to utilize asymmetric problem structure?
Stress detection with encoding physiological signals and convolutional neural network
News and Notes
A model for intelligible interaction between agents that predict and explain
Pasco (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms
Associative Reinforcement Learning: Functions in k-DNF
An incremental off-policy search in a model-free Markov decision process using a single sample path
UnbiasedNets: a dataset diversification framework for robustness bias alleviation in neural networks
Adaptive edge weighting for graph-based learning algorithms
CoMadOut - a robust outlier detection algorithm based on CoMAD
Explainable models via compression of tree ensembles
Online calibrated forecasts: Memory efficiency versus universality for learning in games
Exploring the common principal subspace of deep features in neural networks
Joint consensus and diversity for multi-view semi-supervised classification
Support Vector Machines for Classification in Nonstandard Situations
Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models
The CN2 Induction Algorithm
Additive regularization of topic models
Correction to: Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach
A theoretical and empirical analysis of support vector machine methods for multiple-instance classification
Predicting potential real-time donations in YouTube live streaming services via continuous-time dynamic graphs
Multi-view kernel completion
Overfitting Avoidance as Bias
Commentary: a decomposition of the outlier detection problem into a set of supervised learning problems
Special issue on feature engineering editorial
logicDT: a procedure for identifying response-associated interactions between binary predictors
Learning to Recognize and Grasp Objects
Semi-Lipschitz functions and machine learning for discrete dynamical systems on graphs
Extremely randomized trees
The Power of Self-Directed Learning
Efficient Venn predictors using random forests
Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods
Letter Recognition Using Holland-Style Adaptive Classifiers
A Cognitive Bias Approach to Feature Selection and Weighting for Case-Based Learners
Learning multi-linear representations of distributions for efficient inference
Neural networks for relational learning: an experimental comparison
An end-to-end explainability framework for spatio-temporal predictive modeling
Learning to identify relevant studies for systematic reviews using random forest and external information
Inferential Theory of Learning as a Conceptual Basis for Multistrategy Learning
Adaptive transformer modelling of density function for nonparametric survival analysis
Learning sample-aware threshold for semi-supervised learning
State-based episodic memory for multi-agent reinforcement learning
Machine learning in space: extending our reach
Temporal silhouette: validation of stream clustering robust to concept drift
Hierarchical Learning in Polynomial Support Vector Machines
Editorial: Human and Machine Learning
A Distance-Based Attribute Selection Measure for Decision Tree Induction
autoBOT: evolving neuro-symbolic representations for explainable low resource text classification
Incremental Learning of Linear Model Trees
Rankboost+: an improvement to Rankboost
An extended DEIM algorithm for subset selection and class identification
Algorithms for subsetting attribute values with Relief
Fully convolutional open set segmentation
Competition-Based Induction of Decision Models from Examples
An in-depth review and analysis of mode collapse in generative adversarial networks
Adaptive collaborative minority oversampling for multi-class imbalanced classification
Physics encoded blocks in residual neural network architectures for digital twin models
Sparse hierarchical regression with polynomials
A Necessary Condition for Learning from Positive Examples
Learning and Programming in Classifier Systems
On the Sample Complexity for Nonoverlapping Neural Networks
On testing transitivity in online preference learning
An improved multiclass LogitBoost using adaptive-one-vs-one
Tracking the best hyperplane with a simple budget Perceptron
Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones
Reinforcement learning in feedback control - Challenges and benchmarks from technical process control
Guest editorial: Machine learning in and for music
Unsupervised variational domain adaptation
Improving deep label noise learning with dual active label correction
Analysis of Hannan consistent selection for Monte Carlo tree search in simultaneous move games
Jaccard-constrained dense subgraph discovery
Resampling approach for cluster model selection
The effect of splitting on random forests
Cost-sensitive boosting algorithms: Do we really need them?
Prompt-based contrastive learning to combat the COVID-19 infodemic
Improved MCMC sampling methods for estimating weighted sums in Winnow with application to DNF learning
Fair and green hyperparameter optimization via multi-objective and multiple information source Bayesian optimization
Neighborhood relation-based incremental label propagation algorithm for partially labeled hybrid data
Improving text processing via adversarial low-rank adaptation
Combining Bayesian optimization and Lipschitz optimization
Incremental learning of iterated dependencies
Beyond Limits: Enhancing the Extrapolation Performance of Regression Models by Leaving the Boundary Out
The lattice structure and refinement operators for the hypothesis space bounded by a bottom clause
Reinforcement Learning for Call Admission Control and Routing under Quality of Service Constraints in Multimedia Networks
Recovering networks from distance data
Near-Optimal Reinforcement Learning in Polynomial Time
SA-CAM: Semantic-aware visual explanations for deep convolutional networks
Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers
A flexible cluster-oriented alternative clustering algorithm for choosing from the Pareto front of solutions
Embedding-based Silhouette community detection
Asymptotic stability of equilibrium points of mean shift algorithm
Scalable computational techniques for centrality metrics on temporally detailed social network
PreCoF: counterfactual explanations for fairness
Generalizing p-Laplacian: spectral hypergraph theory and a partitioning algorithm
Ordinal regression with explainable distance metric learning based on ordered sequences
Active Learning Using Arbitrary Binary Valued Queries
On the Convergence of Temporal-Difference Learning with Linear Function Approximation
Linear Least-Squares Algorithms for Temporal Difference Learning
Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned
Some Statistical-Estimation Methods for Stochastic Finite-State Transducers
Addressing data dependency in neural networks: introducing the Knowledge Enhanced Neural Network (KENN) for time series forecasting +
Book Review: Neural Network Perception for Mobile Robot Guidance by Dean A. Pomerleau. Kluwer Academic Publishers, 1993
Goal exploration augmentation via pre-trained skills for sparse-reward long-horizon goal-conditioned reinforcement learning
Beneficial and harmful explanatory machine learning
Learning Fallible Deterministic Finite Automata
Reinterpreting the Category Utility Function
Efficient Incremental Induction of Decision Trees
Inducing Multi-Level Association Rules from Multiple Relations
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events
Risk bound of transfer learning using parametric feature mapping and its application to sparse coding
OWL2Vec*: embedding of OWL ontologies
TFAS: zero-shot NAS for general time-series analysis with time-frequency aware scoring
EM, MCMC, and Chain Flipping for Structure from Motion with Unknown Correspondence
Gene Selection for Cancer Classification using Support Vector Machines
Logical reduction of metarules
Understanding CNN fragility when learning with imbalanced data
On the Stochastic Complexity of Learning Realizable and Unrealizable Rules
A new filter for deformation-invariant persistence diagram
Automated imbalanced classification via layered learning
Reversible jump attack to textual classifiers with modification reduction
RADE: resource-efficient supervised anomaly detection using decision tree-based ensemble methods
Purposive Behavior Acquisition for a Real Robot by Vision-Based Reinforcement Learning
Gradient-based causal discovery with latent variables
Low-resolution human pose estimation and action recognition via pose-driven super-resolution reconstruction
Accelerating a Gibbs sampler for variable selection on genomics data with summarization and variable pre-selection combining an array DBMS and R
Distance metric learning for graph structured data
Guest Editors' introduction: special issue of the ECML/PKDD 2014 journal track
Cost-sensitive learning based on Bregman divergences
Prioritizing the essential: A robust evaluation framework for novelty detection
Minimax PAC bounds on the sample complexity of reinforcement learning with a generative model
Sanitized clustering against confounding bias
Nettop: A light-weight network of orthogonal-plane features for image recognition
Inductive learning of robot task knowledge from raw data and online expert feedback
Heuristic search of optimal machine teaching curricula
ArithmeticGPT: empowering small-size large language models with advanced arithmetic skills
The mechanism of additive composition
Improving latent variable descriptiveness by modelling rather than ad-hoc factors
Bagging Equalizes Influence
Randomizing Outputs to Increase Prediction Accuracy
Open-set learning under covariate shift
Tensor decision trees for continual learning from drifting data streams
A bias/variance decomposition for models using collective inference
Special issue on discovery science
Learning from positive and unlabeled data: a survey
Structure in the Space of Value Functions
Multistrategy Discovery and Detection of Novice Programmer Errors
LSALSA: accelerated source separation via learned sparse coding
A Probabilistic Framework for SVM Regression and Error Bar Estimation
Imbalanced regression using regressor-classifier ensembles
A taxonomy of weight learning methods for statistical relational learning
Opportunism and Learning
Planning for potential: efficient safe reinforcement learning
Adaptive Euclidean maps for histograms: generalized Aitchison embeddings
Multi-label feature ranking with ensemble methods
Case Based Imprecision Estimates for Bayes Classifiers with the Bayesian Bootstrap
TOCOL: improving contextual representation of pre-trained language models via token-level contrastive learning
Potential-Based Algorithms in On-Line Prediction and Game Theory
Learning answer set programs with aggregates via sampling and genetic programming
Semi-supervised local Fisher discriminant analysis for dimensionality reduction
Ijuice: integer JUstIfied counterfactual explanations
The Design of Discrimination Experiments
A segmented topic model based on the two-parameter Poisson-Dirichlet process
Simplification of forest classifiers and regressors by sharing branching conditions
DOC 3 : deep one class classification using contradictions
Block-wise construction of tree-like relational features with monotone reducibility and redundancy
CaDET: interpretable parametric conditional density estimation with decision trees and forests
Probabilistic inductive constraint logic
CaCOM: customizing text-to-image diffusion models in the wild via continual active selection
Statistical Methods for Analyzing Speedup Learning Experiments
Correlated product of experts for sparse Gaussian process regression
Loda: Lightweight on-line detector of anomalies
IntelligentPooling: practical Thompson sampling for mHealth
Expected similarity estimation for large-scale batch and streaming anomaly detection
LLM-based feature generation from text for interpretable machine learning
Statistical hierarchical clustering algorithm for outlier detection in evolving data streams
Qualitative control learning can be much faster than reinforcement learning
Speculate-correct error bounds for k-nearest neighbor classifiers
Forecasting of mobile network traffic and spatio-temporal analysis using modLSTM
Conditional variance penalties and domain shift robustness
Modeling PU learning using probabilistic logic programming
Tree-based dynamic classifier chains
Histogram approaches for imbalanced data streams regression
Preference-based opponent shaping in differentiable games
User migration in blockchain-based online social networks through the lens of temporal node representation shift
Learning to Recognize Volcanoes on Venus
An Upper Bound on the Loss from Approximate Optimal-Value Functions
Learning monotone nonlinear models using the Choquet integral
Robustness and generalization
Rapid Concept Learning for Mobile Robots
Policy gradient in Lipschitz Markov Decision Processes
Forecasting short-term passenger flow via CBGC-SCI: an in-depth comparative study on Shenzhen Metro
Adaptive partitioning schemes for bipartite ranking - How to grow and prune a ranking tree
SAGA: sparse and geometry-aware non-negative matrix factorization through non-linear local embedding
Relational information gain
The Convergence of TD(lambda) for General lambda
Optimal large-scale stochastic optimization of NDCG surrogates for deep learning
Statistical topic models for multi-label document classification
Statistical Properties and Adaptive Tuning of Support Vector Machines
Learning differentiable logic programs for abstract visual reasoning
Temporal graph learning for dynamic link prediction with text in online social networks
GVFs in the real world: making predictions online for water treatment
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning
A Reply to Reich's Book Review of Exemplar-Based Knowledge Acquisition
TD-regularized actor-critic methods
Feature Selection vs Theory Reformulation: A Study of Genetic Refinement of Knowledge-based Neural Networks
Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations
Probabilistic combination of classification rules and its application to medical diagnosis
MapFlow: latent transition via normalizing flow for unsupervised domain adaptation
A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geometric Patterns
Genetic Algorithms, Operators, and DNA Fragment Assembly
Bayesian multi-instance multi-label learning using Gaussian process prior
Learning key steps to attack deep reinforcement learning agents
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
Meta-learning the invariant representation for domain generalization
Chinese character recognition with radical-structured stroke trees
An effective keyword search co-occurrence multi-layer graph mining approach