yusuke1997/dblp-id-title huggingface dataset:
Consistent estimation of small masses in feature sampling
Optimal Learning Rates for Localized SVMs
Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data
XAI Beyond Classification: Interpretable Neural Clustering
Scalable Approximations for Generalized Linear Problems
Using Local Dependencies within Batches to Improve Large Margin Classifiers
More Is Better: Large Scale Partially-supervised Sentiment Classication
A Tight Bound of Hard Thresholding
SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition
Multi-Task Dynamical Systems
Maximum Margin Temporal Clustering
Achieving Optimal Misclassification Proportion in Stochastic Block Models
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions
Consistent Feature Selection for Pattern Recognition in Polynomial Time
A projected semismooth Newton method for a class of nonconvex composite programs with strong prox-regularity
Generalization Error Bounds for Bayesian Mixture Algorithms
Distributed Algorithms for Topic Models
Adaptive Bandits: Towards the best history-dependent strategy
Variational Learning of Inducing Variables in Sparse Gaussian Processes
Dynamic Control of Stochastic Evolution: A Deep Reinforcement Learning Approach to Adaptively Targeting Emergent Drug Resistance
Subspace Learning with Partial Information
Bayesian inference for statistical abduction using Markov chain Monte Carlo
Optimal Bipartite Network Clustering
Generalized probabilistic principal component analysis of correlated data
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions
On the asymptotic normality of an estimate of a regression functional
Sparse Tensor Additive Regression
Bounded Kernel-Based Online Learning
Efficient Feature Selection via Analysis of Relevance and Redundancy
Deep Learning for Efficient Discriminative Parsing
Interactive Algorithms: Pool, Stream and Precognitive Stream
Unfolding-Model-Based Visualization: Theory, Method and Applications
Rounding-based Moves for Semi-Metric Labeling
DALEX: Explainers for Complex Predictive Models in R
Group SLOPE Penalized Low-Rank Tensor Regression
Learning Evaluation Functions to Improve Optimization by Local Search
Scalable Approximate MCMC Algorithms for the Horseshoe Prior
Learning Control Knowledge for Forward Search Planning
On the Concentration of the Minimizers of Empirical Risks
Learning with Mixtures of Trees
Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps
Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD
Kernel Partial Least Squares is Universally Consistent
Foolish Crowds Support Benign Overfitting
An $\ell_{\infty}$ Eigenvector Perturbation Bound and Its Application
A Numerical Measure of the Instability of Mapper-Type Algorithms
DataWig: Missing Value Imputation for Tables
PAC optimal MDP planning with application to invasive species management
Diffusion Bridge Mixture Transports, Schrödinger Bridge Problems and Generative Modeling
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning
Spectral Chinese Restaurant Processes: Nonparametric Clustering Based on Similarities
Model-Preserving Sensitivity Analysis for Families of Gaussian Distributions
Knowledge Graph Completion via Complex Tensor Factorization
Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction
Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection in Genomic Data
Binarsity: a penalization for one-hot encoded features in linear supervised learning
A Generalized Path Integral Control Approach to Reinforcement Learning
DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python
Strong Consistency, Graph Laplacians, and the Stochastic Block Model
MedLDA: maximum margin supervised topic models
Orange: data mining toolbox in python
Sequential Event Prediction with Association Rules
Tree Decomposition for Large-Scale SVM Problems
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Sparse Higher-Order Principal Components Analysis
An Efficient Two Step Algorithm for High Dimensional Change Point Regression Models Without Grid Search
MALTS: Matching After Learning to Stretch
Union of Low-Rank Tensor Spaces: Clustering and Completion
Fast Kernel ICA using an Approximate Newton Method
Neural Feature Learning in Function Space
On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling
Handling Sparsity via the Horseshoe
Local and global sparse Gaussian process approximations
A distributed block coordinate descent method for training l1 regularized linear classifiers
Learning Nearest-Neighbor Quantizers from Labeled Data by Information Loss Minimization
Kernel Method for Persistence Diagrams via Kernel Embedding and Weight Factor
Sampling Techniques for the Nystrom Method
CoCoA: A General Framework for Communication-Efficient Distributed Optimization
On-Line Sequential Bin Packing
Fast Variational Mode-Seeking
Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback
Bi-Level Path Following for Cross Validated Solution of Kernel Quantile Regression
Probabilistic Iterative Methods for Linear Systems
Multivariate Soft Rank via Entropy-Regularized Optimal Transport: Sample Efficiency and Generative Modeling
Low-Rank Kernel Learning with Bregman Matrix Divergences
Revisiting Bayesian blind deconvolution
An Importance Weighted Feature Selection Stability Measure
Sparse Projection Oblique Randomer Forests
Boosted Classification Trees and Class Probability/Quantile Estimation
Universality, Characteristic Kernels and RKHS Embedding of Measures
Effective Ways to Build and Evaluate Individual Survival Distributions
Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams
A Kernel Two-Sample Test for Functional Data
Inference for a Large Directed Acyclic Graph with Unspecified Interventions
Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing
Reverse Engineering of Asynchronous Boolean Networks
Minimax Rates of Estimation for Sparse PCA in High Dimensions
Iterative reweighted algorithms for matrix rank minimization
Dimension Estimation Using Random Connection Models
Consistent Semi-Supervised Graph Regularization for High Dimensional Data
SVM versus Least Squares SVM
Clustering with Semidefinite Programming and Fixed Point Iteration
DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization
A Correlation Clustering Approach to Link Classification in Signed Networks
Variational Multinomial Logit Gaussian Process
Revisiting the Nystrom Method for Improved Large-scale Machine Learning
Hamilton-Jacobi equations on graphs with applications to semi-supervised learning and data depth
Robust Discriminative Clustering with Sparse Regularizers
Implicit Langevin Algorithms for Sampling From Log-concave Densities
Sparse NMF with Archetypal Regularization: Computational and Robustness Properties
Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm
Switch-Reset Models : Exact and Approximate Inference
Asymptotics in Empirical Risk Minimization
An Anticorrelation Kernel for Subsystem Training in Multiple Classifier Systems
Continuous-Time Birth-Death MCMC for Bayesian Regression Tree Models
Convergence Rates of a Class of Multivariate Density Estimation Methods Based on Adaptive Partitioning
Under-bagging Nearest Neighbors for Imbalanced Classification
Parametric Herding
Learning Conditional Generative Models for Phase Retrieval
On the Convergence Rates of Policy Gradient Methods
Causal discovery with continuous additive noise models
Spectral learning of multivariate extremes
Estimation of Generating Processes of Strings Represented with Patterns and Refinements
An asymptotic analysis of distributed nonparametric methods
Variational Inference for Computational Imaging Inverse Problems
q-Learning in Continuous Time
Multi-view Collaborative Gaussian Process Dynamical Systems
New learning methods for supervised and unsupervised preference aggregation
Multicategory large-margin unified machines
On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines
Data-dependent margin-based generalization bounds for classification
Factorized Orthogonal Latent Spaces
Natural Language Processing (Almost) from Scratch
Compact Convex Projections
Scaling Speech Technology to 1, 000+ Languages
The Representational Power of Discrete Bayesian Networks
GenSVM: A Generalized Multiclass Support Vector Machine
Optimization-based Causal Estimation from Heterogeneous Environments
Latent Force Models
Evaluation Method for Feature Rankings and their Aggregations for Biomarker Discovery
A novel M-estimator for robust PCA
Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation
Consistency of the Group Lasso and Multiple Kernel Learning
When Locally Linear Embedding Hits Boundary
Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures
Automatic Differentiation in Machine Learning: a Survey
Learning Rates for Q-learning
BudgetedSVM: a toolbox for scalable SVM approximations
Over-parameterized Deep Nonparametric Regression for Dependent Data with Its Applications to Reinforcement Learning
Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition
Invariant and Equivariant Reynolds Networks
Characterization, Stability and Convergence of Hierarchical Clustering Methods
Multi-task Learning for Recommender System
Inducing Partially Observable Markov Decision Processes
On the convergence of maximum variance unfolding
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
Distributed Minimum Error Entropy Algorithms
Parallelizing exploration-exploitation tradeoffs in Gaussian process bandit optimization
Edge Sampling Using Local Network Information
Exploiting Unrelated Tasks in Multi-Task Learning
Learning Approximate Sequential Patterns for Classification
JCLAL: A Java Framework for Active Learning
Building Support Vector Machines with Reduced Classifier Complexity
Distributions of angles in random packing on spheres
A Strategy for Making Predictions Under Manipulation
Hierarchical Convex NMF for Clustering Massive Data
Learning the Kernel Matrix with Semidefinite Programming
Query Transformations for Improving the Efficiency of ILP Systems
Empirical Bernstein Boosting
Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs
The Relationship Between Agnostic Selective Classification, Active Learning and the Disagreement Coefficient
Certifiably Optimal Low Rank Factor Analysis
Mapping kernels for infinite mapping systems
Nonparametric Risk Bounds for Time-Series Forecasting
Fused Lasso Approach in Regression Coefficients Clustering - Learning Parameter Heterogeneity in Data Integration
Sparse Boosting
Clustering on the Unit Hypersphere using von Mises-Fisher Distributions
Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data
Probability Product Kernels
Unlabeled Data Help in Graph-Based Semi-Supervised Learning: A Bayesian Nonparametrics Perspective
Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions
Overlearning in Marginal Distribution-Based ICA: Analysis and Solutions
Distributed Learning, Communication Complexity and Privacy
Reproducing kernel Hilbert C*-module and kernel mean embeddings
Differentially Private Online Learning
Microcanonical Hamiltonian Monte Carlo
Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations
Online Rank Aggregation
Variational Particle Approximations
Exact Bayesian structure learning from uncertain interventions
Self-paced Multi-view Co-training
Sparse GCA and Thresholded Gradient Descent
Model Selection in Bayesian Neural Networks via Horseshoe Priors
Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm
Incremental Support Vector Learning: Analysis, Implementation and Applications
Permuted and Unlinked Monotone Regression in R^d: an approach based on mixture modeling and optimal transport
On Relevant Dimensions in Kernel Feature Spaces
Feature Extraction for Machine Learning: Logic-Probabilistic Approach
Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure
Divide and conquer kernel ridge regression: a distributed algorithm with minimax optimal rates
Learning the Kernel with Hyperkernels
Dropout: a simple way to prevent neural networks from overfitting
A Unified Framework for Random Forest Prediction Error Estimation
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits
PAMI: An Open-Source Python Library for Pattern Mining
An Autoregressive Approach to Nonparametric Hierarchical Dependent Modeling
Learning Attribute-weighted Voter Model over Social Networks
Prediction and clustering in signed networks: a local to global perspective
Model Selection: Beyond the Bayesian/Frequentist Divide
A Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion
Modeling annotator expertise: Learning when everybody knows a bit of something
Interpretable Classification of Categorical Time Series Using the Spectral Envelope and Optimal Scalings
Higher-Order Spectral Clustering Under Superimposed Stochastic Block Models
Convex Structure Learning in Log-Linear Models: Beyond Pairwise Potentials
Stress functions for nonlinear dimension reduction, proximity analysis, and graph drawing
Coherence Functions for Multicategory Margin-based Classification Methods
Cauchy-Schwarz Regularized Autoencoder
Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning
PaLM: Scaling Language Modeling with Pathways
An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization
Learning Sparse Markov Network Structure via Ensemble-of-Trees Models
Ground metric learning
Loss Control with Rank-one Covariance Estimate for Short-term Portfolio Optimization
Efficient Collapsed Gibbs Sampling for Latent Dirichlet Allocation
Lifted coordinate descent for learning with trace-norm regularization
Multiclass Anomaly Detector: the CS++ Support Vector Machine
Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning
A Tutorial on Conformal Prediction
Ramp loss linear programming support vector machine
Gibbs max-margin topic models with data augmentation
ICML Exploration & Exploitation Challenge: Keep it simple!
Adaptive sampling for large scale boosting
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters
Learning trees from strings: a strong learning algorithm for some context-free grammars
Breaking the Curse of Dimensionality with Convex Neural Networks
Short-term Sparse Portfolio Optimization Based on Alternating Direction Method of Multipliers
Causal Graph Based Decomposition of Factored MDPs
Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization
Classification of Imbalanced Data with a Geometric Digraph Family
Selection by Prediction with Conformal p-values
Undercomplete Blind Subspace Deconvolution
Forward Basis Selection for Sparse Approximation over Dictionary
KL-UCB-Switch: Optimal Regret Bounds for Stochastic Bandits from Both a Distribution-Dependent and a Distribution-Free Viewpoints
Sparse factor analysis for learning and content analytics
Classification with Incomplete Data Using Dirichlet Process Priors
Robust Reinforcement Learning with Bayesian Optimisation and Quadrature
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting
On Generalizations of Some Distance Based Classifiers for HDLSS Data
The Kernel Path in Kernelized LASSO
Distance Metric Learning with Eigenvalue Optimization
Bringing the Illusion of Reality Inside Museums - A Methodological Proposal for an Advanced Museology Using Holographic Showcases
Artificial Intelligence in Retail Marketing: Research Agenda Based on Bibliometric Reflection and Content Analysis (2000-2023)
ICT Validation in Logistics Processes: Improvement of Distribution Processes in a Goods Sector Company
Audio Watermarking System in Real-Time Applications
Security Enhancement in Smart Logistics with Blockchain Technology: A Home Delivery Use Case
Relative Quality and Popularity Evaluation of Multilingual Wikipedia Articles
Interactive Spatiotemporal Analysis of Oil Spills Using Comap in North Dakota
CAMBSRec: A Context-Aware Multi-Behavior Sequential Recommendation Model
Tourist Flow Prediction Based on GA-ACO-BP Neural Network Model
Multimodal Interaction of Contextual and Non-Contextual Sound and Haptics in Virtual Simulations
Towards a Better Integration of Fuzzy Matches in Neural Machine Translation through Data Augmentation
A Proposed Business Intelligent Framework for Recommender Systems
DFPoLD: A Hard Disk Failure Prediction on Low-Quality Datasets
Strategy for Precopy Live Migration and VM Placement in Data Centers Based on Hybrid Machine Learning
Federated Secure Computing
Using Collaborative Tagging for Text Classification: From Text Classification to Opinion Mining
A Survey of Deep Learning for Data Caching in Edge Network
Big Data Management with Incremental K-Means Trees-GPU-Accelerated Construction and Visualization
Tree-Based Algorithm for Stable and Efficient Data Clustering
Information Technology Governance for Higher Education Institutions: A Multi-Country Study
Computer Vision and Machine Learning for Tuna and Salmon Meat Classification
Reinforcement Learning in Education: A Literature Review
Social Media Adoption by Health Professionals: A TAM-Based Study
Advancing the Direction of Health Information Management in Greek Public Hospitals: Theoretical Directions and Methodological Implications for Sharing Information in order to Obtain Decision-Making
Adopting Business Intelligence Techniques in Healthcare Practice
Using the Unity Game Engine to Develop a 3D Simulated Ecological System Based on a Predator-Prey Model Extended by Gene Evolution
Clinical Text Classification for Tuberculosis Diagnosis Using Natural Language Processing and Deep Learning Model with Statistical Feature Selection Technique
Using Random Ordering in User Experience Testing to Predict Final User Satisfaction
Should We Be Concerned about How Information Privacy Concerns Are Measured in Online Contexts? A Systematic Review of Survey Scale Development Studies
Hyperparameter Tuning for Machine Learning Algorithms Used for Arabic Sentiment Analysis
Scalable Interactive Visualization for Connectomics
Using Introspection to Collect Provenance in R
Evaluation Tools to Appraise Social Media and Mobile Applications
Factors That Affect the Usage Intention of Virtual Learning Objects by College Students
EduTubers's Pedagogical Best Practices and Their Theoretical Foundation
ChatGPT in Education: Empowering Educators through Methods for Recognition and Assessment
Fashion Recommendation Systems, Models and Methods: A Review
Optimization of Obstructive Sleep Apnea Management: Novel Decision Support via Unsupervised Machine Learning
Review of Kalah Game Research and the Proposition of a Novel Heuristic-Deterministic Algorithm Compared to Tree-Search Solutions and Human Decision-Making
Human-Computer Interaction in Digital Mental Health
Using Artificial Intelligence-Based Tools to Improve the Literature Review Process: Pilot Test with the Topic "Hybrid Meat Products"
Towards A Taxonomy of Uncertainties: Analysing Sources of Spatio-Temporal Uncertainty on the Example of Non-Standard German Corpora
Blockchain Propels Tourism Industry - An Attempt to Explore Topics and Information in Smart Tourism Management through Text Mining and Machine Learning
Designing a Situational Awareness Information Display: Adopting an Affordance-Based Framework to Amplify User Experience in Environmental Interaction Design
A Framework for Antecedents to Health Information Systems Uptake by Healthcare Professionals: An Exploratory Study of Electronic Medical Records
Convolutional Neural Networks for Human Activity Recognition Using Body-Worn Sensors
Statistical Deadband: A Novel Approach for Event-Based Data Reporting
The Mappability of Clinical Real-World Data of Patients with Melanoma to Oncological Fast Healthcare Interoperability Resources (FHIR) Profiles: A Single-Center Interoperability Study
Information and Communication Technologies in Primary Education: Teachers' Perceptions in Greece
Enhancing Clinical Decision Support for Precision Medicine: A Data-Driven Approach
Non-Invasive Diagnostic Approach for Diabetes Using Pulse Wave Analysis and Deep Learning
Enhancing Foreign Speakers' Satisfaction in Learning Indonesian Language with a Gamified Multiplatform Approach
Translation Quality and Error Recognition in Professional Neural Machine Translation Post-Editing
Evaluating Awareness and Perception of Botnet Activity within Consumer Internet-of-Things (IoT) Networks
Acknowledgement to Reviewers of Informatics in 2019
Chatbot Technology Use and Acceptance Using Educational Personas
Exploring Immersive Learning Experiences: A Survey
Multidimensional Data Exploration by Explicitly Controlled Animation
A Scientometric Study of the Stylometric Research Field
Determinants of ThaiMOOC Engagement: A Longitudinal Perspective on Adoption to Continuance
Adoption of Large-Scale Scrum Practices through the Use of Management 3.0
Designing a Patient Outcome Clinical Assessment Tool for Modified Rankin Scale: "You Feel the Same Way Too"
A Machine Learning Python-Based Search Engine Optimization Audit Software
Thermal-Signature-Based Sleep Analysis Sensor
Exploiting Past Users' Interests and Predictions in an Active Learning Method for Dealing with Cold Start in Recommender Systems
Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation
Visualizing 3D Terrain, Geo-Spatial Data, and Uncertainty
Preparation for Working in a Knowledge-Based Society: New Zealand Student Nurses' Use of Social Media
Choosing a Model for eConsult Specialist Remuneration: Factors to Consider
Machine Learning Applied to the Analysis of Prolonged COVID Symptoms: An Analytical Review
Smartphone Usage before and during COVID-19: A Comparative Study Based on Objective Recording of Usage Data
Prompt Design through ChatGPT's Zero-Shot Learning Prompts: A Case of Cost-Sensitive Learning on a Water Potability Dataset
Social Media and Social Support: A Framework for Patient Satisfaction in Healthcare
A New Co-Evolution Binary Particle Swarm Optimization with Multiple Inertia Weight Strategy for Feature Selection
The Nexus between Business Analytics Capabilities and Knowledge Orientation in Driving Business Model Innovation: The Moderating Role of Industry Type
SSL-SurvFormer: A Self-Supervised Learning and Continuously Monotonic Transformer Network for Missing Values in Survival Analysis
Reinforcement Learning for Predictive Analytics in Smart Cities
Ambient Assisted Living for Improvement of Health and Quality of Life - A Special Issue of the Journal of Informatics
Design Requirements of Breast Cancer Symptom-Management Apps
Proposal for a Standard Architecture for the Integration of Clinical Information Systems in a Complex Hospital Environment
Designing towards the Unknown: Engaging with Material and Aesthetic Uncertainty
Fire in the Operating Room: Use of Mixed Reality Simulation with Nurse Anesthesia Students
Research Trends in the Use of Machine Learning Applied in Mobile Networks: A Bibliometric Approach and Research Agenda
A Comparative Study of Interaction Time and Usability of Using Controllers and Hand Tracking in Virtual Reality Training
Ubiquitous Learning Architecture to Enable Learning Path Design across the Cumulative Learning Continuum