yusuke1997/dblp-id-title huggingface dataset:
Integrating Meta-Information Management and Reflection in Middleware
Dynamic Component Gluing Across Different Componentware Systems
DeepView: A Channel for Distributed Microscopy
End-to-End Transactions in Three-Tier Systems
A Reliable Multicast Protocol in Networks with Mobile Hosts
Real-Time Distributed Object Computing: Ready for Mission-Critical Embedded System Applications
Jini Technology Applied to Railway Systems
3rd International Symposium on Distributed Objects and Applications, DOA 2001, Rome, Italy, September 17-20, 2001
Middleware Mediated Transactions
A Comparison of the Basic DO Concepts in Standardization
Active COM: An Inter-Working Framework for CORBA and DCOM
Spontaneous Networking with CORBA, Jini & JavaCards in RoamX, a Mobile X-Desktop
Reliable Nested Invocation of Methods in Distributed Object-Based Systems
Formalizing Meta-Programming Techniques to Reconcile Heterogeneous Scheduling Disciplines in Open Distributed Real-Time Systems
Formal Support for the Engineering of CORBA-based Distributed Object Systems
Developing Mobile Agent Organizations: A Case Study in Digital Tourism
Mobile Code as an Enabling Technology for Service-Oriented Smartcard Middleware
Adaptability of Object Distribution Protocols Using the Disguises Model Approach
Building Mediators from Components
Surviving the Tornado: The Best Kept Secrets of R&D Success in the Internet Age
Transparent Dynamic Reconfiguration for CORBA
Integrating Capabilities into the Object Model to Protect Distributed Object Systems
Mobile CORBA
QoS-Constrained Event Communications in Distributed Virtual Environments
A Collaborative Word Processing Systems using a CORBA-Based Workflow Framework
Efficient Execution Strategies for Mobile Procedures Querying Distributed Databases
A Reflective Component-Based & Architecture Aware Framework to Manage Architecture Composition
StratOSphere: Unification of Code, Data, Location, Scope, and Mobility
Parallel Data Processing in a Distributed Object-Oriented Model
NASA Global Change Master Directory: An Implementation of Asynchronous Management Protocol in a Heterogeneous Distributed Environment
DOK-Trader: A CORBA Persistent Trader with Query Routing Facilities
Distributed Xbean Applications
The Performance of a Real-time I/O Subsystem for QoS-enabled ORB Middleware
An Adaptable Workflow System Architecture on the Internet for Electronic Commerce Applications
A Distributed Object Web-Publishing Environment using CORBA
Interoperability of Java-based Applications and SAP's Business Framework State of the Art and Desirable Developments
Component Search Service and Deployment of Distributed Applications
Que Sera Sera: The Coincidental Confluence of Economics, Business, and Collaborative Computing
Distributing Mapping Objects with the Geospatial Information Database
ADAPTATION - Algorithms to ADAPTive FAulT MonItOriNg and Their Implementation on CORBA
CORBA-based Architecture for Image Workflow in a Large Consortium of Hospitals
CORBA Solutions for Interoperability in Mobile Agent Environments
A Case Study in Testing Distributed Systems
An Object-Oriented Organic Architecture for Next Generation Intelligent Reconfigurable Mobile Networks
Load Management for Distributed Object-Oriented Environments
Enabling Flexible Cross-Version Interoperability from Distributed Services
A Framework for Policy Bindings
Policy Trading
Interpreting Lion Behaviour as Probabilistic Programs
Inferring deterministic causal relations
Faster Gaussian Summation: Theory and Experiment
A Tractable Probabilistic Model for Subset Selection
Weighing and Integrating Evidence for Stochastic Simulation in Bayesian Networks
Theoretical Foundations for Abstraction-Based Probabilistic Planning
Learning to Smooth with Bidirectional Predictive State Inference Machines
Time-Dependent Utility and Action Under Uncertainty
Lattice Particle Filters
Multi-Cost-Bounded Reachability Analysis of POMDPs
Generating Optimal Plans in Highly-Dynamic Domains
Decentralized Sensor Fusion with Distributed Particle Filters
Bayesian Optimisation of Gated Bayesian Networks for Algorithmic Trading
The optimal noise in noise-contrastive learning is not what you think
Guided Deep Kernel Learning
A Transformational Characterization of Equivalent Bayesian Network Structures
Towards Flatter Loss Surface via Nonmonotonic Learning Rate Scheduling
Multiple decision trees
Solution Methods for Constrained Markov Decision Process with Continuous Probability Modulation
Probabilistic Constraint Satisfaction with Non-Gaussian Noise
UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, Montreal, Quebec, Canada, August 18-20, 1995
Portfolio Allocation for Bayesian Optimization
Probabilistic Exploration in Planning while Learning
Knowledge Combination in Graphical Multiagent Models
The Assumptions Behind Dempster's Rule
Structure-Based Causes and Explanations in the Independent Choice Logic
Optimizing Language Models for Human Preferences is a Causal Inference Problem
Relative Loss Bounds for On-line Density Estirnation with the Exponential Family of Distributions
Generating and Sampling Orbits for Lifted Probabilistic Inference
Functional Wasserstein Variational Policy Optimization
Hallucinated adversarial control for conservative offline policy evaluation
Inference for Optimal Linear Treatment Regimes in Personalized Decision-making
Probabilistic reconciliation of mixed-type hierarchical time series
Interpreting and Using CPDAGs With Background Knowledge
Active Learning with Expert Advice
Dynamic relocation in ridesharing via fixpoint construction
Optimal Transport for Probabilistic Circuits
Decentralized Online Learning in General-Sum Stackelberg Games
Bayesian Multicategory Support Vector Machines
On a Class of Bias-Amplifying Variables that Endanger Effect Estimates
Multi-Relational Structural Entropy
Local Utility Elicitation in GAI Models
UAI 2010, Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, July 8-11, 2010
On the Use of Skeletons when Learning in Bayesian Networks
KBlrn: End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features
Guaranteed Scalable Learning of Latent Tree Models
CSS: Contrastive Semantic Similarities for Uncertainty Quantification of LLMs
Can mean field control (mfc) approximate cooperative multi agent reinforcement learning (marl) with non-uniform interaction?
Learning Determinantal Point Processes
Metric Learning in an RKHS
Informative Synthetic Data Generation for Thorax Disease Classification
Lifted Relational Variational Inference
Problem-dependent Regret Bounds for Online Learning with Feedback Graphs
Discriminative Learning via Semidefinite Probabilistic Models
Predictive State Representations: A New Theory for Modeling Dynamical Systems
Independence Concepts for Convex Sets of Probabilities
Direct and Indirect Effects
Graph Feedback Bandits with Similar Arms
Escaping from zero gradient: Revisiting action-constrained reinforcement learning via Frank-Wolfe policy optimization
Evaluating probabilistic reasoning systems
Characterizing the Set of Coherent Lower Previsions with a Finite Number of Constraints or Vertices
Offline Reward Perturbation Boosts Distributional Shift in Online RL
Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks
Convergence Rates for Greedy Kaczmarz Algorithms, and Randomized Kaczmarz Rules Using the Orthogonality Graph
On Testing Whether an Embedded Bayesian Network Represents a Probability Model
Parallelizing Probabilistic Inference: Some Early Explorations
Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles
Intracluster Moves for Constrained Discrete-Space MCMC
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors
Equitable Partitions of Concave Free Energies
Learning Time Series Segmentation Models from Temporally Imprecise Labels
Value-Directed Sampling Methods for POMDPs
Probabilistic DAG search
MindFlayer SGD: Efficient Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times
Risk Bounds for Low Cost Bipartite Ranking
Testing for Conditional Mean Independence with Covariates through Martingale Difference Divergence
A Submodular-supermodular Procedure with Applications to Discriminative Structure Learning
On revising fuzzy belief bases
UAI '04, Proceedings of the 20th Conference in Uncertainty in Artificial Intelligence, Banff, Canada, July 7-11, 2004
Automating Computer Bottleneck Detection with Belief Nets
Stochastic Variational Inference for Dynamic Correlated Topic Models
Plackett-Luce regression: A new Bayesian model for polychotomous data
Directed Cyclic Graphical Representations of Feedback Models
Sparse linear networks with a fixed butterfly structure: theory and practice
Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection
Efficient Planning Under Uncertainty with Incremental Refinement
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions
Finding Invariant Predictors Efficiently via Causal Structure
Improved Densification of One Permutation Hashing
Conditioning Algorithms for Exact and Approximate Inference in Causal Networks
Asymptotically Exact, Embarrassingly Parallel MCMC
Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream
Accelerating training of batch normalization: A manifold perspective
Randomized Iterative Algorithms for Fisher Discriminant Analysis
Are You Doing Better Than Random Guessing? A Call for Using Negative Controls When Evaluating Causal Discovery Algorithms
Dynamic programming in in uence diagrams with decision circuits
Learning proposals for probabilistic programs with inference combinators
Exploratory Model Building
A New Pruning Method for Solving Decision Trees and Game Trees
A Differential Semantics of Lazy AR Propagation
Continuous Time Bayesian Networks
Applying Discrete PCA in Data Analysis
An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering
Learning binary multi-scale games on networks
Decision Principles to Justify Carnap's Updating Method and to Suggest Corrections
Marginal MAP estimation for inverse RL under occlusion with observer noise
Extremely Greedy Equivalence Search
Zeroth Order Non-convex optimization with Dueling-Choice Bandits
Targeted Reduction of Causal Models
Probabilistic Arc Consistency: A Connection between Constraint Reasoning and Probabilistic Reasoning
Testing Implication of Probabilistic Dependencies
Noisy Search with Comparative Feedback
Nonparametric Bayes Pachinko Allocation
Fitting Graphical Interaction Models to Multivariate Time Series
Structured Message Passing
Utility Elicitation as a Classification Problem
The impact of overconfidence bias on practical accuracy of Bayesian network models: an empirical study
Symbolic Probabilistic Inference with Continuous Variables
Uncertainty in minimum cost multicuts for image and motion segmentation
Exploring the loss landscape in neural architecture search
Welldefined Decision Scenarios
Revisiting DP-Means: fast scalable algorithms via parallelism and delayed cluster creation
A Lagrangian Perspective on Latent Variable Generative Models
Evidence-invariant Sensitivity Bounds
Beyond Log-Supermodularity: Lower Bounds and the Bethe Partition Function
High-dimensional Joint Sparsity Random Effects Model for Multi-task Learning
Asymptotic Model Selection for Directed Networks with Hidden Variables
A Theoretical Framework for Context-Sensitive Temporal Probability Model Construction with Application to Plan Projection
Dirichlet Continual Learning: Tackling Catastrophic Forgetting in NLP
Structured sparsification with joint optimization of group convolution and channel shuffle
Greedy equivalence search in the presence of latent confounders
Learning Choice Functions with Gaussian Processes
Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity
Observation Subset Selection as Local Compilation of Performance Profiles
Learning to reason about contextual knowledge for planning under uncertainty
Probabilistic State-Dependent Grammars for Plan Recognition
Approximate inference on planar graphs using Loop Calculus and Belief Propagation
A Simple Online Algorithm for Competing with Dynamic Comparators
Toward Practical N2 Monte Carlo: the Marginal Particle Filter
Hybrid Processing of Beliefs and Constraints
Layering-MCMC for Structure Learning in Bayesian Networks
Attention-Sensitive Alerting
Using Autodiff to Estimate Posterior Moments, Marginals and Samples
Default reasoning and the transferable belief model
Stable Policy Optimization via Off-Policy Divergence Regularization
RISAN: Robust instance specific deep abstention network
On the Semantics and Automated Deduction for PLFC, a Logic of Possibilistic Uncertainty and Fuzziness
Hierarchical POMDP Controller Optimization by Likelihood Maximization
A Convex Formulation for Learning Task Relationships in Multi-Task Learning
Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings
Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting
"Say EM" for Selecting Probabilistic Models for Logical Sequences
Scalable and robust tensor ring decomposition for large-scale data
Generating decision structures and causal explanations for decision making
From Conditional Oughts to Qualitative Decision Theory
Sound Heuristic Search Value Iteration for Undiscounted POMDPs with Reachability Objectives
An Axiomatic Approach to Robustness in Search Problems with Multiple Scenarios
Structure Learning Constrained by Node-Specific Degree Distribution
Identifiability of total effects from abstractions of time series causal graphs
Label-wise Aleatoric and Epistemic Uncertainty Quantification
NeuroBE: Escalating neural network approximations of Bucket Elimination
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression
Accelerating MCMC via Parallel Predictive Prefetching
Last-iterate Convergence Separation between Extra-gradient and Optimism in Constrained Periodic Games
Parametric Return Density Estimation for Reinforcement Learning
A Framework for Decision-Theoretic Planning I: Combining the Situation Calculus, Conditional Plans, Probability and Utility
Amortized Variational Inference: When and Why?
The Inductive Logic of Information Systems
Value Directed Exploration in Multi-Armed Bandits with Structured Priors
Permutation-Based Causal Structure Learning with Unknown Intervention Targets
DeepGD3: Unknown-Aware Deep Generative/Discriminative Hybrid Defect Detector for PCB Soldering Inspection
Towards Minimax Optimality of Model-based Robust Reinforcement Learning
Properties of Bayesian Belief Network Learning Algorithms
Graph-based Clustering under Differential Privacy
Filtered Fictitious Play for Perturbed Observation Potential Games and Decentralised POMDPs
A Sampling-Based Approach to Computing Equilibria in Succinct Extensive-Form Games
How to Elicit Many Probabilities
Local Expression Languages for Probabilistic Dependence
Generating adversarial examples with graph neural networks
MAA*: A Heuristic Search Algorithm for Solving Decentralized POMDPs
Novel Bernstein-like Concentration Inequalities for the Missing Mass
The Indian Buffet Hawkes Process to Model Evolving Latent Influences
Combinatorial Bayesian optimization with random mapping functions to convex polytopes
On the Role of Generalization in Transferability of Adversarial Examples
Reinforcement learning in many-agent settings under partial observability
A Logic for Default Reasoning About Probabilities
Context-specific approximation in probabilistic inference
Mining Associated Text and Images with Dual-Wing Harmoniums
A New Look at Causal Independence
A Discovery Algorithm for Directed Cyclic Graphs
Online learning with Erdos-Renyi side-observation graphs
Counterfactual Normalization: Proactively Addressing Dataset Shift Using Causal Mechanisms
Contrast-CAT: Contrasting Activations for Enhanced Interpretability in Transformer-based Text Classifiers
Compressed Constraints in Probabilistic Logic and Their Revision
Non Parametric Graph Learning for Bayesian Graph Neural Networks
From Ordinary Differential Equations to Structural Causal Models: the deterministic case
Decentralized Two-Sided Bandit Learning in Matching Market
Probabilistic Models For Joint Clustering And Time-Warping Of Multidimensional Curves
Publishing Number of Walks and Katz Centrality under Local Differential Privacy
Advances in Probabilistic Reasoning
Lifted Tree-Reweighted Variational Inference
Indirectly Visible Bayesian Student Models
Stochastic sensitivity analysis using fuzzy influence diagrams
Submodular Bandit Problem Under Multiple Constraints
Efficient Interactive Maximization of BP and Weakly Submodular Objectives
PAC-learning Bounded Tree-width Graphical Models
High-probability bounds for robust stochastic Frank-Wolfe algorithm
Noise Contrastive Priors for Functional Uncertainty
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation
Pre-Selection of Independent Binary Features: An Application to Diagnosing Scrapie in
Probabilistic Assumption-Based Reasoning
Improved Asymmetric Locality Sensitive Hashing (ALSH) for Maximum Inner Product Search (MIPS)
An Empirical Study of the Simplest Causal Prediction Algorithm
Improving Gradient Estimation by Incorporating Sensor Data
SMuCo: Reinforcement Learning for Visual Control via Sequential Multi-view Total Correlation
Robust Metric Learning by Smooth Optimization
Efficient online inference for nonparametric mixture models
Communication efficient parallel reinforcement learning
Tractable Inference for Complex Stochastic Processes
Unknown mixing times in apprenticeship and reinforcement learning
Robust expected information gain for optimal Bayesian experimental design using ambiguity sets
On Hardware-efficient Inference in Probabilistic Circuits
Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks Using a Polynomial Number of Score Evaluations
Time-Critical Action: Representations and Application
Faster non-convex federated learning via global and local momentum
Hierarchical learning of grids of microtopics
The Shrinkage-Delinkage Trade-off: an Analysis of Factorized Gaussian Approximations for Variational Inference
Updating Sets of Probabilities
Tail Sensitivity Analysis in Bayesian Networks
Algorithm Portfolio Design: Theory vs. Practice
Models and Selection Criteria for Regression and Classification
Invariant Causal Prediction with Local Models
Policy-contingent abstraction for robust robot control
Hierarchical learning of Hidden Markov Models with clustering regularization
Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm
KrADagrad: Kronecker approximation-domination gradient preconditioned stochastic optimization
Streaming Nonlinear Bayesian Tensor Decomposition
Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions
Unsupervised Activity Discovery and Characterization From Event-Streams
Towards Threshold Invariant Fair Classification
Representing and Combining Partially Specified CPTs
Approximate Relative Value Learning for Average-reward Continuous State MDPs
Learning the Structure of Sum-Product Networks via an SVD-based Algorithm
Selective Blocking for Message-Passing Neural Networks on Heterophilic Graphs
Shift-Invariance Sparse Coding for Audio Classification
UAI '86: Proceedings of the Second Annual Conference on Uncertainty in Artificial Intelligence, University of Pennsylvania, Philadelphia, PA, USA, August 8-10, 1986
Efficient Inference on Generalized Fault Diagrams
Bayesian Hyperparameter Optimization for Ensemble Learning
Can Uncertainty Management be Realized in a Finite Totally Ordered Probability Algebra?
FHHOP: A Factored Hybrid Heuristic Online Planning Algorithm for Large POMDPs
From Influence Diagrams to Multi-operator Cluster DAGs
Probabilistic Belief Change: Expansion, Conditioning and Constraining
Noisy adversarial representation learning for effective and efficient image obfuscation
Budgeted Online Collective Inference
Variational MCMC
Bayesian Pseudo-Coresets via Contrastive Divergence
Identification and Estimation of Causal Effects Defined by Shift Interventions
Visual Causal Feature Learning
Making Sensitivity Analysis Computationally Efficient
Bridging Heterogeneous Domains With Parallel Transport For Vision and Multimedia Applications
Adversarial Inverse Optimal Control for General Imitation Learning Losses and Embodiment Transfer
Active Diagnosis via AUC Maximization: An Efficient Approach for Multiple Fault Identification in Large Scale, Noisy Networks
A Bayesian Method Reexamined
On Constant Regret for Low-Rank MDPs
Finite-sample Bounds for Marginal MAP
Lagrangian Decomposition for Neural Network Verification
Constructing the Pignistic Probability Function in a Context of Uncertainty
Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility
Bayesian Multitask Learning with Latent Hierarchies
Belief Update in CLG Bayesian Networks With Lazy Propagation
Decision making with interval influence diagrams
Learning Mixtures of DAG Models
A Target Classification Decision Aid
A Reason Maintenance System Dealing with Vague Data
STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning
Bethe Projections for Non-Local Inference
Evaluation of the Causal Effect of Control Plans in Nonrecursive Structural Equation Models
Automorphism Groups of Graphical Models and Lifted Variational Inference
Mixtures of Gaussians and Minimum Relative Entropy Techniques for Modeling Continuous Uncertainties
The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data
Stability of Causal Inference
Empirical Probabilities in Monadic Deductive Databases
Detecting low-complexity unobserved causes
Offline policy optimization with eligible actions
BayLIME: Bayesian local interpretable model-agnostic explanations
Known unknowns: Learning novel concepts using reasoning-by-elimination
Continuous Value Function Approximation for Sequential Bidding Policies
Efficient Observation Selection in Probabilistic Graphical Models Using Bayesian Lower Bounds
Efficient Neural Network Verification with Exactness Characterization
DF 2 : Distribution-Free Decision-Focused Learning
Fast Exact Inference for Recursive Cardinality Models
Independence with Lower and Upper Probabilities
UAI '87: Proceedings of the Third Annual Conference on Uncertainty in Artificial Intelligence, Seattle, WA, USA, July 10-12, 1987
Dueling Posterior Sampling for Preference-Based Reinforcement Learning
MaskAAE: Latent space optimization for Adversarial Auto-Encoders
Determining the Number of Non-Spurious Arcs in a Learned DAG Model: Investigation of a Bayesian and a Frequentist Approach
Shootout-89, An Evaluation of Knowledge-Based Weather Forecasting Systems
Why is diagnosis using belief networks insensitive to imprecision in probabilities?
GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data
Clustered Fused Graphical Lasso
Simulation-Free Differential Dynamics Through Neural Conservation Laws
Probabilistic Theorem Proving
Active metric learning and classification using similarity queries
Quasi-Bayesian Strategies for Efficient Plan Generation: Application to the Planning to Observe Problem
Dealing with Uncertainty in Situation Assessment: towards a Symbolic Approach
Continuous Time Dynamic Topic Models
Exploiting functional dependencies in qualitative probabilistic reasoning
Stochastic L-BFGS Revisited: Improved Convergence Rates and Practical Acceleration Strategies
Web-Based Question Answering: A Decision-Making Perspective
Probabilistic Program Abstractions
Enhancing Treatment Effect Estimation: A Model Robust Approach Integrating Randomized Experiments and External Controls using the Double Penalty Integration Estimator
Byzantine-tolerant distributed multiclass sparse linear discriminant analysis
Control of problem solving: principles and architecture