KDD 2026 - Personalizing Marketplace Policies with Competing Objectives and Constrained Experiments @TheOfficialACM
KDD 2026 - Personalizing Marketplace Policies with Competing Objectives and Constrained Experiments @TheOfficialACM
Uploaded July 2026 | Updated September 2026, 2 weeks ago
Yufei Wu, Zhen Yan
KDD 2026 - Personalizing Marketplace Policies with Competing Objectives and Constrained ExperimentsKDD2026-OnePath toModel ThemAll: Learnable-TimeFlowMatching for CrystalStructure andEnergyPredictionKDD 2026 - Stationarity-Aware Retrieval-Augmented Time Series ForecastingKDD2026-MitigatingAnomalyHallu.:AModel-AgnosticFramework forUnsuper.AnomalyDetection onDynamicGraphsKDD 2026 - OneLive: Dynamically Unified Generative Framework for Live-Streaming RecommendationKDD2026-The Boy WhoCried Wolf: Adversarial Misclass. of Safe Inputs asUnsafe in MultimodalGuardrailsKDD 2026 - Spectral-Inspired Neural Operator Learning with Limited Data and Unknown PhysicsKDD 2026 -RMEval: Bridging Reward Model Evaluation and Policy Evaluation through Ranking ConsistencyKDD 2026 - Label Annotation for Tabular Anomaly Detection with Large Language ModelsDynamic Matching with Post allocation Service and its Application to Refugee ResettlementKDD2026-SpotAgent:GroundingVisualGeo-localiz. in LargeVision-LanguageModels through AgenticReasoningIntegrating the Ethical and Societal Impacts of GenAI in the Classroom
Association for Computing Machinery (ACM) |

KDD 2026 - Personalizing Marketplace Policies with Competing Objectives and Constrained Experiments

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