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Risk Management

1053 directly classified papers

Papers per year

Papers

Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift NIPS 2024
Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty AISTATS 2024
LLMFactor: Extracting Profitable Factors through Prompts for Explainable Stock Movement Prediction ACL 2024
Adaptive Discretization for Event PredicTion (ADEPT) AISTATS 2024
Monitoring machine learning-based risk prediction algorithms in the presence of performativity AISTATS 2024
Fairness without Harm: An Influence-Guided Active Sampling Approach NIPS 2024
Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures AISTATS 2024
UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation ACL 2024
Conformal Contextual Robust Optimization AISTATS 2024
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons NIPS 2024
Deploying ADVISER: Impact and Lessons from Using Artificial Intelligence for Child Vaccination Uptake in Nigeria AAAI 2024
Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility AAAI 2024
FinBen: A Holistic Financial Benchmark for Large Language Models NIPS 2024
Online Conversion Rate Prediction via Multi-Interval Screening and Synthesizing under Delayed Feedback AAAI 2024
Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction AAAI 2024
Improving Health Information Access in the World’s Largest Maternal Mobile Health Program via Bandit Algorithms AAAI 2024
On the Worst Prompt Performance of Large Language Models NIPS 2024
DGA-GNN: Dynamic Grouping Aggregation GNN for Fraud Detection AAAI 2024
Conformal Inference for Online Prediction with Arbitrary Distribution Shifts JMLR 2024
Adaptive Labeling for Efficient Out-of-distribution Model Evaluation NIPS 2024
Stage-Aware Learning for Dynamic Treatments JMLR 2024
Learning with a linear loss function: excess risk and estimation bounds for ERM, minmax MOM and their regularized versions with applications to robustness in sparse PCA. JMLR 2024
Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources AISTATS 2024
Learning from Noisy Labels via Conditional Distributionally Robust Optimization NIPS 2024
Modeling and Detecting Company Risks from News NAACL 2024