machine learning

Mind the Graph When Balancing Data for Fairness or Robustness NeurIPS 2024 Mitigating Label Bias in Machine Learning: Fairness through Confident Learning AAAI 2024 MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks EACL 2024 Monitoring machine learning-based risk prediction algorithms in the presence of performativity AISTATS 2024 Multilingual Resources for Lexical Complexity Prediction: A Review COLING 2024 POLygraph: Polish Fake News Dataset ACL 2024 Position: AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research ICML 2024 Position: Machine Learning-powered Assessments of the EU Digital Services Act Aid Quantify Policy Impacts on Online Harms ICML 2024 Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized ICML 2024 Preventing Eviction-Caused Homelessness through ML-Informed Distribution of Rental Assistance AAAI 2024 PROSPECT PTMs: Rich Labeled Tandem Mass Spectrometry Dataset of Modified Peptides for Machine Learning in Proteomics NeurIPS 2024 Query Routing for Homogeneous Tools: An Instantiation in the RAG Scenario EMNLP 2024 ReactZyme: A Benchmark for Enzyme-Reaction Prediction NeurIPS 2024 Representation and Generation of Machine Learning Test Functions EACL 2024 Reproduce, Replicate, Reevaluate. The Long but Safe Way to Extend Machine Learning Methods AAAI 2024 Robust Non-linear Normalization of Heterogeneous Feature Distributions with Adaptive Tanh-Estimators AISTATS 2024 RR-PU: A Synergistic Two-Stage Positive and Unlabeled Learning Framework for Robust Tax Evasion Detection AAAI 2024 SolarCube: An Integrative Benchmark Dataset Harnessing Satellite and In-situ Observations for Large-scale Solar Energy Forecasting NeurIPS 2024 Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss NeurIPS 2024 Surveying the FAIRness of Annotation Tools: Difficult to find, difficult to reuse EACL 2024 Towards Harmless Rawlsian Fairness Regardless of Demographic Prior NeurIPS 2024 Towards Reproducible, Automated, and Scalable Anomaly Detection AAAI 2024 Understanding “Democratization” in NLP and ML Research EMNLP 2024 Unveiling the Tapestry of Automated Essay Scoring: A Comprehensive Investigation of Accuracy, Fairness, and Generalizability AAAI 2024 Using Causal Inference to Investigate Contraceptive Discontinuation in Sub-Saharan Africa IJCAI 2024