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Data Mining

643 directly classified papers

Papers per year

Papers

Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains NIPS 2022
Seq2Pat: Sequence-to-Pattern Generation for Constraint-Based Sequential Pattern Mining AAAI 2022
MIMICause: Representation and automatic extraction of causal relation types from clinical notes ACL 2022
PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Data Subset Selection AAAI 2022
Falconn++: A Locality-sensitive Filtering Approach for Approximate Nearest Neighbor Search NIPS 2022
Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data NIPS 2022
Finding Scientific Topics in Continuously Growing Text Corpora COLING 2022
Reduction Algorithms for Persistence Diagrams of Networks: CoralTDA and PrunIT NIPS 2022
Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints NIPS 2022
Accelerating COVID-19 Research with Graph Mining and Transformer-Based Learning AAAI 2022
ByT5 model for massively multilingual grapheme-to-phoneme conversion INTERSPEECH 2022
Scalable and Efficient Non-adaptive Deterministic Group Testing NIPS 2022
Order-Invariant Cardinality Estimators Are Differentially Private NIPS 2022
Efficient and Effective Optimal Transport-Based Biclustering NIPS 2022
Large-Scale IP Usage Identification via Deep Ensemble Learning (Student Abstract) AAAI 2022
Evaluating Corpus Cleanup Methods in the WMT’22 News Translation Task EMNLP 2022
Towards Better Evaluation for Dynamic Link Prediction NIPS 2022
CloudCluster: Unearthing the Functional Structure of a Cloud Service NSDI 2022
Configanator: A Data-driven Approach to Improving CDN Performance. NSDI 2022
Predicting Label Distribution from Multi-label Ranking NIPS 2022
On the Effectiveness of Persistent Homology NIPS 2022
Whiz: Data-Driven Analytics Execution NSDI 2021
iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression CVPR 2021
Edge Sampling Using Local Network Information JMLR 2021
Competency Problems: On Finding and Removing Artifacts in Language Data EMNLP 2021