Memory-Efficient Sequential Pattern Mining with Hybrid Tries

arXiv:2202.06834 · cs.DB, cs.AI, cs.DS, cs.LG · Submitted 2022-02-06 · Read on arXiv

cs.DB, cs.AI, cs.DS, cs.LG

Submitted: 2022-02-06

Updated: 2024-07-27

Code: https://github.com/aminhn/BDTrie

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Sequential Pattern Mining — 2× in this paper

Sources

• Memory-Efficient Implementation of DenseNets

Related papers

• Cost-Aware Mixture-of-Experts Coordination for Model Markets
• Vibe Coding on Trial: Operating Characteristics of Unanimous LLM Juries
• Human-Level Text-to-SQL via Reinforcement Learning on Verified Data, Without Pipeline Engineering
• MetaJoin: Adaptive Join Selections for Heterogeneous Tables
• Bridging Business Intent and Data: A Benchmark for Automatic Relational Data Product Generation
• DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation