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Deep Hash Embedding for Large-Vocab Categorical Feature Representations., , , , , , and . CoRR, (2020)Efficient Data Representation Learning in Google-scale Systems., , , , , , , , and . RecSys, page 267-271. ACM, (2023)Complete the Look: Scene-based Complementary Product Recommendation., , , , and . CoRR, (2018)Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems., , , , , , and . WWW (Companion Volume), page 562-566. ACM / IW3C2, (2020)Candidate Generation with Binary Codes for Large-Scale Top-N Recommendation., and . CIKM, page 1523-1532. ACM, (2019)Estimation of sound source number and directions under a multi-source environment., , and . IROS, page 181-186. IEEE, (2009)Learning to Embed Categorical Features without Embedding Tables for Recommendation., , , , , , and . KDD, page 840-850. ACM, (2021)Column Sampling Based Discrete Supervised Hashing., , and . AAAI, page 1230-1236. AAAI Press, (2016)Visually-Aware Fashion Recommendation and Design with Generative Image Models., , , and . ICDM, page 207-216. IEEE Computer Society, (2017)Feature Learning based Deep Supervised Hashing with Pairwise Labels., , and . CoRR, (2015)