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Learning to Embed Categorical Features without Embedding Tables for Recommendation., , , , , , and . KDD, page 840-850. ACM, (2021)Learned Indexes for a Google-scale Disk-based Database., , , , , , , , and . CoRR, (2020)Evaluation and Refinement of Clustered Search Results with the Crowd., , , , , and . ACM Trans. Interact. Intell. Syst., 8 (2): 14:1-14:28 (2018)Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems., , , , , , , and . CoRR, (2023)The trouble with social computing systems research., , , and . CHI Extended Abstracts, page 389-398. ACM, (2011)Annotate once, appear anywhere: collective foraging for snippets of interest using paragraph fingerprinting., and . CHI, page 1791-1794. ACM, (2009)Model-Driven Research in Human-Centric Computing.. VL/HCC, page 3. IEEE Computer Society, (2010)Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems., , , , , , and . WWW (Companion Volume), page 562-566. ACM / IW3C2, (2020)Counterfactual Fairness in Text Classification through Robustness., , , , , and . AIES, page 219-226. ACM, (2019)Impact on Performance and Process by a Social Annotation System: A Social Reading Experiment., , , , and . HCI (16), volume 5638 of Lecture Notes in Computer Science, page 270-278. Springer, (2009)