Yabo Ni

Orcid: 0000-0002-7535-8125

According to our database1, Yabo Ni authored at least 16 papers between 2013 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
Learning Personalizable Clustered Embedding for Recommender Systems.
Trans. Recomm. Syst., September, 2025

A Neural Network-Enhanced Digital Background Calibration Algorithm for Residue Amplifier Nonlinearity in Pipelined ADCs.
IEEE Trans. Circuits Syst. II Express Briefs, August, 2025

A 12-bit 2-GS/s Pipeline ADC in 28-nm CMOS With Linear-Error Self-Calibration.
IEEE Trans. Very Large Scale Integr. Syst., June, 2025

Kolmogorov-Arnold Networks-Based Calibration for Single-Channel ADCs: High-Precision Nonlinear Code Synthesis With Low Power Consumption.
IEEE Trans. Circuits Syst. I Regul. Pap., June, 2025

Embed Progressive Implicit Preference in Unified Space for Deep Collaborative Filtering.
CoRR, May, 2025

Maximum Inner Product is Query-Scaled Nearest Neighbor.
Proc. VLDB Endow., February, 2025

Dynamic masking-based feature interaction modeling for e-commerce click-through rate prediction.
Eng. Appl. Artif. Intell., 2025

Stitching Inner Product and Euclidean Metrics for Topology-aware Maximum Inner Product Search.
Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

2024
An E-Commerce Dataset Revealing Variations during Sales.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Residual Multi-Task Learner for Applied Ranking.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023
Clustered Embedding Learning for Recommender Systems.
Proceedings of the ACM Web Conference 2023, 2023

2022
Prior-Guided Transfer Learning for Enhancing Item Representation in E-commerce.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Enhancing E-commerce Recommender System Adaptability with Online Deep Controllable Learning-To-Rank.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Scenario-aware and Mutual-based approach for Multi-scenario Recommendation in E-Commerce.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

2018
Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2013
Personalized automatic image annotation based on reinforcement learning.
Proceedings of the 2013 IEEE International Conference on Multimedia and Expo, 2013


  Loading...