Media Summary: Chengliang Chai, Beijing Institute of Technology. Xiang Rong Sheng, Alibaba Group We propose JRC that can Jointly optimize the Ranking and Calibration abilities. JRC improves ... Jiayi Wang, Chengliang Chai, Nan Tang, Jiabin Liu, and Guoliang Li. 2022.

Kdd 2023 Efficient Coreset Selection - Detailed Analysis & Overview

Chengliang Chai, Beijing Institute of Technology. Xiang Rong Sheng, Alibaba Group We propose JRC that can Jointly optimize the Ranking and Calibration abilities. JRC improves ... Jiayi Wang, Chengliang Chai, Nan Tang, Jiabin Liu, and Guoliang Li. 2022. Yunjia Xi, Shanghai Jiao Tong University. Kunal Dahiya, IIT Delhi Large language models or encoders are widely used in real-world search and recommendation ... Zhiyuan Peng, Santa Clara University This is a brief introduction to our paper "Entity-aware of Mulit-task Learning for Query ...

Shibal Ibrahim, Massachusetts Institute of Technology Sparse Mixture-of-Experts (Sparse-MoE) framework Lorenzo Perini, KU Leuven Nowadays, sustainable energy is becoming more and more important. Wind turbines can produce ... Yue Xu, Alibaba Group Multi-factor Sequential Re-ranking with Perception-Aware Diversification. Coffee Sessions with Cody Coleman, Data Quality Over Quantity or Data Supercharge your analytics engineering with the power of automated CI checks. Learn how FINN, a global car subscription ... Karan Samel, Georgia Tech End-to-end query term weighting problem definition, method, and results summary.

Zhe Xu, University of Illinois Urbana-Champaign.

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KDD 2023 - Efficient Coreset Selection with Cluster-based Methods
KDD 2023 - Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering
Recent Advances in Diversity Maximization in the Offline and Composable Coreset Models
KDD 2023 - Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model
Coresets over multiple tables for feature-rich and data-efficient machine learning
Using Coresets to Develop and Maintain Better ML | Eitan Netzer (DataHeroes)
KDD 2023 - On-device Integrated Re-ranking with Heterogeneous Behavior Modeling
FAST: Topology-Aware Frequency-Domain Distribution Matching for Coreset Selection
KDD 2023 - Deep Encoders with Auxiliary Parameters for Extreme Classification
KDD 2023 - Rank-heterogeneous Preference Models for School Choice
KDD 2023 - Entity-aware of Mulit-task Learning for Query Understanding at Walmart
KDD 2023 - Learning Cardinality Constrained Mixture of Experts with Trees and Local Search
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