Multi-Aspect Streaming Tensor Completion. - Qingquan Song; Xiao Huang 001; Hancheng Ge; James Caverlee; Xia Hu 001 (KDD, 2017)

Discriminative Graph Autoencoder. - Haifeng Jin; Qingquan Song; Xia Hu (ICBK, 2018)

Multi-label Adversarial Perturbations. - Qingquan Song; Haifeng Jin; Xiao Huang 001; Xia Hu 001 (ICDM, 2018)

Towards Explanation of DNN-based Prediction with Guided Feature Inversion. - Mengnan Du; Ninghao Liu; Qingquan Song; Xia Hu 001 (KDD, 2018)

TrailMix: An Ensemble Recommender System for Playlist Curation and Continuation. - Xing Zhao 003; Qingquan Song; James Caverlee; Xia Hu 001 (RecSys Challenge, 2018)

Exploring Expert Cognition for Attributed Network Embedding. - Xiao Huang 001; Qingquan Song; Jundong Li; Xia Hu 001 (WSDM, 2018)

Efficient Neural Architecture Search with Network Morphism. - Haifeng Jin; Qingquan Song; Xia Hu (CoRR, 2018)

Large-Scale Heterogeneous Feature Embedding. - Xiao Huang 001; Qingquan Song; Fan Yang 023; Xia Hu 001 (AAAI, 2019)

Graph Recurrent Networks With Attributed Random Walks. - Xiao Huang 001; Qingquan Song; Yuening Li; Xia Hu 001 (KDD, 2019)

Auto-Keras: An Efficient Neural Architecture Search System. - Haifeng Jin; Qingquan Song; Xia Hu 001 (KDD, 2019)

Coupled Variational Recurrent Collaborative Filtering. - Qingquan Song; Shiyu Chang; Xia Hu 001 (KDD, 2019)

Coupled Variational Recurrent Collaborative Filtering. - Qingquan Song; Shiyu Chang; Xia Hu (CoRR, 2019)

Techniques for Automated Machine Learning. - Yi-Wei Chen; Qingquan Song; Xia Hu (CoRR, 2019)

Auto-GNN: Neural Architecture Search of Graph Neural Networks. - Kaixiong Zhou; Qingquan Song; Xiao Huang 001; Xia Hu 001 (CoRR, 2019)

Sub-Architecture Ensemble Pruning in Neural Architecture Search. - Yijun Bian; Qingquan Song; Mengnan Du; Jun Yao; Huanhuan Chen; Xia Hu 001 (CoRR, 2019)

Multi-Channel Graph Convolutional Networks. - Kaixiong Zhou; Qingquan Song; Xiao Huang 001; Daochen Zha; Na Zou 001; Xia Hu 001 (CoRR, 2019)

Tensor Completion Algorithms in Big Data Analytics. - Qingquan Song; Hancheng Ge; James Caverlee; Xia Hu 001 (ACM Trans. Knowl. Discov. Data, 2019)

Multi-Channel Graph Neural Networks. - Kaixiong Zhou; Qingquan Song; Xiao Huang 001; Daochen Zha; Na Zou 001; Xia Hu 001 (IJCAI, 2020)

Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. - Qingquan Song; Dehua Cheng; Hanning Zhou; Jiyan Yang; Yuandong Tian; Xia Hu 001 (KDD, 2020)

Detecting Interactions from Neural Networks via Topological Analysis. - Zirui Liu 001; Qingquan Song; Kaixiong Zhou; Ting-Hsiang Wang; Ying Shan; Xia Hu 001 (NeurIPS, 2020)

AutoRec: An Automated Recommender System. - Ting-Hsiang Wang; Xia Hu 001; Haifeng Jin; Qingquan Song; Xiaotian Han; Zirui Liu 001 (RecSys, 2020)

Towards Interaction Detection Using Topological Analysis on Neural Networks. - Zirui Liu 001; Qingquan Song; Kaixiong Zhou; Ting-Hsiang Wang; Ying Shan; Xia Hu 001 (CoRR, 2020)

On Robustness of Neural Architecture Search Under Label Noise. - Yi-Wei Chen; Qingquan Song; Xi Liu; P. S. Sastry 001; Xia Hu 001 (Frontiers Big Data, 2020)

Techniques for Automated Machine Learning. - Yi-Wei Chen; Qingquan Song; Xia Hu 001 (SIGKDD Explor., 2020)

Generalized Deep Mixed Models. - Jun Shi; Chengming Jiang; Aman Gupta; Mingzhou Zhou; Yunbo Ouyang; Qiang Charles Xiao; Qingquan Song; Yi (Alice) Wu; Haichao Wei; Huiji Gao (KDD, 2022)

Geometric Graph Representation Learning via Maximizing Rate Reduction. - Xiaotian Han; Zhimeng Jiang; Ninghao Liu; Qingquan Song; Jundong Li; Xia Hu 001 (WWW, 2022)

Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization. - Kayhan Behdin; Qingquan Song; Aman Gupta; David Durfee; Ayan Acharya; S. Sathiya Keerthi; Rahul Mazumder (CoRR, 2022)

Auto-GNN: Neural architecture search of graph neural networks. - Kaixiong Zhou; Xiao Huang 001; Qingquan Song; Rui Chen 012; Xia Hu 001 (Frontiers Big Data, 2022)

Subarchitecture Ensemble Pruning in Neural Architecture Search. - Yijun Bian; Qingquan Song; Mengnan Du; Jun Yao; Huanhuan Chen; Xia Hu 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization. - Kayhan Behdin; Qingquan Song; Aman Gupta; Ayan Acharya; David Durfee; Borja Ocejo; S. Sathiya Keerthi; Rahul Mazumder (CoRR, 2023)

AutoKeras: An AutoML Library for Deep Learning. - Haifeng Jin; François Chollet; Qingquan Song; Xia Hu (J. Mach. Learn. Res., 2023)

LiNR: Model Based Neural Retrieval on GPUs at LinkedIn. - Fedor Borisyuk; Qingquan Song; Mingzhou Zhou; Ganesh Parameswaran; Madhu Arun; Siva Popuri; Tugrul Bingol; Zhuotao Pei; Kuang-Hsuan Lee; Lu Zheng; Qizhan Shao; Ali Naqvi; et al. (CIKM, 2024)

LiRank: Industrial Large Scale Ranking Models at LinkedIn. - Fedor Borisyuk; Mingzhou Zhou; Qingquan Song; Siyu Zhu; Birjodh Tiwana; Ganesh Parameswaran; Siddharth Dangi; Lars Hertel; Qiang Charles Xiao; Xiaochen Hou; Yunbo Ouyang; Aman Gupta; et al. (KDD, 2024)

AI Driven Online Advertising: Market Design, Generative AI, and Ethics. - Fengxiang He; Mengnan Du; Aris Filos-Ratsikas; Lu Cheng 001; Qingquan Song; Min Lin; John Vines (WWW (Companion Volume), 2024)

FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference. - Zirui Liu 001; Qingquan Song; Qiang Charles Xiao; Sathiya Keerthi Selvaraj; Rahul Mazumder; Aman Gupta; Xia Hu 001 (CoRR, 2024)

Learning to Retrieve for Job Matching. - Jianqiang Shen; Yuchin Juan; Shaobo Zhang; Ping Liu 002; Wen Pu; Sriram Vasudevan; Qingquan Song; Fedor Borisyuk; Kay Qianqi Shen; Haichao Wei; Yunxiang Ren; Yeou S. Chiou; et al. (CoRR, 2024)

Liger Kernel: Efficient Triton Kernels for LLM Training. - Pin-Lun Hsu; Yun Dai; Vignesh Kothapalli; Qingquan Song; Shao Tang; Siyu Zhu; Steven Shimizu; Shivam Sahni; Haowen Ning; Yanning Chen (CoRR, 2024)

PME: pruning-based multi-size embedding for recommender systems. - Zirui Liu 001; Qingquan Song; Li Li 035; Soo-Hyun Choi; Rui Chen 012; Xia Hu 001 (Frontiers Big Data, 2024)

Comparative Analysis of the Diagonal Stride Technique during Roller Skiing and On-Snow Skiing in Youth Cross-Country Skiers. - Mujia Ma; Shuang Zhao; Ting Long; Qingquan Song; Hans-Christer Holmberg; Hui Liu (Sensors, 2024)

Efficient Algorithms for Leveraging LLMs for Generative and Predictive Recommender Systems. - Kayhan Behdin; Yun Dai; Gregory Dexter; Aman Gupta; Rahul Mazumder; Ankan Saha; Qingquan Song; Shao Tang; Sirou Zhu; Pin-Lun Hsu (WWW (Companion Volume), 2025)

AlphaPO - Reward shape matters for LLM alignment. - Aman Gupta; Shao Tang; Qingquan Song; Sirou Zhu; Jiwoo Hong; Ankan Saha; Viral Gupta; Noah Lee; Eunki Kim; Jason Zhu; Natesh Pillai; S. Sathiya Keerthi (CoRR, 2025)

360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation. - Hamed Firooz; Maziar Sanjabi; Adrian Englhardt; Aman Gupta; Ben Levine; Dre Olgiati; Gungor Polatkan; Iuliia Melnychuk; Karthik Ramgopal; Kirill Talanine; Kutta Srinivasan; Luke Simon; et al. (CoRR, 2025)

LLM Query Scheduling with Prefix Reuse and Latency Constraints. - Gregory Dexter; Shao Tang; Ata Fatahi Baarzi; Qingquan Song; Tejas Dharamsi; Aman Gupta (CoRR, 2025)

Efficient AI in Practice: Training and Deployment of Efficient LLMs for Industry Applications. - Kayhan Behdin; Yun Dai; Ata Fatahi Baarzi; Aman Gupta; Qingquan Song; Shao Tang; Hejian Sang; Gregory Dexter; Sirou Zhu; Siyu Zhu; Tejas Dharamsi; Maziar Sanjabi; et al. (CoRR, 2025)