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ORCIDLin Ning 0001
Person information
- affiliation: Google, Mountain View, CA, USA
- affiliation (PhD 2020): North Carolina State University, Raleigh, NC, USA
Other persons with the same name
- Lin Ning 0002 — Chengdu Neusoft University, School of Healthcare Technology, China (and 2 more)
- Lin Ning 0003 — Tsinghua University, Department of Automation, Beijing, China
Other persons with a similar name
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2020 – today
- 2024
[i8]Lin Ning, Luyang Liu, Jiaxing Wu, Neo Wu, Devora Berlowitz, Sushant Prakash, Bradley Green, Shawn O'Banion, Jun Xie:
User-LLM: Efficient LLM Contextualization with User Embeddings. CoRR abs/2402.13598 (2024)- [i7]Lin Ning, Harsh Lara, Meiqi Guo, Abhinav Rastogi:
MoDE: Effective Multi-task Parameter Efficient Fine-Tuning with a Mixture of Dyadic Experts. CoRR abs/2408.01505 (2024) - [i6]Chao Wang, Neo Wu, Lin Ning, Luyang Liu, Jun Xie, Shawn O'Banion, Bradley Green:
UserSumBench: A Benchmark Framework for Evaluating User Summarization Approaches. CoRR abs/2408.16966 (2024) - [i5]Jiaxing Wu, Lin Ning, Luyang Liu, Harrison Lee, Neo Wu, Chao Wang, Sushant Prakash, Shawn O'Banion, Bradley Green, Jun Xie:
RLPF: Reinforcement Learning from Prediction Feedback for User Summarization with LLMs. CoRR abs/2409.04421 (2024) - 2022
- [j2]Nihat Mert Cicek, Lin Ning, Ozcan Ozturk
, Xipeng Shen:
General Reuse-Centric CNN Accelerator. IEEE Trans. Computers 71(4): 880-891 (2022) - [c10]Honglin Yuan, Warren Richard Morningstar, Lin Ning, Karan Singhal:
What Do We Mean by Generalization in Federated Learning? ICLR 2022 - [c9]Lin Ning, Steve Chien, Shuang Song, Mei Chen, Yunqi Xue, Devora Berlowitz:
EANA: Reducing Privacy Risk on Large-scale Recommendation Models. RecSys 2022: 399-407 - [i4]Sean Augenstein, Andrew Hard, Lin Ning, Karan Singhal, Satyen Kale, Kurt Partridge, Rajiv Mathews:
Mixed Federated Learning: Joint Decentralized and Centralized Learning. CoRR abs/2205.13655 (2022) - 2021
- [c8]Hui Guan, Umana Chaudhary, Yuanchao Xu, Lin Ning, Lijun Zhang, Xipeng Shen:
Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. ICDM 2021: 1078-1083 - [c7]Lin Ning, Guoyang Chen, Weifeng Zhang, Xipeng Shen:
Simple Augmentation Goes a Long Way: ADRL for DNN Quantization. ICLR 2021 - [i3]Lin Ning, Karan Singhal, Ellie X. Zhou, Sushant Prakash:
Learning Federated Representations and Recommendations with Limited Negatives. CoRR abs/2108.07931 (2021) - [i2]Honglin Yuan, Warren R. Morningstar, Lin Ning, Karan Singhal:
What Do We Mean by Generalization in Federated Learning? CoRR abs/2110.14216 (2021)
2010 – 2019
- 2019
- [c6]Lin Ning, Hui Guan, Xipeng Shen:
Adaptive Deep Reuse: Accelerating CNN Training on the Fly. ICDE 2019: 1538-1549 - [c5]Lin Ning, Xipeng Shen:
Deep reuse: streamline CNN inference on the fly via coarse-grained computation reuse. ICS 2019: 438-448 - [c4]Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim:
In-Place Zero-Space Memory Protection for CNN. NeurIPS 2019: 5735-5744 - [i1]Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim:
In-Place Zero-Space Memory Protection for CNN. CoRR abs/1910.14479 (2019) - 2018
- [j1]Lin Ning, Randall Pittman, Xipeng Shen:
LCD: A Fast Contrastive Divergence Based Algorithm for Restricted Boltzmann Machine. Neural Networks 108: 399-410 (2018) - 2017
- [c3]Lin Ning, Randall Pittman, Xipeng Shen:
POSTER: Cutting the Fat: Speeding Up RBM for Fast Deep Learning Through Generalized Redundancy Elimination. PACT 2017: 154-155 - [c2]Lin Ning, Randall Pittman, Xipeng Shen:
LCD: A Fast Contrastive Divergence Based Algorithm for Restricted Boltzmann Machine. ICDM 2017: 1015-1020 - [c1]Yufei Ding, Lin Ning, Hui Guan, Xipeng Shen:
Generalizations of the theory and deployment of triangular inequality for compiler-based strength reduction. PLDI 2017: 33-48
Coauthor Index
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