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Jingwei Zhuo
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2020 – today
- 2024
- [c15]Zhirui Kuai, Zuxu Chen, Huimu Wang, Mingming Li, Dadong Miao, Binbin Wang, Xusong Chen, Li Kuang, Yuxing Han, Jiaxing Wang, Guoyu Tang, Lin Liu, Songlin Wang, Jingwei Zhuo:
Breaking the Hourglass Phenomenon of Residual Quantization: Enhancing the Upper Bound of Generative Retrieval. EMNLP (Industry Track) 2024: 677-685 - [i10]Mingming Li, Huimu Wang, Zuxu Chen, Guangtao Nie, Yiming Qiu, Binbin Wang, Guoyu Tang, Lin Liu, Jingwei Zhuo:
Generative Retrieval with Preference Optimization for E-commerce Search. CoRR abs/2407.19829 (2024) - [i9]Zhirui Kuai, Zuxu Chen, Huimu Wang, Mingming Li, Dadong Miao, Binbin Wang, Xusong Chen, Li Kuang, Yuxing Han, Jiaxing Wang, Guoyu Tang, Lin Liu, Songlin Wang, Jingwei Zhuo:
Breaking the Hourglass Phenomenon of Residual Quantization: Enhancing the Upper Bound of Generative Retrieval. CoRR abs/2407.21488 (2024) - 2023
- [c14]Mingming Li, Chunyuan Yuan, Huimu Wang, Peng Wang, Jingwei Zhuo, Binbin Wang, Lin Liu, Sulong Xu:
Adaptive Hyper-parameter Learning for Deep Semantic Retrieval. EMNLP (Industry Track) 2023: 775-782 - [c13]Jiaxing Wang, Yong Li, Jingwei Zhuo, Xupeng Shi, Weizhong Zhang, Lixing Gong, Tong Tao, Pengzhang Liu, Yongjun Bao, Weipeng Yan:
DynaMS: Dyanmic Margin Selection for Efficient Deep Learning. ICLR 2023 - [c12]Mingming Li
, Chunyuan Yuan
Learning Query-aware Embedding Index for Improving E-commerce Dense Retrieval. SIGIR 2023: 3265-3269 - [c11]Zhigong Zhou
Semantic-enhanced Modality-asymmetric Retrieval for Online E-commerce Search. SIGIR 2023: 3405-3409 - [c10]Binbin Wang
Learning Multi-Stage Multi-Grained Semantic Embeddings for E-Commerce Search. WWW (Companion Volume) 2023: 411-415 - [i8]Binbin Wang, Mingming Li, Zhixiong Zeng, Jingwei Zhuo, Songlin Wang, Sulong Xu, Bo Long, Weipeng Yan:
Learning Multi-Stage Multi-Grained Semantic Embeddings for E-Commerce Search. CoRR abs/2303.11009 (2023) - 2022
- [c9]Yiming Qiu
Pre-training Tasks for User Intent Detection and Embedding Retrieval in E-commerce Search. CIKM 2022: 4424-4428 - [i7]Jingwei Zhuo, Bin Liu, Xiang Li, Han Zhu, Xiaoqiang Zhu:
WSLRec: Weakly Supervised Learning for Neural Sequential Recommendation Models. CoRR abs/2202.13616 (2022) - [i6]Yiming Qiu, Chenyu Zhao, Han Zhang, Jingwei Zhuo, Tianhao Li, Xiaowei Zhang, Songlin Wang, Sulong Xu, Bo Long, Wen-Yun Yang:
Pre-training Tasks for User Intent Detection and Embedding Retrieval in E-commerce Search. CoRR abs/2208.06150 (2022) - 2020
- [c8]Jingwei Zhuo, Ziru Xu, Wei Dai, Han Zhu, Han Li, Jian Xu, Kun Gai:
Learning Optimal Tree Models under Beam Search. ICML 2020: 11650-11659 - [i5]Jingwei Zhuo, Ziru Xu, Wei Dai, Han Zhu, Han Li, Jian Xu, Kun Gai:
Learning Optimal Tree Models Under Beam Search. CoRR abs/2006.15408 (2020)
2010 – 2019
- 2019
- [c7]Chang Liu, Jingwei Zhuo, Pengyu Cheng, Ruiyi Zhang, Jun Zhu:
Understanding and Accelerating Particle-Based Variational Inference. ICML 2019: 4082-4092 - [c6]Chang Liu, Jingwei Zhuo, Jun Zhu:
Understanding MCMC Dynamics as Flows on the Wasserstein Space. ICML 2019: 4093-4103 - [i4]Chang Liu, Jingwei Zhuo, Jun Zhu:
Understanding MCMC Dynamics as Flows on the Wasserstein Space. CoRR abs/1902.00282 (2019) - 2018
- [c5]Yichi Zhou, Jun Zhu, Jingwei Zhuo:
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors. ICML 2018: 5995-6003 - [c4]Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, Bo Zhang:
Message Passing Stein Variational Gradient Descent. ICML 2018: 6013-6022 - [i3]Chang Liu, Jingwei Zhuo, Pengyu Cheng, Ruiyi Zhang, Jun Zhu, Lawrence Carin:
Accelerated First-order Methods on the Wasserstein Space for Bayesian Inference. CoRR abs/1807.01750 (2018) - 2017
- [c3]Wenbo Hu, Jun Zhu, Hang Su, Jingwei Zhuo, Bo Zhang:
Semi-supervised Max-margin Topic Model with Manifold Posterior Regularization. IJCAI 2017: 1865-1871 - [i2]Yichi Zhou, Jun Zhu, Jingwei Zhuo:
Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors. CoRR abs/1708.04781 (2017) - [i1]Jianqiao Wangni, Jingwei Zhuo, Jun Zhu:
Learning Random Fourier Features by Hybrid Constrained Optimization. CoRR abs/1712.02527 (2017) - 2016
- [c2]Jingwei Zhuo, Yong Cao, Jun Zhu, Bo Zhang, Zaiqing Nie:
Segment-Level Sequence Modeling using Gated Recursive Semi-Markov Conditional Random Fields. ACL (1) 2016 - 2015
- [c1]Jingwei Zhuo, Jun Zhu, Bo Zhang:
Adaptive Dropout Rates for Learning with Corrupted Features. IJCAI 2015: 4126-4133
Coauthor Index
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