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Bo Peng 0009
Person information
- affiliation: Ohio State University, Department of Computer Science and Engineering, Columbus, OH, USA
Other persons with the same name
- Bo Peng — disambiguation page
- Bo Peng 0001 — University of Texas, Department of Genetics, Houston, TX, USA
- Bo Peng 0002 — Chinese Academy of Sciences, National Laboratory of Pattern Recognition, Beijing, China
- Bo Peng 0003 — University of Leeds, School of Electronic and Electrical Engineering, UK
- Peng Bo 0001 (aka: Bo Peng 0004) — Beihang University, School of Electronic and Information Engineering, Beijing, China
- Bo Peng 0005 — Arizona State University, Tempe, USA
- Bo Peng 0006 — Southwest Jiaotong University, Institute of Artificial Intelligence, School of Information Science and Technology, Chengdu, China
- Bo Peng 0007 — School of Electrical and Information Engineering, Tianjin University, Tianjin, China
- Bo Peng 0008 — Chinese Academy of Sciences, Suzhou Institute of Biomedical Engineering and Technology, China
- Bo Peng 0010 — Southwestern University of Finance and Economics, Faculty of Business Administration, Chengdu, China (and 1 more)
- Bo Peng 0011 — Indiana University, School of Informatics and Computing, Bloomington, IN, USA
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2020 – today
- 2024
- [j6]Bo Peng, Srinivasan Parthasarathy, Xia Ning:
Intention enhanced mixed attentive model for session-based recommendation. Data Min. Knowl. Discov. 38(4): 2032-2061 (2024) - [j5]Bo Peng, Ziqi Chen, Srinivasan Parthasarathy, Xia Ning:
Modeling Sequences as Star Graphs to Address Over-Smoothing in Self-Attentive Sequential Recommendation. ACM Trans. Knowl. Discov. Data 18(8): 207:1-207:24 (2024) - [c6]Bo Peng, Xinyi Ling, Ziru Chen, Huan Sun, Xia Ning:
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data. ICML 2024 - [i13]Bo Peng, Xinyi Ling, Ziru Chen, Huan Sun, Xia Ning:
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data. CoRR abs/2402.08831 (2024) - 2023
- [j4]Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning:
M2: Mixed Models With Preferences, Popularities and Transitions for Next-Basket Recommendation. IEEE Trans. Knowl. Data Eng. 35(4): 4033-4046 (2023) - [c5]Arpita Saha, Maggie Samaan, Bo Peng, Xia Ning:
A Multi-Layered GRU Model for COVID-19 Patient Representation and Phenotyping from Large-Scale EHR Data. BCB 2023: 21:1-21:6 - [c4]Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning:
HAM: Hybrid Associations Models for Sequential Recommendation (Extended abstract). ICDE 2023: 3873-3874 - [i12]Ziqi Chen, Bo Peng, Srinivasan Parthasarathy, Xia Ning:
Shape-conditioned 3D Molecule Generation via Equivariant Diffusion Models. CoRR abs/2308.11890 (2023) - [i11]Bo Peng, Srinivasan Parthasarathy, Xia Ning:
Multi-modality Meets Re-learning: Mitigating Negative Transfer in Sequential Recommendation. CoRR abs/2309.10195 (2023) - [i10]Bo Peng, Ben Burns, Ziqi Chen, Srinivasan Parthasarathy, Xia Ning:
Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation. CoRR abs/2310.01612 (2023) - [i9]Shunian Xiang, Patrick J. Lawrence, Bo Peng, Chienwei Chiang, Dokyoon Kim, Li Shen, Xia Ning:
Modeling Path Importance for Effective Alzheimer's Disease Drug Repurposing. CoRR abs/2310.15211 (2023) - [i8]Bo Peng, Ziqi Chen, Srinivasan Parthasarathy, Xia Ning:
Modeling Sequences as Star Graphs to Address Over-smoothing in Self-attentive Sequential Recommendation. CoRR abs/2311.07742 (2023) - 2022
- [j3]Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning:
$\mathop {\mathtt {HAM}}$HAM: Hybrid Associations Models for Sequential Recommendation. IEEE Trans. Knowl. Data Eng. 34(10): 4838-4853 (2022) - [i7]Bo Peng, Chang-Yu Tai, Srinivasan Parthasarathy, Xia Ning:
Prospective Preference Enhanced Mixed Attentive Model for Session-based Recommendation. CoRR abs/2206.01875 (2022) - [i6]Bo Peng, Srinivasan Parthasarathy, Xia Ning:
Recursive Attentive Methods with Reused Item Representations for Sequential Recommendation. CoRR abs/2209.07997 (2022) - 2021
- [j2]Zhiyun Ren, Bo Peng, Titus K. Schleyer, Xia Ning:
Hybrid collaborative filtering methods for recommending search terms to clinicians. J. Biomed. Informatics 113: 103635 (2021) - 2020
- [j1]Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning:
Cognitive biomarker prioritization in Alzheimer's Disease using brain morphometric data. BMC Medical Informatics Decis. Mak. 20(1): 319 (2020) - [i5]Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning:
Personalized Prioritization of Cognitive Biomarkers in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. CoRR abs/2002.07699 (2020) - [i4]Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning:
HAM: Hybrid Associations Model with Pooling for Sequential Recommendation. CoRR abs/2002.11890 (2020) - [i3]Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning:
M2pht: Mixed Models with Preferences and Hybrid Transitions for Next-Basket Recommendation. CoRR abs/2004.01646 (2020) - [i2]Zhiyun Ren, Bo Peng, Titus K. Schleyer, Xia Ning:
Hybrid Collaborative Filtering Models for Clinical Search Recommendation. CoRR abs/2008.01193 (2020)
2010 – 2019
- 2019
- [c3]Bo Peng, Xia Ning:
Deep Learning for High-Order Drug-Drug Interaction Prediction. BCB 2019: 197-206 - [c2]Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning:
Prioritization of Cognitive Assessments in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. BHI 2019: 1-4 - [c1]Bo Peng, Zhiyun Ren, Xiaohui Yao, Kefei Liu, Andrew J. Saykin, Li Shen, Xia Ning:
Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank. MBIA/MFCA@MICCAI 2019: 139-148 - [i1]Bo Peng, Renqiang Min, Xia Ning:
CNN-based Dual-Chain Models for Knowledge Graph Learning. CoRR abs/1911.06910 (2019)
Coauthor Index
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last updated on 2024-11-18 21:49 CET by the dblp team
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