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Xi Liu 0011
Person information
- affiliation: Texas A&M University, Department of Electrical and Computer Engineering, College Station, TX, USA
Other persons with the same name
- Xi Liu — disambiguation page
- Xi Liu 0001 — Broadcom, Matawan, NJ, USA (and 1 more)
- Xi Liu 0002 — Yunnan University, School of Information Science and Engineering, Kunming, China
- Xi Liu 0003 — Pennsylvania State University, Department of Geography, University Park, PA, USA
- Xi Liu 0004 — Sun Yat-sen University, School of Electronics and Information Technology, Guangzhou, China
- Xi Liu 0005 — Shanghai University, Shanghai Institute for Advanced Communication and Data Science, China
- Xi Liu 0006 — Xi'an Jiaotong University, School of Electronic and Information Engineering, Xi'an, China
- Xi Liu 0007 — Chengdu University of Technology, College of Earth Science, Chengdu, China
- Xi Liu 0008 — Nanchang University, School of Information Engineering, Nanchang, China
- Xi Liu 0009 — Fujitsu Research & Development Center, Beijing, China (and 1 more)
- Xi Liu 0010 — Hefei Normal University, School of Mathematics and Statistics, Hefei, China (and 1 more)
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2020 – today
- 2023
- [c21]Hsin-En Su, Yen-Ju Chen, Ping-Chun Hsieh, Xi Liu:
Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees. AISTATS 2023: 1331-1378 - [c20]Wei Hung, Bo-Kai Huang, Ping-Chun Hsieh, Xi Liu:
Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots. ICLR 2023 - 2022
- [c19]Tao Liu, P. R. Kumar, Ruida Zhou, Xi Liu:
Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales. NeurIPS 2022 - [i17]Wei Hung, Bo-Kai Huang, Ping-Chun Hsieh, Xi Liu:
Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots. CoRR abs/2212.03117 (2022) - [i16]Hsin-En Su, Yen-Ju Chen, Ping-Chun Hsieh, Xi Liu:
Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees. CoRR abs/2212.05237 (2022) - 2021
- [c18]Yu-Heng Hung, Ping-Chun Hsieh, Xi Liu, P. R. Kumar:
Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits. AAAI 2021: 7874-7882 - [c17]Akshay Mete, Rahul Singh, Xi Liu, P. R. Kumar:
Reward Biased Maximum Likelihood Estimation for Reinforcement Learning. L4DC 2021: 815-827 - [c16]Bing-Jing Hsieh, Ping-Chun Hsieh, Xi Liu:
Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization. NeurIPS 2021: 7718-7731 - [c15]Jyun-Li Lin, Wei Hung, Shang-Hsuan Yang, Ping-Chun Hsieh, Xi Liu:
Escaping from zero gradient: Revisiting action-constrained reinforcement learning via Frank-Wolfe policy optimization. UAI 2021: 397-407 - [i15]Jyun-Li Lin, Wei Hung, Shang-Hsuan Yang, Ping-Chun Hsieh, Xi Liu:
Escaping from Zero Gradient: Revisiting Action-Constrained Reinforcement Learning via Frank-Wolfe Policy Optimization. CoRR abs/2102.11055 (2021) - [i14]Bing-Jing Hsieh, Ping-Chun Hsieh, Xi Liu:
Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization. CoRR abs/2106.04335 (2021) - [i13]Tao Liu, P. R. Kumar, Xi Liu:
Learning from Small Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales. CoRR abs/2109.12784 (2021) - 2020
- [j1]Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, Na Wang:
Micro- and macro-level churn analysis of large-scale mobile games. Knowl. Inf. Syst. 62(4): 1465-1496 (2020) - [c14]Hanzi Mao, Xi Liu, Nick Duffield, Hao Yuan, Shuiwang Ji, Binayak P. Mohanty:
Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis. ICDM 2020: 392-401 - [c13]Xi Liu, Ping-Chun Hsieh, Yu-Heng Hung, Anirban Bhattacharya, P. R. Kumar:
Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits. ICML 2020: 6248-6258 - [c12]Ping-Chun Hsieh, Xi Liu, I-Hong Hou:
Fresher content or smoother playback?: a brownian-approximation framework for scheduling real-time wireless video streams. MobiHoc 2020: 41-50 - [i12]Xi Liu, Li Li, Ping-Chun Hsieh, Muhe Xie, Yong Ge, Rui Chen:
Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning. CoRR abs/2001.09595 (2020) - [i11]Yu-Heng Hung, Ping-Chun Hsieh, Xi Liu, P. R. Kumar:
Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits. CoRR abs/2010.04091 (2020)
2010 – 2019
- 2019
- [c11]Xianshan Qu, Li Li, Xi Liu, Rui Chen, Yong Ge, Soo-Hyun Choi:
A Dynamic Neural Network Model for Click-Through Rate Prediction in Real-Time Bidding. IEEE BigData 2019: 1887-1896 - [c10]Arman Hasanzadeh, Xi Liu, Nick Duffield, Krishna R. Narayanan:
Piecewise Stationary Modeling of Random Processes Over Graphs With an Application to Traffic Prediction. IEEE BigData 2019: 3779-3788 - [c9]Ping-Chun Hsieh, Xi Liu, Anirban Bhattacharya, P. R. Kumar:
Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging. ICML 2019: 2800-2809 - [c8]Xidao Wen, Konstantinos Pelechrinis, Yu-Ru Lin, Xi Liu, Yongsu Ahn, Nan Cao:
FacIt: Factorizing Tensors into Interpretable and Scrutinizable Patterns. IEEE VIS (Short Papers) 2019: 76-80 - [c7]Xi Liu, Ping-Chun Hsieh, Nick Duffield, Rui Chen, Muhe Xie, Xidao Wen:
Real-Time Streaming Graph Embedding Through Local Actions. WWW (Companion Volume) 2019: 285-293 - [c6]Xidao Wen, Yu-Ru Lin, Xi Liu, Peter Brusilovsky, Jordan Barria-Pineda:
Iterative Discriminant Tensor Factorization for Behavior Comparison in Massive Open Online Courses. WWW 2019: 2068-2079 - [i10]Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, Na Wang:
Micro- and Macro-Level Churn Analysis of Large-Scale Mobile Games. CoRR abs/1901.06247 (2019) - [i9]Xi Liu, Ping-Chun Hsieh, Anirban Bhattacharya, P. R. Kumar:
Bandit Learning Through Biased Maximum Likelihood Estimation. CoRR abs/1907.01287 (2019) - [i8]Ping-Chun Hsieh, Xi Liu, I-Hong Hou:
Fresher Content or Smoother Playback? A Brownian-Approximation Framework for Real-Time Video Delivery in Wireless Networks. CoRR abs/1911.00902 (2019) - 2018
- [c5]Xi Liu, Ping-Chun Hsieh, P. R. Kumar:
Safe Intersection Management for Mixed Transportation Systems with Human-Driven and Autonomous Vehicles. Allerton 2018: 834-841 - [c4]Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, Na Wang:
A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games. ICDM 2018: 277-286 - [i7]Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, Na Wang:
A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games. CoRR abs/1808.06573 (2018) - [i6]Xi Liu, Ping-Chun Hsieh, P. R. Kumar:
Safe Intersection Management for Mixed Transportation Systems with Human-Driven and Autonomous Vehicles. CoRR abs/1808.06632 (2018) - [i5]Xi Liu, Ke Ma, P. R. Kumar:
Towards Provably Safe Mixed Transportation Systems with Human-driven and Automated Vehicles. CoRR abs/1810.05807 (2018) - [i4]Ping-Chun Hsieh, Xi Liu, Anirban Bhattacharya, P. R. Kumar:
Heteroscedastic Bandits with Reneging. CoRR abs/1810.12418 (2018) - [i3]Xi Liu, Ping-Chun Hsieh, Nick Duffield, Rui Chen, Muhe Xie, Xidao Wen:
Streaming Network Embedding through Local Actions. CoRR abs/1811.05932 (2018) - 2017
- [c3]Ping-Chun Hsieh, Xi Liu, Jian Jiao, I-Hong Hou, Yunlong Zhang, P. R. Kumar:
Throughput-Optimal Scheduling for Multi-Hop Networked Transportation Systems With Switch-Over Delay. MobiHoc 2017: 16:1-16:10 - [i2]Ping-Chun Hsieh, I-Hong Hou, Xi Liu:
Delay-Optimal Scheduling for Queueing Systems with Switching Overhead. CoRR abs/1701.03831 (2017) - [i1]Ping-Chun Hsieh, Xi Liu, Jian Jiao, I-Hong Hou, Yunlong Zhang, P. R. Kumar:
Throughput-Optimal Scheduling for Multi-Hop Networked Transportation Systems With Switch-Over Delay. CoRR abs/1701.03991 (2017) - 2016
- [c2]Xi Liu, P. R. Kumar:
Towards safety of transportation systems with a mixture of automated and human-driven vehicles. COMSNETS 2016: 1-3 - 2015
- [c1]Xi Liu, Ke Ma, P. R. Kumar:
Towards provably safe mixed transportation systems with human-driven and automated vehicles. CDC 2015: 4688-4694
Coauthor Index
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