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2020 – today
- 2024
[c54]Manish Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Xuchao Zhang, Jonathan Mace, Dax Vandevoorde, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan:
Building AI Agents for Autonomous Clouds: Challenges and Design Principles. SoCC 2024: 99-110- [c53]Yinfang Chen
, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xuedong Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo Ghosh, Xuchao Zhang, Chaoyun Zhang, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang, Tianyin Xu:
Automatic Root Cause Analysis via Large Language Models for Cloud Incidents. EuroSys 2024: 674-688 - [c52]Chen Ling, Xujiang Zhao, Xuchao Zhang, Wei Cheng, Yanchi Liu, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen:
Uncertainty Quantification for In-Context Learning of Large Language Models. NAACL-HLT 2024: 3357-3370 - [c51]Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Henrique B. Las-Casas, Rodrigo Fonseca, Saravan Rajmohan:
Exploring LLM-Based Agents for Root Cause Analysis. SIGSOFT FSE Companion 2024: 208-219 - [c50]Xuchao Zhang, Supriyo Ghosh, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan:
Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4. SIGSOFT FSE Companion 2024: 266-277 - [c49]Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Henrique B. Las-Casas, Rodrigo Fonseca, Saravan Rajmohan:
LM-PACE: Confidence Estimation by Large Language Models for Effective Root Causing of Cloud Incidents. SIGSOFT FSE Companion 2024: 388-398 - [c48]Drishti Goel, Fiza Husain, Aditya Singh, Supriyo Ghosh, Anjaly Parayil, Chetan Bansal, Xuchao Zhang, Saravan Rajmohan:
X-Lifecycle Learning for Cloud Incident Management using LLMs. SIGSOFT FSE Companion 2024: 417-428 - [i34]Xuchao Zhang, Supriyo Ghosh, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan:
Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4. CoRR abs/2401.13810 (2024) - [i33]Chen Ling, Xujiang Zhao, Wei Cheng, Yanchi Liu, Yiyou Sun, Xuchao Zhang, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen:
Uncertainty Decomposition and Quantification for In-Context Learning of Large Language Models. CoRR abs/2402.10189 (2024) - [i32]Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Henrique B. Las-Casas, Rodrigo Fonseca, Saravan Rajmohan:
Exploring LLM-based Agents for Root Cause Analysis. CoRR abs/2403.04123 (2024) - [i31]Drishti Goel, Fiza Husain, Aditya Singh, Supriyo Ghosh, Anjaly Parayil, Chetan Bansal, Xuchao Zhang, Saravan Rajmohan:
X-lifecycle Learning for Cloud Incident Management using LLMs. CoRR abs/2404.03662 (2024) - [i30]Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou, Huaxiu Yao:
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models. CoRR abs/2406.06007 (2024) - [i29]Manish Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Xuchao Zhang, Jonathan Mace, Dax Vandevoorde, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan:
Building AI Agents for Autonomous Clouds: Challenges and Design Principles. CoRR abs/2407.12165 (2024) - 2023
- [c47]Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang:
Time Series Contrastive Learning with Information-Aware Augmentations. AAAI 2023: 4534-4542 - [c46]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
TART: Improved Few-shot Text Classification Using Task-Adaptive Reference Transformation. ACL (1) 2023: 11014-11026 - [c45]Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao:
Open-ended Commonsense Reasoning with Unrestricted Answer Candidates. EMNLP (Findings) 2023: 8035-8047 - [c44]Xujiang Zhao, Xuchao Zhang, Chen Zhao, Jin-Hee Cho, Lance M. Kaplan, Dong Hyun Jeong, Audun Jøsang, Haifeng Chen, Feng Chen:
Multi-Label Temporal Evidential Neural Networks for Early Event Detection. ICASSP 2023: 1-5 - [c43]Toufique Ahmed, Supriyo Ghosh, Chetan Bansal, Thomas Zimmermann, Xuchao Zhang, Saravan Rajmohan:
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models. ICSE 2023: 1737-1749 - [c42]Jianfeng He, Xuchao Zhang, Shuo Lei, Abdulaziz Alhamadani, Fanglan Chen, Bei Xiao, Chang-Tien Lu:
CLUR: Uncertainty Estimation for Few-Shot Text Classification with Contrastive Learning. KDD 2023: 698-710 - [c41]Pradeep Dogga, Chetan Bansal, Richard Costleigh, Gopinath Jayagopal, Suman Nath, Xuchao Zhang:
AutoARTS: Taxonomy, Insights and Tools for Root Cause Labelling of Incidents in Microsoft Azure. USENIX ATC 2023: 359-372 - [c40]Abdulaziz Alhamadani, Xuchao Zhang, Jianfeng He, Aadyant Khatri, Chang-Tien Lu:
LANS: Large-scale Arabic News Summarization Corpus. ArabicNLP 2023: 89-100 - [i28]Toufique Ahmed, Supriyo Ghosh, Chetan Bansal, Thomas Zimmermann, Xuchao Zhang, Saravan Rajmohan:
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models. CoRR abs/2301.03797 (2023) - [i27]Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao:
Knowledge-enhanced Neural Machine Reasoning: A Review. CoRR abs/2302.02093 (2023) - [i26]Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang:
Time Series Contrastive Learning with Information-Aware Augmentations. CoRR abs/2303.11911 (2023) - [i25]Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xuedong Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo Ghosh, Xuchao Zhang, Chaoyun Zhang, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang:
Empowering Practical Root Cause Analysis by Large Language Models for Cloud Incidents. CoRR abs/2305.15778 (2023) - [i24]Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Carl Yang, Liang Zhao:
Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models. CoRR abs/2305.18703 (2023) - [i23]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
TART: Improved Few-shot Text Classification Using Task-Adaptive Reference Transformation. CoRR abs/2306.02175 (2023) - [i22]Xuchao Zhang, Menglin Xia, Camille Couturier, Guoqing Zheng, Saravan Rajmohan, Victor Rühle:
Hybrid Retrieval-Augmented Generation for Real-time Composition Assistance. CoRR abs/2308.04215 (2023) - [i21]Chen Ling, Xujiang Zhao, Xuchao Zhang, Yanchi Liu, Wei Cheng, Haoyu Wang, Zhengzhang Chen, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao:
Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty. CoRR abs/2309.03433 (2023) - [i20]Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Henrique B. Las-Casas, Rodrigo Fonseca, Saravan Rajmohan:
PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis. CoRR abs/2309.05833 (2023) - [i19]Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao:
Open-ended Commonsense Reasoning with Unrestricted Answer Scope. CoRR abs/2310.11672 (2023) - 2022
- [j4]Jianfeng He, Xuchao Zhang, Shuo Lei, Shuhui Wang, Chang-Tien Lu, Bei Xiao:
Semantic inpainting on segmentation map via multi-expansion loss. Neurocomputing 501: 306-317 (2022) - [j3]Shuo Lei, Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu:
Online and Distributed Robust Regressions with Extremely Noisy Labels. ACM Trans. Knowl. Discov. Data 16(3): 41:1-41:24 (2022) - [j2]Tian Shi, Xuchao Zhang, Ping Wang, Chandan K. Reddy:
Corpus-level and Concept-based Explanations for Interpretable Document Classification. ACM Trans. Knowl. Discov. Data 16(3): 48:1-48:17 (2022) - [c39]Liyan Xu, Xuchao Zhang, Bo Zong, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao, Jinho D. Choi:
Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency Graph. AAAI 2022: 11538-11546 - [c38]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Bowen Du, Chang-Tien Lu:
Cross-Domain Few-Shot Semantic Segmentation. ECCV (30) 2022: 73-90 - [c37]Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen:
Seed: Sound Event Early Detection Via Evidential Uncertainty. ICASSP 2022: 3618-3622 - [c36]Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, Liang Zhao:
DeepGAR: Deep Graph Learning for Analogical Reasoning. ICDM 2022: 1065-1070 - [c35]Shengming Zhang, Yanchi Liu, Xuchao Zhang, Wei Cheng, Haifeng Chen, Hui Xiong:
CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event Sequences. KDD 2022: 4541-4550 - [c34]Dheeraj Rajagopal, Xuchao Zhang, Michael Gamon, Sujay Kumar Jauhar, Diyi Yang, Eduard H. Hovy:
One Document, Many Revisions: A Dataset for Classification and Description of Edit Intents. LREC 2022: 5517-5524 - [c33]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
Uncertainty-Aware Cross-Lingual Transfer with Pseudo Partial Labels. NAACL-HLT (Findings) 2022: 1987-1997 - [i18]Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen:
SEED: Sound Event Early Detection via Evidential Uncertainty. CoRR abs/2202.02441 (2022) - [i17]Abdulaziz Alhamadani, Xuchao Zhang, Jianfeng He, Chang-Tien Lu:
LANS: Large-scale Arabic News Summarization Corpus. CoRR abs/2210.13600 (2022) - [i16]Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, Liang Zhao:
DeepGAR: Deep Graph Learning for Analogical Reasoning. CoRR abs/2211.10821 (2022) - 2021
- [c32]Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B. Davidson:
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series. AAAI 2021: 651-659 - [c31]Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang:
Multi-Task Recurrent Modular Networks. AAAI 2021: 10496-10504 - [c30]Tao Wang, Zhiyuan Shao, Yifu Xiao, Xuchao Zhang, Yitian Chen, Binze Shi, Siyu Chen, Yuxian Wang, Jiajie Peng, Xuequn Shang:
Predicting Hepatoma-Related Genes Based on Representation Learning of PPI network and Gene Ontology Annotations. BIBM 2021: 1892-1898 - [c29]Jingchao Ni, Zhengzhang Chen, Wei Cheng, Bo Zong, Dongjin Song, Yanchi Liu, Xuchao Zhang, Haifeng Chen:
Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization. CIKM 2021: 1366-1375 - [c28]Liyan Xu, Xuchao Zhang, Xujiang Zhao, Haifeng Chen, Feng Chen, Jinho D. Choi:
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation. EMNLP (1) 2021: 6716-6723 - [c27]Jianfeng He, Bei Xiao, Xuchao Zhang, Shuo Lei, Shuhui Wang, Chang-Tien Lu:
Reducing Noise Pixels and Metric Bias in Semantic Inpainting on Segmentation Map. ICCVW 2021: 1876-1885 - [c26]Lichen Wang, Bo Zong, Yunyu Liu, Can Qin, Wei Cheng, Wenchao Yu, Xuchao Zhang, Haifeng Chen, Yun Fu:
Aspect-based Sentiment Classification via Reinforcement Learning. ICDM 2021: 1391-1396 - [c25]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
Few-Shot Semantic Segmentation via Prototype Augmentation with Image-Level Annotations. ICME 2021: 1-6 - [c24]Xuchao Zhang, Bo Zong, Wei Cheng, Jingchao Ni, Yanchi Liu, Haifeng Chen:
Unsupervised Concept Representation Learning for Length-Varying Text Similarity. NAACL-HLT 2021: 5611-5620 - [i15]Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B. Davidson:
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series. CoRR abs/2103.02164 (2021) - [i14]Dongsheng Luo, Wei Cheng, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Bo Zong, Yanchi Liu, Zhengzhang Chen, Dongjin Song, Haifeng Chen, Xiang Zhang:
Unsupervised Document Embedding via Contrastive Augmentation. CoRR abs/2103.14542 (2021) - [i13]Liyan Xu, Xuchao Zhang, Xujiang Zhao, Haifeng Chen, Feng Chen, Jinho D. Choi:
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation. CoRR abs/2109.00194 (2021) - [i12]Liyan Xu, Xuchao Zhang, Bo Zong, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao, Jinho D. Choi:
Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph. CoRR abs/2112.00503 (2021) - [i11]Junxiang Wang, Xuchao Zhang, Bo Zong, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao:
Do Multi-Lingual Pre-trained Language Models Reveal Consistent Token Attributions in Different Languages? CoRR abs/2112.12356 (2021) - 2020
- [c23]Xuchao Zhang, Yifeng Gao, Jessica Lin, Chang-Tien Lu:
TapNet: Multivariate Time Series Classification with Attentional Prototypical Network. AAAI 2020: 6845-6852 - [c22]Xuchao Zhang, Xian Wu, Fanglan Chen, Liang Zhao, Chang-Tien Lu:
Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data. AAAI 2020: 6853-6860 - [c21]Jianfeng He, Xuchao Zhang, Shuo Lei, Zhiqian Chen, Fanglan Chen, Abdulaziz Alhamadani, Bei Xiao, Chang-Tien Lu:
Towards More Accurate Uncertainty Estimation In Text Classification. EMNLP (1) 2020: 8362-8372 - [c20]Xuchao Zhang, Yingwen Shao:
Robust Multi-Target Regression for Correlated Data Corruption. ICDM 2020: 1406-1411 - [c19]Xuchao Zhang, Wei Cheng, Bo Zong, Yuncong Chen, Jianwu Xu, Ding Li, Haifeng Chen:
Temporal Context-Aware Representation Learning for Question Routing. WSDM 2020: 753-761 - [i10]Tian Shi, Xuchao Zhang, Ping Wang, Chandan K. Reddy:
A Concept-based Abstraction-Aggregation Deep Neural Network for Interpretable Document Classification. CoRR abs/2004.13003 (2020) - [i9]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations. CoRR abs/2007.01496 (2020) - [i8]Jianfeng He, Xuchao Zhang, Shuo Lei, Shuhui Wang, Qingming Huang, Chang-Tien Lu, Bei Xiao:
Semantic Editing On Segmentation Map Via Multi-Expansion Loss. CoRR abs/2010.08128 (2020)
2010 – 2019
- 2019
- [b1]Xuchao Zhang:
Scalable Robust Models Under Adversarial Data Corruption. Virginia Tech, Blacksburg, VA, USA, 2019 - [j1]Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu:
Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation. ACM Trans. Knowl. Discov. Data 13(3): 28:1-28:22 (2019) - [c18]Taoran Ji, Xuchao Zhang, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan:
Feature driven learning framework for cybersecurity event detection. ASONAM 2019: 196-203 - [c17]Chao Huang, Baoxu Shi, Xuchao Zhang, Xian Wu, Nitesh V. Chawla:
Similarity-Aware Network Embedding with Self-Paced Learning. CIKM 2019: 2113-2116 - [c16]Chao Huang, Xian Wu, Xuchao Zhang, Suwen Lin, Nitesh V. Chawla:
Deep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity. CIKM 2019: 2141-2144 - [c15]Xuchao Zhang, Dheeraj Rajagopal, Michael Gamon, Sujay Kumar Jauhar, Chang-Tien Lu:
Modeling the Relationship between User Comments and Edits in Document Revision. EMNLP/IJCNLP (1) 2019: 5001-5010 - [c14]Chao Huang, Xian Wu, Xuchao Zhang, Chuxu Zhang, Jiashu Zhao, Dawei Yin, Nitesh V. Chawla:
Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics. KDD 2019: 2613-2622 - [c13]Xuchao Zhang, Fanglan Chen, Chang-Tien Lu, Naren Ramakrishnan:
Mitigating Uncertainty in Document Classification. NAACL-HLT (1) 2019: 3126-3136 - [i7]Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu:
Robust Regression via Online Feature Selection under Adversarial Data Corruption. CoRR abs/1902.01729 (2019) - [i6]Xuchao Zhang, Fanglan Chen, Chang-Tien Lu, Naren Ramakrishnan:
Mitigating Uncertainty in Document Classification. CoRR abs/1907.07590 (2019) - 2018
- [c12]Lei Zhang, Liang Zhao, Xuchao Zhang, Wenmo Kong, Zitong Sheng, Chang-Tien Lu:
Situation-Based Interpretable Learning for Personality Prediction in Social Media. IEEE BigData 2018: 1554-1562 - [c11]Zhiqian Chen, Feng Chen, Rongjie Lai, Xuchao Zhang, Chang-Tien Lu:
Rational Neural Networks for Approximating Graph Convolution Operator on Jump Discontinuities. ICDM 2018: 59-68 - [c10]Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu:
Robust Regression via Online Feature Selection Under Adversarial Data Corruption. ICDM 2018: 1440-1445 - [c9]Xuchao Zhang, Liang Zhao, Zhiqian Chen, Chang-Tien Lu:
Distributed Self-Paced Learning in Alternating Direction Method of Multipliers. IJCAI 2018: 3148-3154 - [i5]Xuchao Zhang, Liang Zhao, Zhiqian Chen, Chang-Tien Lu:
Distributed Self-Paced Learning in Alternating Direction Method of Multipliers. CoRR abs/1807.02234 (2018) - [i4]Bingsheng Wang, Xuchao Zhang, Chang-Tien Lu, Feng Chen:
Water Disaggregation via Shape Features based Bayesian Discriminative Sparse Coding. CoRR abs/1808.08951 (2018) - [i3]Zhiqian Chen, Feng Chen, Rongjie Lai, Xuchao Zhang, Chang-Tien Lu:
Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator. CoRR abs/1808.10073 (2018) - 2017
- [c8]Xuchao Zhang, Liang Zhao, Zhiqian Chen, Arnold P. Boedihardjo, Jing Dai, Chang-Tien Lu:
Trendi: Tracking stories in news and microblogs via emerging, evolving and fading topics. IEEE BigData 2017: 1590-1599 - [c7]Xuchao Zhang, Zhiqian Chen, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu:
TRACES: Generating Twitter stories via shared subspace and temporal smoothness. IEEE BigData 2017: 1688-1693 - [c6]Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu, Naren Ramakrishnan:
Spatiotemporal Event Forecasting from Incomplete Hyper-local Price Data. CIKM 2017: 507-516 - [c5]Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu:
Online and Distributed Robust Regressions Under Adversarial Data Corruption. ICDM 2017: 625-634 - [c4]Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu:
Robust Regression via Heuristic Hard Thresholding. IJCAI 2017: 3434-3440 - [c3]Zhiqian Chen, Xuchao Zhang, Arnold P. Boedihardjo, Jing Dai, Chang-Tien Lu:
Multimodal Storytelling via Generative Adversarial Imitation Learning. IJCAI 2017: 3967-3973 - [i2]Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu:
Online and Distributed Robust Regressions under Adversarial Data Corruption. CoRR abs/1710.00904 (2017) - [i1]Zhiqian Chen, Xuchao Zhang, Arnold P. Boedihardjo, Jing Dai, Chang-Tien Lu:
Multimodal Storytelling via Generative Adversarial Imitation Learning. CoRR abs/1712.01455 (2017) - 2016
- [c2]Xuchao Zhang, Zhiqian Chen, Weisheng Zhong, Arnold P. Boedihardjo, Chang-Tien Lu:
Storytelling in heterogeneous Twitter entity network based on hierarchical cluster routing. IEEE BigData 2016: 1522-1531 - [c1]Ting Hua, Xuchao Zhang, Wei Wang, Chang-Tien Lu, Naren Ramakrishnan:
Automatical Storyline Generation with Help from Twitter. CIKM 2016: 2383-2388
Coauthor Index
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