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- affiliation: Arizona State University, Tempe, AZ, USA
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2020 – today
- 2024
[j13]Qiang Huang
, Jing Ma, Jundong Li, Ruocheng Guo, Huiyan Sun, Yi Chang:
Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data. ACM Trans. Knowl. Discov. Data 18(3): 48:1-48:21 (2024)- [j12]Jingtong Gao, Xiangyu Zhao, Muyang Li, Minghao Zhao, Runze Wu, Ruocheng Guo, Yiding Liu, Dawei Yin:
SMLP4Rec: An Efficient All-MLP Architecture for Sequential Recommendations. ACM Trans. Inf. Syst. 42(3): 86:1-86:23 (2024) - [c55]Bohan Jiang, Lu Cheng, Zhen Tan, Ruocheng Guo, Huan Liu:
Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media. DSAA 2024: 1-10 - [c54]Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu:
Fair Classifiers that Abstain without Harm. ICLR 2024 - [c53]Zonghao Chen, Ruocheng Guo, Jean-Francois Ton, Yang Liu:
Conformal Counterfactual Inference under Hidden Confounding. KDD 2024: 397-408 - [c52]Qinwei Yang, Xueqing Liu, Yan Zeng, Ruocheng Guo, Yang Liu, Peng Wu:
Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards. NeurIPS 2024 - [c51]Sheng Zhang, Maolin Wang, Xiangyu Zhao, Ruocheng Guo, Yao Zhao, Chenyi Zhuang, Jinjie Gu, Zijian Zhang, Hongzhi Yin:
DNS-Rec: Data-aware Neural Architecture Search for Recommender Systems. RecSys 2024: 591-600 - [c50]Maolin Wang, Yaoming Zhen, Yu Pan, Yao Zhao, Chenyi Zhuang, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao:
Tensorized Hypergraph Neural Networks. SDM 2024: 127-135 - [c49]Maolin Wang, Yao Zhao, Jiajia Liu, Jingdong Chen, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao:
Large Multimodal Model Compression via Iterative Efficient Pruning and Distillation. WWW (Companion Volume) 2024: 235-244 - [i56]Maolin Wang, Yu Pan, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao, Wanyu Wang, Yiqi Wang, Zitao Liu, Langming Liu:
Cumulative Distribution Function based General Temporal Point Processes. CoRR abs/2402.00388 (2024) - [i55]Sheng Zhang, Maolin Wang, Yao Zhao, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao, Zijian Zhang, Hongzhi Yin:
EASRec: Elastic Architecture Search for Efficient Long-term Sequential Recommender Systems. CoRR abs/2402.00390 (2024) - [i54]Chen Wang, Fangxin Wang, Ruocheng Guo, Yueqing Liang, Kay Liu, Philip S. Yu:
Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction. CoRR abs/2402.08976 (2024) - [i53]Xinjian Zhao, Liang Zhang, Yang Liu, Ruocheng Guo, Xiangyu Zhao:
Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation. CoRR abs/2402.10468 (2024) - [i52]Zhen Tan, Alimohammad Beigi, Song Wang, Ruocheng Guo, Amrita Bhattacharjee, Bohan Jiang, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu:
Large Language Models for Data Annotation: A Survey. CoRR abs/2402.13446 (2024) - [i51]Bohan Jiang, Lu Cheng, Zhen Tan, Ruocheng Guo, Huan Liu:
Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media. CoRR abs/2403.04009 (2024) - [i50]Zonghao Chen, Ruocheng Guo, Jean-François Ton, Yang Liu:
Conformal Counterfactual Inference under Hidden Confounding. CoRR abs/2405.12387 (2024) - [i49]Jingyu Peng, Maolin Wang, Xiangyu Zhao, Kai Zhang, Wanyu Wang, Pengyue Jia, Qi Liu, Ruocheng Guo, Qi Liu:
Stepwise Reasoning Error Disruption Attack of LLMs. CoRR abs/2412.11934 (2024) - 2023
- [j11]Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, Kasim Selçuk Candan:
Causal Disentanglement for Implicit Recommendations with Network Information. ACM Trans. Knowl. Discov. Data 17(7): 94:1-94:18 (2023) - [c48]Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li:
Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance. EMNLP (Findings) 2023: 12528-12540 - [c47]Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao:
Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization. ICDM 2023: 1361-1366 - [c46]Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li:
Learning for Counterfactual Fairness from Observational Data. KDD 2023: 1620-1630 - [c45]Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu:
Virtual Node Tuning for Few-shot Node Classification. KDD 2023: 2177-2188 - [c44]Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo:
Debiasing Recommendation by Learning Identifiable Latent Confounders. KDD 2023: 3353-3363 - [c43]Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang:
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems. KDD 2023: 3865-3876 - [c42]Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu:
Equal Opportunity of Coverage in Fair Regression. NeurIPS 2023 - [c41]Yichuan Li, Kyumin Lee, Nima Kordzadeh, Ruocheng Guo:
What Boosts Fake News Dissemination on Social Media? A Causal Inference View. PAKDD (4) 2023: 234-246 - [c40]Muyang Li, Zijian Zhang, Xiangyu Zhao, Wanyu Wang, Minghao Zhao, Runze Wu, Ruocheng Guo:
AutoMLP: Automated MLP for Sequential Recommendations. WWW 2023: 1190-1198 - [i48]Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo:
Debiasing Recommendation by Learning Identifiable Latent Confounders. CoRR abs/2302.05052 (2023) - [i47]Muyang Li, Zijian Zhang, Xiangyu Zhao, Wanyu Wang, Minghao Zhao, Runze Wu, Ruocheng Guo:
AutoMLP: Automated MLP for Sequential Recommendations. CoRR abs/2303.06337 (2023) - [i46]Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang:
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems. CoRR abs/2305.16391 (2023) - [i45]Maolin Wang, Yaoming Zhen, Yu Pan, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao:
Tensorized Hypergraph Neural Networks. CoRR abs/2306.02560 (2023) - [i44]Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu:
Virtual Node Tuning for Few-shot Node Classification. CoRR abs/2306.06063 (2023) - [i43]Ruocheng Guo, Jean-François Ton, Yang Liu:
Fair Learning to Rank with Distribution-free Risk Control. CoRR abs/2306.07188 (2023) - [i42]Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li:
Learning for Counterfactual Fairness from Observational Data. CoRR abs/2307.08232 (2023) - [i41]Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li:
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment. CoRR abs/2308.05374 (2023) - [i40]Yegor Klochkov, Jean-Francois Ton, Ruocheng Guo, Yang Liu, Hang Li:
Deep Concept Removal. CoRR abs/2310.05755 (2023) - [i39]Tongxin Yin, Jean-François Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu:
Fair Classifiers that Abstain without Harm. CoRR abs/2310.06205 (2023) - [i38]Xiangyu Zhao, Maolin Wang, Xinjian Zhao, Jiansheng Li, Shucheng Zhou, Dawei Yin, Qing Li, Jiliang Tang, Ruocheng Guo:
Embedding in Recommender Systems: A Survey. CoRR abs/2310.18608 (2023) - [i37]Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li:
Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance. CoRR abs/2311.01108 (2023) - [i36]Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S. Yu:
Equal Opportunity of Coverage in Fair Regression. CoRR abs/2311.02243 (2023) - [i35]Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao:
Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization. CoRR abs/2311.10341 (2023) - [i34]Maolin Wang, Yao Zhao, Jiajia Liu, Jingdong Chen, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao:
Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup. CoRR abs/2312.05795 (2023) - 2022
- [j10]Jiayu Shang, Xubo Tang, Ruocheng Guo, Yanni Sun:
Accurate identification of bacteriophages from metagenomic data using Transformer. Briefings Bioinform. 23(4) (2022) - [j9]Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu:
Evaluation Methods and Measures for Causal Learning Algorithms. IEEE Trans. Artif. Intell. 3(6): 924-943 (2022) - [c39]Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. IEEE Big Data 2022: 596-605 - [c38]Anique Tahir, Lu Cheng, Ruocheng Guo, Huan Liu:
Distributional Shift Adaptation using Domain-Specific Features. IEEE Big Data 2022: 5593-5597 - [c37]Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu:
Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective. ICDM 2022: 438-447 - [c36]Lu Cheng, Ruocheng Guo, Kasim Selçuk Candan, Huan Liu:
Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. ICWSM 2022: 67-78 - [c35]Muyang Li, Xiangyu Zhao, Chuan Lyu, Minghao Zhao, Runze Wu, Ruocheng Guo:
MLP4Rec: A Pure MLP Architecture for Sequential Recommendations. IJCAI 2022: 2138-2144 - [c34]Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li:
CLEAR: Generative Counterfactual Explanations on Graphs. NeurIPS 2022 - [c33]Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu:
Supervised Graph Contrastive Learning for Few-Shot Node Classification. ECML/PKDD (2) 2022: 394-411 - [c32]Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Selçuk Candan, Huan Liu:
Causal Disentanglement with Network Information for Debiased Recommendations. SISAP 2022: 265-273 - [c31]Lu Cheng, Ruocheng Guo, Huan Liu:
Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies. WSDM 2022: 103-112 - [c30]Lu Cheng, Ruocheng Guo, Huan Liu:
Causal Mediation Analysis with Hidden Confounders. WSDM 2022: 113-122 - [c29]Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li:
Learning Fair Node Representations with Graph Counterfactual Fairness. WSDM 2022: 695-703 - [c28]Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu:
Graph Few-shot Class-incremental Learning. WSDM 2022: 987-996 - [i33]Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li:
Learning Fair Node Representations with Graph Counterfactual Fairness. CoRR abs/2201.03662 (2022) - [i32]Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu:
Evaluation Methods and Measures for Causal Learning Algorithms. CoRR abs/2202.02896 (2022) - [i31]Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu:
A Simple Yet Effective Pretraining Strategy for Graph Few-shot Learning. CoRR abs/2203.15936 (2022) - [i30]Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, K. Selçuk Candan:
Causal Disentanglement with Network Information for Debiased Recommendations. CoRR abs/2204.07221 (2022) - [i29]Muyang Li, Xiangyu Zhao, Chuan Lyu, Minghao Zhao, Runze Wu, Ruocheng Guo:
MLP4Rec: A Pure MLP Architecture for Sequential Recommendations. CoRR abs/2204.11510 (2022) - [i28]Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li:
CLEAR: Generative Counterfactual Explanations on Graphs. CoRR abs/2210.08443 (2022) - [i27]Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu:
Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective. CoRR abs/2211.01154 (2022) - [i26]Anique Tahir, Lu Cheng, Ruocheng Guo, Huan Liu:
Distributional Shift Adaptation using Domain-Specific Features. CoRR abs/2211.04670 (2022) - [i25]Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks. CoRR abs/2212.12621 (2022) - 2021
- [j8]Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, Huan Liu:
A Survey of Learning Causality with Data: Problems and Methods. ACM Comput. Surv. 53(4): 75:1-75:37 (2021) - [j7]Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu, Xia Hu:
Adversarial Attacks and Defenses: An Interpretation Perspective. SIGKDD Explor. 23(1): 86-99 (2021) - [j6]Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah L. Hall, Huan Liu:
Modeling Temporal Patterns of Cyberbullying Detection with Hierarchical Attention Networks. Trans. Data Sci. 2(2): 8:1-8:23 (2021) - [c27]Paras Sheth, Ujun Jeong, Ruocheng Guo, Huan Liu, K. Selçuk Candan:
CauseBox: A Causal Inference Toolbox for BenchmarkingTreatment Effect Estimators with Machine Learning Methods. CIKM 2021: 4789-4793 - [c26]Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li:
Multi-Cause Effect Estimation with Disentangled Confounder Representation. IJCAI 2021: 2790-2796 - [c25]Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Causal Understanding of Fake News Dissemination on Social Media. KDD 2021: 148-157 - [c24]Jing Ma, Ruocheng Guo, Chen Chen, Aidong Zhang, Jundong Li:
Deconfounding with Networked Observational Data in a Dynamic Environment. WSDM 2021: 166-174 - [c23]Lu Cheng, Ruocheng Guo, Huan Liu:
Long-Term Effect Estimation with Surrogate Representation. WSDM 2021: 274-282 - [i24]Ruocheng Guo, Pengchuan Zhang, Hao Liu, Emre Kiciman:
Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix. CoRR abs/2101.07732 (2021) - [i23]Lu Cheng, Ruocheng Guo, Huan Liu:
Causal Mediation Analysis with Hidden Confounders. CoRR abs/2102.11724 (2021) - [i22]Lu Cheng, Ruocheng Guo, Kasim Selçuk Candan, Huan Liu:
Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication. CoRR abs/2110.01746 (2021) - [i21]Lu Cheng, Ruocheng Guo, Huan Liu:
Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies. CoRR abs/2112.10274 (2021) - [i20]Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu:
Graph Few-shot Class-incremental Learning. CoRR abs/2112.12819 (2021) - 2020
- [j5]Raha Moraffah, Mansooreh Karami, Ruocheng Guo, Adrienne Raglin, Huan Liu:
Causal Interpretability for Machine Learning - Problems, Methods and Evaluation. SIGKDD Explor. 22(1): 18-33 (2020) - [j4]Ericsson Marin, Ruocheng Guo, Paulo Shakarian:
Measuring Time-Constrained Influence to Predict Adoption in Online Social Networks. ACM Trans. Soc. Comput. 3(3): 13:1-13:26 (2020) - [c22]Ruocheng Guo, Jundong Li, Yichuan Li, K. Selçuk Candan, Adrienne Raglin, Huan Liu:
IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data. IJCAI 2020: 4534-4540 - [c21]Ruocheng Guo, Xiaoting Zhao, Adam Henderson, Liangjie Hong, Huan Liu:
Debiasing Grid-based Product Search in E-commerce. KDD 2020: 2852-2860 - [c20]Ruocheng Guo, Jundong Li, Huan Liu:
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data. SDM 2020: 271-279 - [c19]Lu Cheng, Ruocheng Guo, K. Selçuk Candan, Huan Liu:
Representation Learning for Imbalanced Cross-Domain Classification. SDM 2020: 478-486 - [c18]Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo, Hamidreza Alvari, Alexander Nou, Huan Liu:
Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning. WSDM 2020: 34-42 - [c17]Ruocheng Guo, Jundong Li, Huan Liu:
Learning Individual Causal Effects from Networked Observational Data. WSDM 2020: 232-240 - [i19]Raha Moraffah, Mansooreh Karami, Ruocheng Guo, Adrienne Raglin, Huan Liu:
Causal Interpretability for Machine Learning - Problems, Methods and Evaluation. CoRR abs/2003.03934 (2020) - [i18]Lu Cheng, Ruocheng Guo, Huan Liu:
Long-Term Effect Estimation with Surrogate Representation. CoRR abs/2008.08236 (2020) - [i17]Lu Cheng, Ruocheng Guo, Kai Shu, Huan Liu:
Towards Causal Understanding of Fake News Dissemination. CoRR abs/2010.10580 (2020)
2010 – 2019
- 2019
- [j3]Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian:
Using network motifs to characterize temporal network evolution leading to diffusion inhibition. Soc. Netw. Anal. Min. 9(1): 14:1-14:24 (2019) - [c16]Jundong Li, Liang Wu, Ruocheng Guo, Chenghao Liu, Huan Liu:
Multi-level network embedding with boosted low-rank matrix approximation. ASONAM 2019: 49-56 - [c15]Yichuan Li, Ruocheng Guo, Weiying Wang, Huan Liu:
Causal Learning in Question Quality Improvement. Bench 2019: 204-214 - [c14]Lu Cheng, Ruocheng Guo, Raha Moraffah, K. Selçuk Candan, Adrienne Raglin, Huan Liu:
A Practical Data Repository for Causal Learning with Big Data. Bench 2019: 234-248 - [c13]Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu:
Privacy Preserving Text Representation Learning. HT 2019: 275-276 - [c12]Jundong Li, Ruocheng Guo, Chenghao Liu, Huan Liu:
Adaptive Unsupervised Feature Selection on Attributed Networks. KDD 2019: 92-100 - [c11]Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah L. Hall, Huan Liu:
Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network. SDM 2019: 235-243 - [c10]Ghazaleh Beigi, Ruocheng Guo, Alexander Nou, Yanchao Zhang, Huan Liu:
Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles. WSDM 2019: 213-221 - [c9]Lu Cheng, Ruocheng Guo, Huan Liu:
Robust Cyberbullying Detection with Causal Interpretation. WWW (Companion Volume) 2019: 169-175 - [i16]Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian:
Using network motifs to characterize temporal network evolution leading to diffusion inhibition. CoRR abs/1903.00862 (2019) - [i15]Elham Shaabani, Ruocheng Guo, Paulo Shakarian:
Detecting Pathogenic Social Media Accounts without Content or Network Structure. CoRR abs/1905.01556 (2019) - [i14]Ruocheng Guo, Jundong Li, Huan Liu:
Learning Individual Treatment Effects from Networked Observational Data. CoRR abs/1906.03485 (2019) - [i13]Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu:
I Am Not What I Write: Privacy Preserving Text Representation Learning. CoRR abs/1907.03189 (2019) - [i12]Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo, Hamidreza Alvari, Alexander Nou, Huan Liu:
Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning. CoRR abs/1911.09872 (2019) - [i11]Ruocheng Guo, Jundong Li, Huan Liu:
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data. CoRR abs/1912.10536 (2019) - 2018
- [c8]Vineeth Rakesh, Ruocheng Guo, Raha Moraffah, Nitin Agarwal, Huan Liu:
Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects. CIKM 2018: 1679-1682 - [c7]Elham Shaabani, Ruocheng Guo, Paulo Shakarian:
Detecting Pathogenic Social Media Accounts without Content or Network Structure. ICDIS 2018: 57-64 - [c6]Ruocheng Guo, Jundong Li, Huan Liu:
INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process. IJCAI 2018: 2191-2197 - [c5]Ruocheng Guo, Hamidreza Alvari, Paulo Shakarian:
Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression. SDM 2018: 729-737 - [i10]Vineeth Rakesh, Ruocheng Guo, Raha Moraffah, Nitin Agarwal, Huan Liu:
Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects. CoRR abs/1808.03333 (2018) - [i9]Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian:
Understanding and forecasting lifecycle events in information cascades. CoRR abs/1809.06050 (2018) - [i8]Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, Huan Liu:
A Survey of Learning Causality with Data: Problems and Methods. CoRR abs/1809.09337 (2018) - [i7]Ghazaleh Beigi, Ruocheng Guo, Alexander Nou, Yanchao Zhang, Huan Liu:
Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles. CoRR abs/1811.09340 (2018) - 2017
- [j2]Soumajyoti Sarkar, Ruocheng Guo, Paulo Shakarian:
Understanding and forecasting lifecycle events in information cascades. Soc. Netw. Anal. Min. 7(1): 55:1-55:22 (2017) - [c4]Ericsson Marin, Ruocheng Guo, Paulo Shakarian:
Temporal Analysis of Influence to Predict Users' Adoption in Online Social Networks. SBP-BRiMS 2017: 254-261 - [i6]Ericsson Marin, Ruocheng Guo, Paulo Shakarian:
Temporal Analysis of Influence to Predict Users' Adoption in Online Social Networks. CoRR abs/1705.02399 (2017) - [i5]Ruocheng Guo, Hamidreza Alvari, Paulo Shakarian:
Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression. CoRR abs/1712.09133 (2017) - 2016
- [j1]Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar, Paulo Shakarian:
Toward early and order-of-magnitude cascade prediction in social networks. Soc. Netw. Anal. Min. 6(1): 64:1-64:18 (2016) - [c3]Ruocheng Guo, Paulo Shakarian:
A comparison of methods for cascade prediction. ASONAM 2016: 591-598 - [c2]Nikhil Kumar, Ruocheng Guo, Ashkan Aleali, Paulo Shakarian:
An empirical evaluation of social influence metrics. ASONAM 2016: 1329-1336 - [i4]Ruocheng Guo, Paulo Shakarian:
A Comparison of Methods for Cascade Prediction. CoRR abs/1606.05730 (2016) - [i3]Nikhil Kumar, Ruocheng Guo, Ashkan Aleali, Paulo Shakarian:
An Empirical Evaluation Of Social Influence Metrics. CoRR abs/1607.00720 (2016) - [i2]Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar, Paulo Shakarian:
Toward Early and Order-of-Magnitude Cascade Prediction in Social Networks. CoRR abs/1608.02646 (2016) - 2015
- [b1]Paulo Shakarian, Abhinav Bhatnagar, Ashkan Aleali, Elham Shaabani, Ruocheng Guo:
Diffusion in Social Networks. Springer Briefs in Computer Science, Springer 2015, ISBN 978-3-319-23104-4, pp. 1-101 - [c1]Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar, Paulo Shakarian:
Toward Order-of-Magnitude Cascade Prediction. ASONAM 2015: 1610-1613 - [i1]Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar, Paulo Shakarian:
Toward Order-of-Magnitude Cascade Prediction. CoRR abs/1508.03371 (2015)
Coauthor Index
K. Selçuk Candan
aka: Kasim Selçuk Candan
aka: Kasim Selçuk Candan
[c55] [i52] [i51] [j11] [c45] [i44] [j9] [c39] [c38] [c36] [c33] [c32] [c31] [c30] [c28] [i32] [i31] [i30] [i26] [i25] [j8] [j7] [j6] [c27] [c25] [c23] [i23] [i22] [i21] [i20] [j5] [c22] [c21] [c20] [c19] [c18] [c17] [i19] [i18] [i17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [i14] [i13] [i12] [i11] [c8] [c6] [i10] [i8] [i7]
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last updated on 2025-02-12 00:06 CET by the dblp team
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