default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJames Caverlee
Person information
- affiliation: Texas A&M University
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j24]Kaize Ding
, Jianling Wang, Jundong Li, James Caverlee, Huan Liu:
Robust Graph Meta-Learning for Weakly Supervised Few-Shot Node Classification. ACM Trans. Knowl. Discov. Data 18(4): 83:1-83:18 (2024)- [c165]Takeshi Onishi, James Caverlee:
Political Bias of Large Language Models in Few-Shot News Summarization. BIAS 2024: 32-45 - [c164]Rui Yang, Haoran Liu, Edison Marrese-Taylor, Qingcheng Zeng, Yuhe Ke, Wanxin Li, Lechao Cheng, Qingyu Chen, James Caverlee, Yutaka Matsuo, Irene Li:
KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques. BioNLP@ACL 2024: 155-166 - [c163]Chengkai Liu, Jianghao Lin, Hanzhou Liu, Jianling Wang, James Caverlee:
Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation. CIKM 2024: 1430-1440 - [c162]Rohan Chaudhury, Maria Teleki, Xiangjue Dong, James Caverlee:
DACL: Disfluency Augmented Curriculum Learning for Fluent Text Generation. LREC/COLING 2024: 4311-4321 - [c161]Maria Teleki, Xiangjue Dong, James Caverlee:
Quantifying the Impact of Disfluency on Spoken Content Summarization. LREC/COLING 2024: 13419-13428 - [c160]Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, Shu Kong:
The Neglected Tails in Vision-Language Models. CVPR 2024: 12988-12997 - [c159]Allen Lin, Jianling Wang, Ziwei Zhu, James Caverlee:
Federated Conversational Recommender Systems. ECIR (5) 2024: 50-65 - [c158]Jinhao Pan, Ziwei Zhu, Jianling Wang, Allen Lin, James Caverlee:
Countering Mainstream Bias via End-to-End Adaptive Local Learning. ECIR (5) 2024: 75-89 - [c157]Yibo Wang, Xiangjue Dong, James Caverlee, Philip S. Yu:
DA³: A Distribution-Aware Adversarial Attack against Language Models. EMNLP 2024: 1808-1825 - [c156]Zhuoer Wang, Leonardo F. R. Ribeiro, Alexandros Papangelis, Rohan Mukherjee, Tzu-Yen Wang, Xinyan Zhao, Arijit Biswas, James Caverlee, Angeliki Metallinou:
FANTAstic SEquences and Where to Find Them: Faithful and Efficient API Call Generation through State-tracked Constrained Decoding and Reranking. EMNLP (Findings) 2024: 6179-6191 - [c155]Guanchu Wang, Yu-Neng Chuang, Ruixiang Tang, Shaochen Zhong, Jiayi Yuan, Hongye Jin, Zirui Liu, Vipin Chaudhary, Shuai Xu, James Caverlee, Xia Ben Hu:
Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion. EMNLP 2024: 6928-6941 - [c154]Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, James Caverlee, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Improving Data Efficiency for Recommenders and LLMs. RecSys 2024: 790-792 - [c153]Haoran Liu, Bokun Wang, Jianling Wang, Xiangjue Dong, Tianbao Yang, James Caverlee:
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks. WWW (Companion Volume) 2024: 485-488 - [c152]Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen:
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. WWW (Companion Volume) 2024: 726-729 - [i44]Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, Shu Kong:
The Neglected Tails of Vision-Language Models. CoRR abs/2401.12425 (2024) - [i43]Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H. Chi, James Caverlee, Julian J. McAuley, Derek Zhiyuan Cheng:
How to Train Data-Efficient LLMs. CoRR abs/2402.09668 (2024) - [i42]Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee:
Disclosure and Mitigation of Gender Bias in LLMs. CoRR abs/2402.11190 (2024) - [i41]Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen:
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. CoRR abs/2402.11724 (2024) - [i40]Chengkai Liu, Jianghao Lin, Jianling Wang, Hanzhou Liu, James Caverlee:
Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models. CoRR abs/2403.03900 (2024) - [i39]Rui Yang, Haoran Liu, Edison Marrese-Taylor, Qingcheng Zeng, Yuhe Ke, Wanxin Li, Lechao Cheng, Qingyu Chen, James Caverlee, Yutaka Matsuo, Irene Li:
KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques. CoRR abs/2403.05881 (2024) - [i38]Jinhao Pan, Ziwei Zhu, Jianling Wang, Allen Lin, James Caverlee:
Countering Mainstream Bias via End-to-End Adaptive Local Learning. CoRR abs/2404.08887 (2024) - [i37]Chengkai Liu, Jianghao Lin, Hanzhou Liu, Jianling Wang, James Caverlee:
Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation. CoRR abs/2406.12580 (2024) - [i36]Zhuoer Wang, Leonardo F. R. Ribeiro, Alexandros Papangelis, Rohan Mukherjee, Tzu-Yen Wang, Xinyan Zhao, Arijit Biswas, James Caverlee, Angeliki Metallinou:
FANTAstic SEquences and Where to Find Them: Faithful and Efficient API Call Generation through State-tracked Constrained Decoding and Reranking. CoRR abs/2407.13945 (2024) - [i35]Chengkai Liu, Jianling Wang, James Caverlee:
TwinCL: A Twin Graph Contrastive Learning Model for Collaborative Filtering. CoRR abs/2409.19169 (2024) - [i34]Guanchu Wang, Yu-Neng Chuang, Ruixiang Tang, Shaochen Zhong, Jiayi Yuan, Hongye Jin, Zirui Liu, Vipin Chaudhary, Shuai Xu, James Caverlee, Xia Hu:
Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion. CoRR abs/2410.05331 (2024) - [i33]Millennium Bismay, Xiangjue Dong, James Caverlee:
ReasoningRec: Bridging Personalized Recommendations and Human-Interpretable Explanations through LLM Reasoning. CoRR abs/2410.23180 (2024) - 2023
- [c151]Xiangjue Dong, Yun He, Ziwei Zhu, James Caverlee:
PromptAttack: Probing Dialogue State Trackers with Adversarial Prompts. ACL (Findings) 2023: 10651-10666 - [c150]Karthic Madanagopal, James Caverlee:
Reinforced Sequence Training based Subjective Bias Correction. EACL 2023: 2577-2590 - [c149]Xiangjue Dong, Jiaying Lu, Jianling Wang, James Caverlee:
Closed-book Question Generation via Contrastive Learning. EACL 2023: 3142-3154 - [c148]Han Zhang, Ziwei Zhu, James Caverlee:
Evolution of Filter Bubbles and Polarization in News Recommendation. ECIR (2) 2023: 685-693 - [c147]Zhuoer Wang, Yicheng Wang, Ziwei Zhu, James Caverlee:
Unsupervised Candidate Answer Extraction through Differentiable Masker-Reconstructor Model. EMNLP (Findings) 2023: 5712-5723 - [c146]Xiangjue Dong, Ziwei Zhu, Zhuoer Wang, Maria Teleki, James Caverlee:
Co²PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning. EMNLP (Findings) 2023: 5859-5871 - [c145]Karthic Madanagopal, James Caverlee:
Bias Neutralization in Non-Parallel Texts: A Cyclic Approach with Auxiliary Guidance. EMNLP 2023: 14265-14278 - [c144]Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). KDD 2023: 5608-5617 - [c143]Mostafa Rahmani, James Caverlee, Fei Wang:
Incorporating Time in Sequential Recommendation Models. RecSys 2023: 784-790 - [c142]Allen Lin, Ziwei Zhu, Jianling Wang, James Caverlee:
Enhancing User Personalization in Conversational Recommenders. WWW 2023: 770-778 - [i32]Han Zhang, Ziwei Zhu, James Caverlee:
Evolution of Filter Bubbles and Polarization in News Recommendation. CoRR abs/2301.10926 (2023) - [i31]Allen Lin, Ziwei Zhu, Jianling Wang, James Caverlee:
Enhancing User Personalization in Conversational Recommenders. CoRR abs/2302.06656 (2023) - [i30]Yingqiang Ge, Mostafa Rahmani, Athirai A. Irissappane, Jose Sepulveda, James Caverlee, Fei Wang:
Automated Data Denoising for Recommendation. CoRR abs/2305.07070 (2023) - [i29]Xiangjue Dong, Yun He, Ziwei Zhu, James Caverlee:
PromptAttack: Probing Dialogue State Trackers with Adversarial Prompts. CoRR abs/2306.04535 (2023) - [i28]Haoran Liu, Bokun Wang, Jianling Wang, Xiangjue Dong, Tianbao Yang, James Caverlee:
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks. CoRR abs/2308.15614 (2023) - [i27]Xiangjue Dong, Ziwei Zhu, Zhuoer Wang, Maria Teleki, James Caverlee:
Co$^2$PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning. CoRR abs/2310.12490 (2023) - [i26]Zhuoer Wang, Yicheng Wang, Ziwei Zhu, James Caverlee:
Unsupervised Candidate Answer Extraction through Differentiable Masker-Reconstructor Model. CoRR abs/2310.13106 (2023) - [i25]Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee:
Probing Explicit and Implicit Gender Bias through LLM Conditional Text Generation. CoRR abs/2311.00306 (2023) - [i24]Yibo Wang, Xiangjue Dong, James Caverlee, Philip S. Yu:
DALA: A Distribution-Aware LoRA-Based Adversarial Attack against Pre-trained Language Models. CoRR abs/2311.08598 (2023) - 2022
- [j23]Weiwen Liu, Yin Zhang, Jianling Wang, Yun He, James Caverlee, Patrick P. K. Chan, Daniel S. Yeung, Pheng-Ann Heng:
Item Relationship Graph Neural Networks for E-Commerce. IEEE Trans. Neural Networks Learn. Syst. 33(9): 4785-4799 (2022) - [c141]Kaize Ding, Jianling Wang, James Caverlee, Huan Liu:
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning. AAAI 2022: 6524-6531 - [c140]Zhuoer Wang, Qizhang Feng, Mohinish Chatterjee, Xing Zhao, Yezi Liu, Yuening Li, Abhay Kumar Singh, Frank M. Shipman, Xia Hu, James Caverlee:
RES: An Interpretable Replicability Estimation System for Research Publications. AAAI 2022: 13230-13232 - [c139]Allen Lin, Jianling Wang, Ziwei Zhu, James Caverlee:
Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems. CIKM 2022: 1238-1247 - [c138]Ziwei Zhu, James Caverlee:
Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning. WSDM 2022: 1497-1506 - [c137]Karthic Madanagopal, James Caverlee:
Improving Linguistic Bias Detection in Wikipedia using Cross-Domain Adaptive Pre-Training. WWW (Companion Volume) 2022: 1301-1309 - [c136]Yun He, Xue Feng, Cheng Cheng, Geng Ji, Yunsong Guo, James Caverlee:
MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks. WWW 2022: 2205-2215 - [i23]Yun He, Xue Feng, Cheng Cheng, Geng Ji, Yunsong Guo, James Caverlee:
MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks. CoRR abs/2203.06801 (2022) - [i22]Ziwei Zhu, Yun He, Xing Zhao, James Caverlee:
Evolution of Popularity Bias: Empirical Study and Debiasing. CoRR abs/2207.03372 (2022) - [i21]Allen Lin, Jianling Wang, Ziwei Zhu, James Caverlee:
Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems. CoRR abs/2208.03298 (2022) - [i20]Allen Lin, Ziwei Zhu, Jianling Wang, James Caverlee:
Towards Fair Conversational Recommender Systems. CoRR abs/2208.03854 (2022) - [i19]Xiangjue Dong, Jiaying Lu, Jianling Wang, James Caverlee:
Closed-book Question Generation via Contrastive Learning. CoRR abs/2210.06781 (2022) - [i18]Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). CoRR abs/2210.14309 (2022) - 2021
- [c135]Yin Zhang, Yun He, James Caverlee:
Vibe check: social resonance learning for enhanced recommendation. ASONAM 2021: 164-167 - [c134]Ziwei Zhu, Yun He, Xing Zhao, James Caverlee:
Popularity Bias in Dynamic Recommendation. KDD 2021: 2439-2449 - [c133]Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee:
Session-based Recommendation with Hypergraph Attention Networks. SDM 2021: 82-90 - [c132]Ziwei Zhu, Jingu Kim, Trung Nguyen, Aish Fenton, James Caverlee:
Fairness among New Items in Cold Start Recommender Systems. SIGIR 2021: 767-776 - [c131]Jianling Wang, Kaize Ding, James Caverlee:
Sequential Recommendation for Cold-start Users with Meta Transitional Learning. SIGIR 2021: 1783-1787 - [c130]Ziwei Zhu, Yun He, Xing Zhao, Yin Zhang, Jianling Wang, James Caverlee:
Popularity-Opportunity Bias in Collaborative Filtering. WSDM 2021: 85-93 - [c129]Karthic Madanagopal, James Caverlee:
Towards Ongoing Detection of Linguistic Bias on Wikipedia. WWW (Companion Volume) 2021: 629-631 - [c128]Xing Zhao, Ziwei Zhu, James Caverlee:
Rabbit Holes and Taste Distortion: Distribution-Aware Recommendation with Evolving Interests. WWW 2021: 888-899 - [i17]Ziwei Zhu, Jianling Wang, James Caverlee:
Fairness-aware Personalized Ranking Recommendation via Adversarial Learning. CoRR abs/2103.07849 (2021) - [i16]Jian Wu, Rajal Nivargi, Sree Sai Teja Lanka, Arjun Manoj Menon, Sai Ajay Modukuri, Nishanth Nakshatri, Xin Wei, Zhuoer Wang, James Caverlee, Sarah Michele Rajtmajer, C. Lee Giles:
Predicting the Reproducibility of Social and Behavioral Science Papers Using Supervised Learning Models. CoRR abs/2104.04580 (2021) - [i15]Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, Huan Liu:
Weakly-supervised Graph Meta-learning for Few-shot Node Classification. CoRR abs/2106.06873 (2021) - [i14]Monika Daryani, James Caverlee:
Identifying Hijacked Reviews. CoRR abs/2107.05385 (2021) - [i13]Jianling Wang, Kaize Ding, James Caverlee:
Sequential Recommendation for Cold-start Users with Meta Transitional Learning. CoRR abs/2107.06427 (2021) - [i12]Kaize Ding, Jianling Wang, James Caverlee, Huan Liu:
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning. CoRR abs/2112.09810 (2021) - [i11]Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee:
Session-based Recommendation with Hypergraph Attention Networks. CoRR abs/2112.14266 (2021) - 2020
- [c127]Parisa Kaghazgaran, James Caverlee:
Towards an Automated Writing Assistant for Online Reviews. AutomationXP@CHI 2020 - [c126]Jianling Wang, James Caverlee:
Recommending Music Curators: A Neural Style-Aware Approach. ECIR (1) 2020: 191-204 - [c125]Yun He, Ziwei Zhu, Yin Zhang, Qin Chen, James Caverlee:
Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition. EMNLP (1) 2020: 4604-4614 - [c124]Yun He, Zhuoer Wang, Yin Zhang, Ruihong Huang, James Caverlee:
PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge. EMNLP (1) 2020: 7572-7582 - [c123]Yin Zhang, Ziwei Zhu, Yun He, James Caverlee:
Content-Collaborative Disentanglement Representation Learning for Enhanced Recommendation. RecSys 2020: 43-52 - [c122]Ziwei Zhu, Yun He, Yin Zhang, James Caverlee:
Unbiased Implicit Recommendation and Propensity Estimation via Combinational Joint Learning. RecSys 2020: 551-556 - [c121]Ziwei Zhu, Jianling Wang, James Caverlee:
Measuring and Mitigating Item Under-Recommendation Bias in Personalized Ranking Systems. SIGIR 2020: 449-458 - [c120]Parisa Kaghazgaran, Jianling Wang, Ruihong Huang, James Caverlee:
ADORE: Aspect Dependent Online REview Labeling for Review Generation. SIGIR 2020: 1021-1030 - [c119]Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu, James Caverlee:
Next-item Recommendation with Sequential Hypergraphs. SIGIR 2020: 1101-1110 - [c118]Ziwei Zhu, Shahin Sefati, Parsa Saadatpanah, James Caverlee:
Recommendation for New Users and New Items via Randomized Training and Mixture-of-Experts Transformation. SIGIR 2020: 1121-1130 - [c117]Yun He, Yin Zhang, Weiwen Liu, James Caverlee:
Consistency-Aware Recommendation for User-Generated Item List Continuation. WSDM 2020: 250-258 - [c116]Jianling Wang, Ziwei Zhu, James Caverlee:
User Recommendation in Content Curation Platforms. WSDM 2020: 627-635 - [c115]Jianling Wang, Kaize Ding, Ziwei Zhu, Yin Zhang, James Caverlee:
Key Opinion Leaders in Recommendation Systems: Opinion Elicitation and Diffusion. WSDM 2020: 636-644 - [c114]Jianling Wang, Raphael Louca, Diane Hu, Caitlin Cellier, James Caverlee, Liangjie Hong:
Time to Shop for Valentine's Day: Shopping Occasions and Sequential Recommendation in E-commerce. WSDM 2020: 645-653 - [c113]Xing Zhao, Ziwei Zhu, Yin Zhang, James Caverlee:
Improving the Estimation of Tail Ratings in Recommender System with Multi-Latent Representations. WSDM 2020: 762-770 - [c112]Xing Zhao, Ziwei Zhu, Majid Alfifi, James Caverlee:
Addressing the Target Customer Distortion Problem in Recommender Systems. WWW 2020: 2969-2975 - [c111]Yin Zhang, Yun He, Jianling Wang, James Caverlee:
Adaptive Hierarchical Translation-based Sequential Recommendation. WWW 2020: 2984-2990 - [e5]James Caverlee, Xia (Ben) Hu, Mounia Lalmas, Wei Wang:
WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020. ACM 2020, ISBN 978-1-4503-6822-3 [contents] - [i10]Habeeb Hooshmand, James Caverlee:
Understanding Car-Speak: Replacing Humans in Dealerships. CoRR abs/2002.02070 (2020) - [i9]Yun He, Zhuoer Wang, Yin Zhang, Ruihong Huang, James Caverlee:
PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge. CoRR abs/2010.03725 (2020) - [i8]Yun He, Ziwei Zhu, Yin Zhang, Qin Chen, James Caverlee:
Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition. CoRR abs/2010.03746 (2020)
2010 – 2019
- 2019
- [j22]Qingquan Song, Hancheng Ge, James Caverlee, Xia Hu:
Tensor Completion Algorithms in Big Data Analytics. ACM Trans. Knowl. Discov. Data 13(1): 6:1-6:48 (2019) - [c110]Parisa Kaghazgaran, Majid Alfifi, James Caverlee:
Wide-Ranging Review Manipulation Attacks: Model, Empirical Study, and Countermeasures. CIKM 2019: 981-990 - [c109]Yun He, Jianling Wang, Wei Niu, James Caverlee:
A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists. CIKM 2019: 1481-1490 - [c108]Yin Zhang, James Caverlee:
Instagrammers, Fashionistas, and Me: Recurrent Fashion Recommendation with Implicit Visual Influence. CIKM 2019: 1583-1592 - [c107]Majid Alfifi, Parisa Kaghazgaran, James Caverlee, Fred Morstatter:
A Large-Scale Study of ISIS Social Media Strategy: Community Size, Collective Influence, and Behavioral Impact. ICWSM 2019: 58-67 - [c106]Parisa Kaghazgaran, Majid Alfifi, James Caverlee:
TOmCAT: Target-Oriented Crowd Review Attacks and Countermeasures. ICWSM 2019: 302-312 - [c105]Yin Zhang, Ninghao Liu, Shuiwang Ji, James Caverlee, Xia Hu:
An Interpretable Neural Model with Interactive Stepwise Influence. PAKDD (3) 2019: 528-540 - [c104]Jianling Wang, James Caverlee:
Recurrent Recommendation with Local Coherence. WSDM 2019: 564-572 - [c103]Ziwei Zhu, Jianling Wang, James Caverlee:
Improving Top-K Recommendation via JointCollaborative Autoencoders. WWW 2019: 3483-3482 - [i7]Yun He, Haochen Chen, Ziwei Zhu, James Caverlee:
Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation. CoRR abs/1901.00597 (2019) - [i6]Yun He, Jianling Wang, Wei Niu, James Caverlee:
A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists. CoRR abs/1912.13023 (2019) - [i5]Yun He, Yin Zhang, Weiwen Liu, James Caverlee:
Consistency-Aware Recommendation for User-Generated ItemList Continuation. CoRR abs/1912.13031 (2019) - 2018
- [j21]Benjamin A. Knott, Jonathan Gratch, Angelo Cangelosi, James Caverlee:
ACM Transactions on Interactive Intelligent Systems (TiiS) Special Issue on Trust and Influence in Intelligent Human-Machine Interaction. ACM Trans. Interact. Intell. Syst. 8(4): 25:1-25:3 (2018) - [j20]Victor Bahl, Barbara Carminati, James Caverlee, Ing-Ray Chen, Wynne Hsu, Toru Ishida, Valérie Issarny, Surya Nepal, Indrakshi Ray, Kui Ren, Shamik Sural, Mei-Ling Shyu:
Editorial. IEEE Trans. Serv. Comput. 11(1): 1-4 (2018) - [c102]Wei Niu, James Caverlee, Haokai Lu:
Location-Sensitive User Profiling Using Crowdsourced Labels. AAAI 2018: 386-393 - [c101]Chenxi Qiu, Anna Cinzia Squicciarini, Dev Rishi Khare, Barbara Carminati, James Caverlee:
CrowdEval: A Cost-Efficient Strategy to Evaluate Crowdsourced Worker's Reliability. AAMAS 2018: 1486-1494 - [c100]Ziwei Zhu, Xia Hu, James Caverlee:
Fairness-Aware Tensor-Based Recommendation. CIKM 2018: 1153-1162 - [c99]Cheng Cao, Zhengzhang Chen, James Caverlee, Lu-An Tang, Chen Luo, Zhichun Li:
Behavior-based Community Detection: Application to Host Assessment In Enterprise Information Networks. CIKM 2018: 1977-1985 - [c98]Hancheng Ge, Kai Zhang, Majid Alfifi, Xia Hu, James Caverlee:
DisTenC: A Distributed Algorithm for Scalable Tensor Completion on Spark. ICDE 2018: 137-148 - [c97]