Alex Beutel

123 papers A* 27A 12B 1C 3Journal 62Unranked 16
YearRankTypeTitle / Venue / Authors
2026 J jnl
IH-Challenge: A Training Dataset to Improve Instruction Hierarchy on Frontier LLMs.
CoRR
Chuan Guo, Juan Felipe Ceron Uribe, Sicheng Zhu, Christopher A. Choquette-Choo, Stephanie Lin, Nikhil Kandpal, Milad Nasr, Rai, Sam Toyer, Miles Wang, Yaodong Yu, Alex Beutel, Kai Xiao
2025 A* conf
First-Person Fairness in Chatbots.
ICLR
Tyna Eloundou, Alex Beutel, David G. Robinson, Keren Gu, Anna-Luisa Brakman, Pamela Mishkin, Meghan Shah, Johannes Heidecke, Lilian Weng, Adam Tauman Kalai
2025 J jnl
From Hard Refusals to Safe-Completions: Toward Output-Centric Safety Training.
CoRR
Yuan Yuan, Tina Sriskandarajah, Anna-Luisa Brakman, Alec Helyar, Alex Beutel, Andrea Vallone, Saachi Jain
2025 J jnl
HealthBench: Evaluating Large Language Models Towards Improved Human Health.
CoRR
Rahul K. Arora, Jason Wei, Rebecca Soskin Hicks, Preston Bowman, Joaquin Quiñonero Candela, Foivos Tsimpourlas, Michael Sharman, Meghan Shah, Andrea Vallone, Alex Beutel, Johannes Heidecke, Karan Singhal
2024 J jnl
Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks.
Trans. Mach. Learn. Res.
Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel
2024 A* conf
Controlled Decoding from Language Models.
ICML
Sidharth Mudgal, Jong Lee, Harish Ganapathy, Yaguang Li, Tao Wang, Yanping Huang, Zhifeng Chen, Heng-Tze Cheng, Michael Collins, Trevor Strohman, Jilin Chen, Alex Beutel, Ahmad Beirami
2024 J jnl
Deliberative Alignment: Reasoning Enables Safer Language Models.
CoRR
Melody Y. Guan, Manas Joglekar, Eric Wallace, Saachi Jain, Boaz Barak, Alec Helyar, Rachel Dias, Andrea Vallone, Hongyu Ren, Jason Wei, Hyung Won Chung, Sam Toyer, Johannes Heidecke, Alex Beutel, Amelia Glaese
2024 J jnl
Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning.
CoRR
Alex Beutel, Kai Xiao, Johannes Heidecke, Lilian Weng
2024 J jnl
First-Person Fairness in Chatbots.
CoRR
Tyna Eloundou, Alex Beutel, David G. Robinson, Keren Gu-Lemberg, Anna-Luisa Brakman, Pamela Mishkin, Meghan Shah, Johannes Heidecke, Lilian Weng, Adam Tauman Kalai
2024 — conf
Generalized People Diversity: Learning a Human Perception-Aligned Diversity Representation for People Images.
FAccT
Hansa Srinivasan, Candice Schumann, Aradhana Sinha, David Madras, Gbolahan Oluwafemi Olanubi, Alex Beutel, Susanna Ricco, Jilin Chen
2024 J jnl
Generalized People Diversity: Learning a Human Perception-Aligned Diversity Representation for People Images.
CoRR
Hansa Srinivasan, Candice Schumann, Aradhana Sinha, David Madras, Gbolahan Oluwafemi Olanubi, Alex Beutel, Susanna Ricco, Jilin Chen
2024 J jnl
Multi-Group Fairness Evaluation via Conditional Value-at-Risk Testing.
IEEE J. Sel. Areas Inf. Theory
Lucas Monteiro Paes, Ananda Theertha Suresh, Alex Beutel, Flávio P. Calmon, Ahmad Beirami
2024 A* conf
Rule Based Rewards for Language Model Safety.
NeurIPS
Tong Mu, Alec Helyar, Johannes Heidecke, Joshua Achiam, Andrea Vallone, Ian Kivlichan, Molly Lin, Alex Beutel, John Schulman, Lilian Weng
2024 J jnl
Rule Based Rewards for Language Model Safety.
CoRR
Tong Mu, Alec Helyar, Johannes Heidecke, Joshua Achiam, Andrea Vallone, Ian Kivlichan, Molly Lin, Alex Beutel, John Schulman, Lilian Weng
2024 J jnl
The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions.
CoRR
Eric Wallace, Kai Xiao, Reimar Leike, Lilian Weng, Johannes Heidecke, Alex Beutel
2023 J jnl
Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks.
CoRR
Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel
2023 J jnl
Controlled Decoding from Language Models.
CoRR
Sidharth Mudgal, Jong Lee, Harish Ganapathy, Yaguang Li, Tao Wang, Yanping Huang, Zhifeng Chen, Heng-Tze Cheng, Michael Collins, Trevor Strohman, Jilin Chen, Alex Beutel, Ahmad Beirami
2023 A* conf
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data.
NeurIPS
Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin
2023 J jnl
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data.
CoRR
Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin
2023 J jnl
Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals.
CoRR
Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel
2023 — conf
Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation.
EMNLP (Findings)
Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed H. Chi, Jilin Chen, Alex Beutel
2023 A* conf
Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting.
EMNLP
Preethi Lahoti, Nicholas Blumm, Xiao Ma, Raghavendra Kotikalapudi, Sahitya Potluri, Qijun Tan, Hansa Srinivasan, Ben Packer, Ahmad Beirami, Alex Beutel, Jilin Chen
2023 J jnl
Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting.
CoRR
Preethi Lahoti, Nicholas Blumm, Xiao Ma, Raghavendra Kotikalapudi, Sahitya Potluri, Qijun Tan, Hansa Srinivasan, Ben Packer, Ahmad Beirami, Alex Beutel, Jilin Chen
2023 J jnl
Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning.
CoRR
Ananth Balashankar, Xiao Ma, Aradhana Sinha, Ahmad Beirami, Yao Qin, Jilin Chen, Alex Beutel
2023 A conf
Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenders.
RecSys
Yueqi Wang, Yoni Halpern, Shuo Chang, Jingchen Feng, Elaine Ya Le, Longfei Li, Xujian Liang, Min-Cheng Huang, Shane Li, Alex Beutel, Yaping Zhang, Shuchao Bi
2023 J jnl
Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenders.
CoRR
Yueqi Wang, Yoni Halpern, Shuo Chang, Jingchen Feng, Elaine Ya Le, Longfei Li, Xujian Liang, Min-Cheng Huang, Shane Li, Alex Beutel, Yaping Zhang, Shuchao Bi
2023 J jnl
Let's Do a Thought Experiment: Using Counterfactuals to Improve Moral Reasoning.
CoRR
Xiao Ma, Swaroop Mishra, Ahmad Beirami, Alex Beutel, Jilin Chen
2023 J jnl
Multi-Group Fairness Evaluation via Conditional Value-at-Risk Testing.
CoRR
Lucas Monteiro Paes, Ananda Theertha Suresh, Alex Beutel, Flávio P. Calmon, Ahmad Beirami
2023 J jnl
Towards A Scalable Solution for Improving Multi-Group Fairness in Compositional Classification.
CoRR
James Atwood, Tina Tian, Ben Packer, Meghana Deodhar, Jilin Chen, Alex Beutel, Flavien Prost, Ahmad Beirami
2023 J jnl
Towards Robust Prompts on Vision-Language Models.
CoRR
Jindong Gu, Ahmad Beirami, Xuezhi Wang, Alex Beutel, Philip H. S. Torr, Yao Qin
2023 — conf
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel.
SaTML
Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel
2023 J jnl
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel.
CoRR
Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel
2022 J jnl
A Human-ML Collaboration Framework for Improving Video Content Reviews.
CoRR
Meghana Deodhar, Xiao Ma, Yixin Cai, Alex Koes, Alex Beutel, Jilin Chen
2022 — conf
A human-ML collaboration framework for improving video content reviews.
CIKM Workshops
Meghana Deodhar, Xiao Ma, Yixin Cai, Alex Koes, Alex Beutel, Jilin Chen
2022 J jnl
Flexible text generation for counterfactual fairness probing.
CoRR
Zee Fryer, Vera Axelrod, Ben Packer, Alex Beutel, Jilin Chen, Kellie Webster
2022 J jnl
Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations.
CoRR
Flavien Prost, Ben Packer, Jilin Chen, Li Wei, Pierre Kremp, Nick Blumm, Susan Wang, Tulsee Doshi, Tonia Osadebe, Lukasz Heldt, Ed H. Chi, Alex Beutel
2022 J jnl
Striving for data-model efficiency: Identifying data externalities on group performance.
CoRR
Esther Rolf, Ben Packer, Alex Beutel, Fernando Diaz
2022 J jnl
Underspecification Presents Challenges for Credibility in Modern Machine Learning.
J. Mach. Learn. Res.
Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
2022 A* conf
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation.
NeurIPS
Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang
2021 — conf
Can We Improve Model Robustness through Secondary Attribute Counterfactuals?
EMNLP (1)
Ananth Balashankar, Xuezhi Wang, Ben Packer, Nithum Thain, Ed H. Chi, Alex Beutel
2021 A conf
Enhancing Neural Recommender Models through Domain-Specific Concordance.
WSDM
Ananth Balashankar, Alex Beutel, Lakshminarayanan Subramanian
2021 — conf
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information.
FAccT
Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang
2021 J jnl
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information.
CoRR
Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang
2021 A* conf
Improving Calibration through the Relationship with Adversarial Robustness.
NeurIPS
Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi
2021 C conf
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective.
AIES
Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
2021 J jnl
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective.
CoRR
Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
2021 J jnl
Measuring Recommender System Effects with Simulated Users.
CoRR
Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
2021 A conf
Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems.
WSDM
Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
2021 A* conf
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities.
WWW
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen
2021 J jnl
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities.
CoRR
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen
2021 A* conf
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning.
KDD
Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
2021 J jnl
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning.
CoRR
Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
2021 J jnl
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation.
CoRR
Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang
2020 — conf
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation.
EMNLP (1)
Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi
2020 J jnl
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation.
CoRR
Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi
2020 A* conf
Deep Reinforcement Learning for Information Retrieval: Fundamentals and Advances.
SIGIR
Weinan Zhang, Xiangyu Zhao, Li Zhao, Dawei Yin, Grace Hui Yang, Alex Beutel
2020 A* conf
Fairness without Demographics through Adversarially Reweighted Learning.
NeurIPS
Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi
2020 J jnl
Fairness without Demographics through Adversarially Reweighted Learning.
CoRR
Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi
2020 J jnl
Improving Uncertainty Estimates through the Relationship with Adversarial Robustness.
CoRR
Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi
2020 J jnl
Learned Indexes for a Google-scale Disk-based Database.
CoRR
Hussam Abu-Libdeh, Deniz Altinbüken, Alex Beutel, Ed H. Chi, Lyric Doshi, Tim Kraska, Xiaozhou Li, Andy Ly, Christopher Olston
2020 J jnl
Measuring and Reducing Gendered Correlations in Pre-trained Models.
CoRR
Kellie Webster, Xuezhi Wang, Ian Tenney, Alex Beutel, Emily Pitler, Ellie Pavlick, Jilin Chen, Slav Petrov
2020 J jnl
Underspecification Presents Challenges for Credibility in Modern Machine Learning.
CoRR
Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
2019 C conf
Counterfactual Fairness in Text Classification through Robustness.
AIES
Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed H. Chi, Alex Beutel
2019 J jnl
FACTS-IR: fairness, accountability, confidentiality, transparency, and safety in information retrieval.
SIGIR Forum
Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, Michael D. Ekstrand, Adam Roegiest, Aldo Lipani, Alex Beutel, Ana Lucic, Ana-Andreea Stoica, Anubrata Das, Asia Biega, Bart Voorn, Claudia Hauff, Damiano Spina, David D. Lewis, Douglas W. Oard, Emine Yilmaz, Faegheh Hasibi, Gabriella Kazai, Graham McDonald, Hinda Haned, Iadh Ounis, Ilse van der Linden, Joris Baan, Kamuela N. Lau, Krisztian Balog, Mahmoud F. Sayed, Maria Panteli, Mark Sanderson, Matthew Lease, Preethi Lahoti, Toshihiro Kamishima
2019 A* conf
Fairness in Recommendation Ranking through Pairwise Comparisons.
KDD
Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow
2019 J jnl
Fairness in Recommendation Ranking through Pairwise Comparisons.
CoRR
Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow
2019 J jnl
Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems.
CoRR
Xuezhi Wang, Nithum Thain, Anu Sinha, Ed H. Chi, Jilin Chen, Alex Beutel
2019 C conf
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements.
AIES
Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathan Bischof, Ed H. Chi
2019 J jnl
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements.
CoRR
Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathan Bischof, Ed H. Chi
2019 A conf
SageDB: A Learned Database System.
CIDR
Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi, Ani Kristo, Guillaume Leclerc, Samuel Madden, Hongzi Mao, Vikram Nathan
2019 A conf
Top-K Off-Policy Correction for a REINFORCE Recommender System.
WSDM
Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi
2019 J jnl
Toward a better trade-off between performance and fairness with kernel-based distribution matching.
CoRR
Flavien Prost, Hai Qian, Qiuwen Chen, Ed H. Chi, Jilin Chen, Alex Beutel
2019 A* conf
Towards Neural Mixture Recommender for Long Range Dependent User Sequences.
WWW
Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi
2019 J jnl
Towards Neural Mixture Recommender for Long Range Dependent User Sequences.
CoRR
Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi
2019 J jnl
Transfer of Machine Learning Fairness across Domains.
CoRR
Candice Schumann, Xuezhi Wang, Alex Beutel, Jilin Chen, Hai Qian, Ed H. Chi
2018 A conf
Categorical-attributes-based item classification for recommender systems.
RecSys
Qian Zhao, Jilin Chen, Minmin Chen, Sagar Jain, Alex Beutel, Francois Belletti, Ed H. Chi
2018 J jnl
Counterfactual Fairness in Text Classification through Robustness.
CoRR
Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed H. Chi, Alex Beutel
2018 A conf
Factorized Recurrent Neural Architectures for Longer Range Dependence.
AISTATS
Francois Belletti, Alex Beutel, Sagar Jain, Ed Huai-hsin Chi
2018 A conf
Latent Cross: Making Use of Context in Recurrent Recommender Systems.
WSDM
Alex Beutel, Paul Covington, Sagar Jain, Can Xu, Jia Li, Vince Gatto, Ed H. Chi
2018 — ch.
Network Anomaly Detection Using Co-clustering.
Encyclopedia of Social Network Analysis and Mining. 2nd Ed.
Evangelos E. Papalexakis, Alex Beutel, Peter Steenkiste
2018 A* conf
Q&R: A Two-Stage Approach toward Interactive Recommendation.
KDD
Konstantina Christakopoulou, Alex Beutel, Rui Li, Sagar Jain, Ed H. Chi
2018 — conf
The Case for Learned Index Structures.
SIGMOD Conference
Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis
2018 J jnl
Top-K Off-Policy Correction for a REINFORCE Recommender System.
CoRR
Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi
2017 A* conf
Beyond Globally Optimal: Focused Learning for Improved Recommendations.
WWW
Alex Beutel, Ed Huai-hsin Chi, Zhiyuan Cheng, Hubert Pham, John R. Anderson
2017 J jnl
Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations.
CoRR
Alex Beutel, Jilin Chen, Zhe Zhao, Ed H. Chi
2017 J jnl
Graph-Based Fraud Detection in the Face of Camouflage.
ACM Trans. Knowl. Discov. Data
Bryan Hooi, Kijung Shin, Hyun Ah Song, Alex Beutel, Neil Shah, Christos Faloutsos
2017 — conf
Joint Training of Ratings and Reviews with Recurrent Recommender Networks.
ICLR (Workshop)
Chao-Yuan Wu, Amr Ahmed, Alex Beutel, Alexander J. Smola
2017 J jnl
OEC: Open-Ended Classification for Future-Proof Link-Fraud Detection.
CoRR
Neil Shah, Hemank Lamba, Alex Beutel, Christos Faloutsos
2017 A conf
Recurrent Recommender Networks.
WSDM
Chao-Yuan Wu, Amr Ahmed, Alex Beutel, Alexander J. Smola, How Jing
2017 J jnl
The Case for Learned Index Structures.
CoRR
Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis
2017 A* conf
The Many Faces of Link Fraud.
ICDM
Neil Shah, Hemank Lamba, Alex Beutel, Christos Faloutsos
2016 A conf
BIRDNEST: Bayesian Inference for Ratings-Fraud Detection.
SDM
Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos
2016 J jnl
Catching Synchronized Behaviors in Large Networks: A Graph Mining Approach.
ACM Trans. Knowl. Discov. Data
Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang
2016 — conf
EdgeCentric: Anomaly Detection in Edge-Attributed Networks.
ICDM Workshops
Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Günnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos
2016 — conf
Explaining Reviews and Ratings with PACO: Poisson Additive Co-Clustering.
WWW (Companion Volume)
Chao-Yuan Wu, Alex Beutel, Amr Ahmed, Alexander J. Smola
2016 A* conf
FRAUDAR: Bounding Graph Fraud in the Face of Camouflage.
KDD
Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos
2016 J jnl
Inferring lockstep behavior from connectivity pattern in large graphs.
Knowl. Inf. Syst.
Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang
2016 J jnl
Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms.
IEEE Trans. Knowl. Data Eng.
Meng Jiang, Alex Beutel, Peng Cui, Bryan Hooi, Shiqiang Yang, Christos Faloutsos
2016 J jnl
TerraNNI: Natural Neighbor Interpolation on 2D and 3D Grids Using a GPU.
ACM Trans. Spatial Algorithms Syst.
Pankaj K. Agarwal, Alex Beutel, Thomas Mølhave
2015 A* conf
A General Suspiciousness Metric for Dense Blocks in Multimodal Data.
ICDM
Meng Jiang, Alex Beutel, Peng Cui, Bryan Hooi, Shiqiang Yang, Christos Faloutsos
2015 A* conf
ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly.
WWW
Alex Beutel, Amr Ahmed, Alexander J. Smola
2015 J jnl
ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly.
CoRR
Alex Beutel, Amr Ahmed, Alexander J. Smola
2015 J jnl
BIRDNEST: Bayesian Inference for Ratings-Fraud Detection.
CoRR
Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos
2015 J jnl
EdgeCentric: Anomaly Detection in Edge-Attributed Networks.
CoRR
Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Günnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos
2015 J jnl
Explaining reviews and ratings with PACO: Poisson Additive Co-Clustering.
CoRR
Chao-Yuan Wu, Alex Beutel, Amr Ahmed, Alexander J. Smola
2015 A* conf
Fraud Detection through Graph-Based User Behavior Modeling.
CCS
Alex Beutel, Leman Akoglu, Christos Faloutsos
2015 A* conf
Graph-Based User Behavior Modeling: From Prediction to Fraud Detection.
KDD
Alex Beutel, Leman Akoglu, Christos Faloutsos
2015 — conf
ND-Sync: Detecting Synchronized Fraud Activities.
PAKDD (2)
Maria Giatsoglou, Despoina Chatzakou, Neil Shah, Alex Beutel, Christos Faloutsos, Athena Vakali
2014 A* conf
CatchSync: catching synchronized behavior in large directed graphs.
KDD
Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang
2014 A* conf
CoBaFi: collaborative bayesian filtering.
WWW
Alex Beutel, Kenton Murray, Christos Faloutsos, Alexander J. Smola
2014 — conf
Detecting suspicious following behavior in multimillion-node social networks.
WWW (Companion Volume)
Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang
2014 A conf
FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop.
SDM
Alex Beutel, Partha Pratim Talukdar, Abhimanu Kumar, Christos Faloutsos, Evangelos E. Papalexakis, Eric P. Xing
2014 A conf
Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data.
AISTATS
Abhimanu Kumar, Alex Beutel, Qirong Ho, Eric P. Xing
2014 — conf
Inferring Strange Behavior from Connectivity Pattern in Social Networks.
PAKDD (1)
Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang
2014 — ch.
Network Anomaly Detection Using Co-clustering.
Encyclopedia of Social Network Analysis and Mining
Evangelos E. Papalexakis, Alex Beutel, Peter Steenkiste
2014 A* conf
Spotting Suspicious Link Behavior with fBox: An Adversarial Perspective.
ICDM
Neil Shah, Alex Beutel, Brian Gallagher, Christos Faloutsos
2014 J jnl
Spotting Suspicious Link Behavior with fBox: An Adversarial Perspective.
CoRR
Neil Shah, Alex Beutel, Brian Gallagher, Christos Faloutsos
2013 A* conf
CopyCatch: stopping group attacks by spotting lockstep behavior in social networks.
WWW
Alex Beutel, Wanhong Xu, Venkatesan Guruswami, Christopher Palow, Christos Faloutsos
2012 A* conf
Interacting viruses in networks: can both survive?
KDD
Alex Beutel, B. Aditya Prakash, Roni Rosenfeld, Christos Faloutsos
2012 B conf
Network Anomaly Detection Using Co-clustering.
ASONAM
Evangelos E. Papalexakis, Alex Beutel, Peter Steenkiste
2012 A* conf
Winner takes all: competing viruses or ideas on fair-play networks.
WWW
B. Aditya Prakash, Alex Beutel, Roni Rosenfeld, Christos Faloutsos
2011 — conf
TerraNNI: natural neighbor interpolation on a 3D grid using a GPU.
GIS
Alex Beutel, Thomas Mølhave, Pankaj K. Agarwal, Arnold P. Boedihardjo, James A. Shine
2010 — conf
Natural neighbor interpolation based grid DEM construction using a GPU.
GIS
Alex Beutel, Thomas Mølhave, Pankaj K. Agarwal