Alex Beutel

Orcid: 0000-0002-5917-2849

According to our database1, Alex Beutel authored at least 85 papers between 2010 and 2024.

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Bibliography

2024
Generalized People Diversity: Learning a Human Perception-Aligned Diversity Representation for People Images.
CoRR, 2024

2023
Multi-Group Fairness Evaluation via Conditional Value-at-Risk Testing.
CoRR, 2023

Controlled Decoding from Language Models.
CoRR, 2023

Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning.
CoRR, 2023

Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks.
CoRR, 2023

Towards A Scalable Solution for Improving Multi-Group Fairness in Compositional Classification.
CoRR, 2023

Let's Do a Thought Experiment: Using Counterfactuals to Improve Moral Reasoning.
CoRR, 2023

Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals.
CoRR, 2023

Towards Robust Prompts on Vision-Language Models.
CoRR, 2023

What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel.
CoRR, 2023

Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenders.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Effective Robustness against Natural Distribution Shifts for Models with Different Training Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Underspecification Presents Challenges for Credibility in Modern Machine Learning.
J. Mach. Learn. Res., 2022

Striving for data-model efficiency: Identifying data externalities on group performance.
CoRR, 2022

Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations.
CoRR, 2022

Flexible text generation for counterfactual fairness probing.
CoRR, 2022

Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A human-ML collaboration framework for improving video content reviews.
Proceedings of the CIKM 2022 Workshops co-located with 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), 2022

2021
Measuring Recommender System Effects with Simulated Users.
CoRR, 2021

Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Enhancing Neural Recommender Models through Domain-Specific Concordance.
Proceedings of the WSDM '21, 2021

Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems.
Proceedings of the WSDM '21, 2021

Improving Calibration through the Relationship with Adversarial Robustness.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Can We Improve Model Robustness through Secondary Attribute Counterfactuals?
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020
Learned Indexes for a Google-scale Disk-based Database.
CoRR, 2020

Measuring and Reducing Gendered Correlations in Pre-trained Models.
CoRR, 2020

Improving Uncertainty Estimates through the Relationship with Adversarial Robustness.
CoRR, 2020

Deep Reinforcement Learning for Information Retrieval: Fundamentals and Advances.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Fairness without Demographics through Adversarially Reweighted Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
FACTS-IR: fairness, accountability, confidentiality, transparency, and safety in information retrieval.
SIGIR Forum, 2019

Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems.
CoRR, 2019

Toward a better trade-off between performance and fairness with kernel-based distribution matching.
CoRR, 2019

Transfer of Machine Learning Fairness across Domains.
CoRR, 2019

Towards Neural Mixture Recommender for Long Range Dependent User Sequences.
Proceedings of the World Wide Web Conference, 2019

Top-K Off-Policy Correction for a REINFORCE Recommender System.
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Fairness in Recommendation Ranking through Pairwise Comparisons.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

SageDB: A Learned Database System.
Proceedings of the 9th Biennial Conference on Innovative Data Systems Research, 2019

Counterfactual Fairness in Text Classification through Robustness.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018
Network Anomaly Detection Using Co-clustering.
Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Latent Cross: Making Use of Context in Recurrent Recommender Systems.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

The Case for Learned Index Structures.
Proceedings of the 2018 International Conference on Management of Data, 2018

Categorical-attributes-based item classification for recommender systems.
Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Q&R: A Two-Stage Approach toward Interactive Recommendation.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Factorized Recurrent Neural Architectures for Longer Range Dependence.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Graph-Based Fraud Detection in the Face of Camouflage.
ACM Trans. Knowl. Discov. Data, 2017

OEC: Open-Ended Classification for Future-Proof Link-Fraud Detection.
CoRR, 2017

Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations.
CoRR, 2017

Beyond Globally Optimal: Focused Learning for Improved Recommendations.
Proceedings of the 26th International Conference on World Wide Web, 2017

Recurrent Recommender Networks.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Joint Training of Ratings and Reviews with Recurrent Recommender Networks.
Proceedings of the 5th International Conference on Learning Representations, 2017

The Many Faces of Link Fraud.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016
TerraNNI: Natural Neighbor Interpolation on 2D and 3D Grids Using a GPU.
ACM Trans. Spatial Algorithms Syst., 2016

Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms.
IEEE Trans. Knowl. Data Eng., 2016

Catching Synchronized Behaviors in Large Networks: A Graph Mining Approach.
ACM Trans. Knowl. Discov. Data, 2016

Inferring lockstep behavior from connectivity pattern in large graphs.
Knowl. Inf. Syst., 2016

Explaining Reviews and Ratings with PACO: Poisson Additive Co-Clustering.
Proceedings of the 25th International Conference on World Wide Web, 2016

BIRDNEST: Bayesian Inference for Ratings-Fraud Detection.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

FRAUDAR: Bounding Graph Fraud in the Face of Camouflage.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

EdgeCentric: Anomaly Detection in Edge-Attributed Networks.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2015
ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly.
Proceedings of the 24th International Conference on World Wide Web, 2015

ND-Sync: Detecting Synchronized Fraud Activities.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Graph-Based User Behavior Modeling: From Prediction to Fraud Detection.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

A General Suspiciousness Metric for Dense Blocks in Multimodal Data.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Fraud Detection through Graph-Based User Behavior Modeling.
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 2015

2014
Network Anomaly Detection Using Co-clustering.
Encyclopedia of Social Network Analysis and Mining, 2014

Detecting suspicious following behavior in multimillion-node social networks.
Proceedings of the 23rd International World Wide Web Conference, 2014

CoBaFi: collaborative bayesian filtering.
Proceedings of the 23rd International World Wide Web Conference, 2014

FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Inferring Strange Behavior from Connectivity Pattern in Social Networks.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2014

CatchSync: catching synchronized behavior in large directed graphs.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Spotting Suspicious Link Behavior with fBox: An Adversarial Perspective.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
CopyCatch: stopping group attacks by spotting lockstep behavior in social networks.
Proceedings of the 22nd International World Wide Web Conference, 2013

2012
Winner takes all: competing viruses or ideas on fair-play networks.
Proceedings of the 21st World Wide Web Conference 2012, 2012

Interacting viruses in networks: can both survive?
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Network Anomaly Detection Using Co-clustering.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2012

2011
TerraNNI: natural neighbor interpolation on a 3D grid using a GPU.
Proceedings of the 19th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems, 2011

2010
Natural neighbor interpolation based grid DEM construction using a GPU.
Proceedings of the 18th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems, 2010


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