Moritz Hardt

Orcid: 0009-0000-7694-3038

Affiliations:
  • Max Planck Institute for Intelligent Systems, Germany
  • University of California, Berkeley, CA, USA (former)


According to our database1, Moritz Hardt authored at least 106 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of two.
  • Erdős number3 of three.

Timeline

Legend:

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Bibliography

2024
Lawma: The Power of Specialization for Legal Tasks.
CoRR, 2024

Evaluating language models as risk scores.
CoRR, 2024

Limits to Predicting Online Speech Using Large Language Models.
CoRR, 2024

Training on the Test Task Confounds Evaluation and Emergence.
CoRR, 2024

An engine not a camera: Measuring performative power of online search.
CoRR, 2024

ImageNot: A contrast with ImageNet preserves model rankings.
CoRR, 2024

Predictors from causal features do not generalize better to new domains.
CoRR, 2024

Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Causal Inference from Competing Treatments.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Allocation Requires Prediction Only if Inequality Is Low.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Don't Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Causal Inference out of Control: Estimating Performativity without Treatment Randomization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Test-Time Training on Nearest Neighbors for Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Unprocessing Seven Years of Algorithmic Fairness.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Performative Prediction: Past and Future.
CoRR, 2023

What Makes ImageNet Look Unlike LAION.
CoRR, 2023

Questioning the Survey Responses of Large Language Models.
CoRR, 2023

Difficult Lessons on Social Prediction from Wisconsin Public Schools.
CoRR, 2023

Causal Inference out of Control: Estimating the Steerability of Consumption.
CoRR, 2023

Algorithmic Collective Action in Machine Learning.
Proceedings of the International Conference on Machine Learning, 2023

A Theory of Dynamic Benchmarks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Is Your Model Predicting the Past?
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

2022
Algorithmic amplification of politics on Twitter.
Proc. Natl. Acad. Sci. USA, 2022

County-level Algorithmic Audit of Racial Bias in Twitter's Home Timeline.
CoRR, 2022

Backward baselines: Is your model predicting the past?
CoRR, 2022

Performative Power.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Causal Inference Struggles with Agency on Online Platforms.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Adversarial Scrutiny of Evidentiary Statistical Software.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
Patterns, predictions, and actions: A story about machine learning.
CoRR, 2021

Understanding deep learning (still) requires rethinking generalization.
Commun. ACM, 2021

Retiring Adult: New Datasets for Fair Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Alternative Microfoundations for Strategic Classification.
Proceedings of the 38th International Conference on Machine Learning, 2021

From Optimizing Engagement to Measuring Value.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020
Revisiting Design Choices in Proximal Policy Optimization.
CoRR, 2020

Stochastic Optimization for Performative Prediction.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A System for Massively Parallel Hyperparameter Tuning.
Proceedings of the Third Conference on Machine Learning and Systems, 2020

Test-Time Training with Self-Supervision for Generalization under Distribution Shifts.
Proceedings of the 37th International Conference on Machine Learning, 2020

Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Performative Prediction.
Proceedings of the 37th International Conference on Machine Learning, 2020

Strategic Classification is Causal Modeling in Disguise.
Proceedings of the 37th International Conference on Machine Learning, 2020

Identity Crisis: Memorization and Generalization Under Extreme Overparameterization.
Proceedings of the 8th International Conference on Learning Representations, 2020

Explaining an increase in predicted risk for clinical alerts.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Linear Dynamics: Clustering without identification.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Generalization in Overparameterized Models.
Proceedings of the Beyond the Worst-Case Analysis of Algorithms, 2020

2019
Strategic Adaptation to Classifiers: A Causal Perspective.
CoRR, 2019

Test-Time Training for Out-of-Distribution Generalization.
CoRR, 2019

Identity Crisis: Memorization and Generalization under Extreme Overparameterization.
CoRR, 2019

A Meta-Analysis of Overfitting in Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Model Similarity Mitigates Test Set Overuse.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Natural Analysts in Adaptive Data Analysis.
Proceedings of the 36th International Conference on Machine Learning, 2019

The Implicit Fairness Criterion of Unconstrained Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

The advantages of multiple classes for reducing overfitting from test set reuse.
Proceedings of the 36th International Conference on Machine Learning, 2019

Stable Recurrent Models.
Proceedings of the 7th International Conference on Learning Representations, 2019

Model Reconstruction from Model Explanations.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

The Social Cost of Strategic Classification.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Open Problem: How fast can a multiclass test set be overfit?
Proceedings of the Conference on Learning Theory, 2019

2018
Gradient Descent Learns Linear Dynamical Systems.
J. Mach. Learn. Res., 2018

Massively Parallel Hyperparameter Tuning.
CoRR, 2018

Group calibration is a byproduct of unconstrained learning.
CoRR, 2018

When Recurrent Models Don't Need To Be Recurrent.
CoRR, 2018

Sanity Checks for Saliency Maps.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Delayed Impact of Fair Machine Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Climbing a shaky ladder: Better adaptive risk estimation.
CoRR, 2017

Guilt-free data reuse.
Commun. ACM, 2017

Avoiding Discrimination through Causal Reasoning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Understanding deep learning requires rethinking generalization.
Proceedings of the 5th International Conference on Learning Representations, 2017

Identity Matters in Deep Learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Private Spectral Analysis.
Encyclopedia of Algorithms, 2016

Special Section on the Fifty-Fourth Annual IEEE Symposium on Foundations of Computer Science (FOCS 2013).
SIAM J. Comput., 2016

Equality of Opportunity in Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Strategic Classification.
Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science, 2016

Train faster, generalize better: Stability of stochastic gradient descent.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Tight Bounds for Learning a Mixture of Two Gaussians.
Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, 2015

Preserving Statistical Validity in Adaptive Data Analysis.
Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, 2015

Generalization in Adaptive Data Analysis and Holdout Reuse.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Differentially Private Learning of Structured Discrete Distributions.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

The Ladder: A Reliable Leaderboard for Machine Learning Competitions.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Sharp bounds for learning a mixture of two gaussians.
CoRR, 2014

The Noisy Power Method: A Meta Algorithm with Applications.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Preventing False Discovery in Interactive Data Analysis Is Hard.
Proceedings of the 55th IEEE Annual Symposium on Foundations of Computer Science, 2014

Understanding Alternating Minimization for Matrix Completion.
Proceedings of the 55th IEEE Annual Symposium on Foundations of Computer Science, 2014

Fast matrix completion without the condition number.
Proceedings of The 27th Conference on Learning Theory, 2014

Computational Limits for Matrix Completion.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Privately Releasing Conjunctions and the Statistical Query Barrier.
SIAM J. Comput., 2013

On the Provable Convergence of Alternating Minimization for Matrix Completion.
CoRR, 2013

How robust are linear sketches to adaptive inputs?
Proceedings of the Symposium on Theory of Computing Conference, 2013

Beyond worst-case analysis in private singular vector computation.
Proceedings of the Symposium on Theory of Computing Conference, 2013

Multiple Kernel Completion and its application to cardiac disease discrimination.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

Algorithms and Hardness for Robust Subspace Recovery.
Proceedings of the COLT 2013, 2013

Robust subspace iteration and privacy-preserving spectral analysis.
Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012
Can We Reconcile Robustness and Efficiency in Unsupervised Learning?
CoRR, 2012

Beating randomized response on incoherent matrices.
Proceedings of the 44th Symposium on Theory of Computing Conference, 2012

Private data release via learning thresholds.
Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms, 2012

A Simple and Practical Algorithm for Differentially Private Data Release.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Graph densification.
Proceedings of the Innovations in Theoretical Computer Science 2012, 2012

Fairness through awareness.
Proceedings of the Innovations in Theoretical Computer Science 2012, 2012

2011
A Study of Privacy and Fairness in Sensitive Data Analysis
PhD thesis, 2011

Subsampling Mathematical Relaxations and Average-case Complexity.
Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete Algorithms, 2011

2010
On the geometry of differential privacy.
Proceedings of the 42nd ACM Symposium on Theory of Computing, 2010

A Multiplicative Weights Mechanism for Privacy-Preserving Data Analysis.
Proceedings of the 51th Annual IEEE Symposium on Foundations of Computer Science, 2010

2009
Deterministically testing sparse polynomial identities of unbounded degree.
Inf. Process. Lett., 2009

Subsampling Semidefinite Programs and Max-Cut on the Sphere.
Electron. Colloquium Comput. Complex., 2009

The uniform hardcore lemma via approximate Bregman projections.
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009

2008
Asymptotically Optimal Hitting Sets Against Polynomials.
Proceedings of the Automata, Languages and Programming, 35th International Colloquium, 2008

Rounding Parallel Repetitions of Unique Games.
Proceedings of the 49th Annual IEEE Symposium on Foundations of Computer Science, 2008

2006
Higher-Order Syntax and Saturation Algorithms for Hybrid Logic.
Proceedings of the International Workshop on Hybrid Logic, 2006


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