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ORCIDEsther Rolf
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Books and Theses
- 2022
[b1]Esther Rolf:
Incorporating Intent, Impact, and Context for Beneficial Machine Learning. University of California, Berkeley, USA, 2022
Journal Articles
- 2021
- [j1]Esther Rolf
, David Fridovich-Keil, Max Simchowitz, Benjamin Recht, Claire J. Tomlin:
A Successive-Elimination Approach to Adaptive Robotic Source Seeking. IEEE Trans. Robotics 37(1): 34-47 (2021)
Conference and Workshop Papers
- 2025
- [c14]Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm:
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery. AAAI 2025: 4347-4355 - [c13]Rahul Nair, Bhanu Tokas, Gabriel Tseng, Esther Rolf, Hannah Kerner:
Classification Drives Geographic Bias in Street Scene Segmentation. CVPR Workshops 2025: 629-638 - 2024
- [c12]Lucia Gordon, Esther Rolf, Milind Tambe:
Combining Diverse Information for Coordinated Action: Stochastic Bandit Algorithms for Heterogeneous Agents. ECAI 2024: 3284-3291 - [c11]Marc Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia:
Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks. ICLR 2024 - [c10]Esther Rolf, Konstantin Klemmer, Caleb Robinson, Hannah Kerner:
Position: Mission Critical - Satellite Data is a Distinct Modality in Machine Learning. ICML 2024 - [c9]David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White:
Position: Application-Driven Innovation in Machine Learning. ICML 2024 - 2023
- [c8]Emily L. Aiken, Esther Rolf, Joshua Blumenstock:
Fairness and Representation in Satellite-Based Poverty Maps: Evidence of Urban-Rural Disparities and Their Impacts on Downstream Policy. IJCAI 2023: 5888-5896 - 2022
- [c7]Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic:
Resolving label uncertainty with implicit posterior models. UAI 2022: 1707-1717 - 2021
- [c6]Esther Rolf, Theodora T. Worledge, Benjamin Recht, Michael I. Jordan:
Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data. ICML 2021: 9040-9051 - 2020
- [c5]Esther Rolf, Michael I. Jordan, Benjamin Recht:
Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information. AISTATS 2020: 1759-1769 - [c4]Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock:
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning. ICML 2020: 8158-8168 - 2019
- [c3]Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt:
Delayed Impact of Fair Machine Learning. IJCAI 2019: 6196-6200 - 2018
- [c2]Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt:
Delayed Impact of Fair Machine Learning. ICML 2018: 3156-3164 - 2013
- [c1]Esther Rolf, Matt Whitlock, Byung-Cheol Min, Eric T. Matson:
Enhancing Wi-Fi Signal Strength of a Dynamic Heterogeneous System Using a Mobile Robot Provider. RiTA 2013: 927-937
Informal and Other Publications
- 2025
- [i23]Mirali Purohit, Gedeon Muhawenayo, Esther Rolf, Hannah Kerner:
How Does the Spatial Distribution of Pre-training Data Affect Geospatial Foundation Models? CoRR abs/2501.12535 (2025) - [i22]Arjun Rao, Esther Rolf:
Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery. CoRR abs/2507.13385 (2025) - [i21]Livia Betti, Farooq Sanni, Gnouyaro Sogoyou, Togbe Agbagla, Cullen Molitor, Tamma Carleton, Esther Rolf:
Mapping on a Budget: Optimizing Spatial Data Collection for ML. CoRR abs/2509.03749 (2025) - 2024
- [i20]Esther Rolf, Konstantin Klemmer, Caleb Robinson, Hannah Kerner:
Mission Critical - Satellite Data is a Distinct Modality in Machine Learning. CoRR abs/2402.01444 (2024) - [i19]David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White:
Application-Driven Innovation in Machine Learning. CoRR abs/2403.17381 (2024) - [i18]Lucia Gordon, Esther Rolf, Milind Tambe:
Combining Diverse Information for Coordinated Action: Stochastic Bandit Algorithms for Heterogeneous Agents. CoRR abs/2408.03405 (2024) - [i17]Esther Rolf, Lucia Gordon, Milind Tambe, Andrew Davies:
Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas. CoRR abs/2411.14354 (2024) - [i16]Rahul Nair, Gabriel Tseng, Esther Rolf, Bhanu Tokas, Hannah Kerner:
Classification Drives Geographic Bias in Street Scene Segmentation. CoRR abs/2412.11061 (2024) - 2023
- [i15]Esther Rolf:
Evaluation Challenges for Geospatial ML. CoRR abs/2303.18087 (2023) - [i14]Emily L. Aiken, Esther Rolf, Joshua Blumenstock:
Fairness and representation in satellite-based poverty maps: Evidence of urban-rural disparities and their impacts on downstream policy. CoRR abs/2305.01783 (2023) - [i13]Lily Xu, Esther Rolf, Sara Beery, Joseph R. Bennett, Tanya Y. Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa S. Chapman, Anthony Corso, Andrew Davies, Nikhil Garg, Angela Gaylard, Robert Heilmayr, Hannah Kerner, Konstantin Klemmer, Vipin Kumar, Lester Mackey, Claire Monteleoni, Paul Moorcroft, Jonathan Palmer, Andrew Perrault, David Thau, Milind Tambe:
Reflections from the Workshop on AI-Assisted Decision Making for Conservation. CoRR abs/2307.08774 (2023) - [i12]Marc Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia:
Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks. CoRR abs/2310.06743 (2023) - [i11]Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm:
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery. CoRR abs/2311.17179 (2023) - 2022
- [i10]Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic:
Resolving label uncertainty with implicit posterior models. CoRR abs/2202.14000 (2022) - [i9]Esther Rolf, Ben Packer, Alex Beutel, Fernando Diaz:
Striving for data-model efficiency: Identifying data externalities on group performance. CoRR abs/2211.06348 (2022) - [i8]Satej Soman, Emily L. Aiken, Esther Rolf, Joshua Blumenstock:
Can Strategic Data Collection Improve the Performance of Poverty Prediction Models? CoRR abs/2211.08735 (2022) - 2021
- [i7]Esther Rolf, Theodora Worledge, Benjamin Recht, Michael I. Jordan:
Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data. CoRR abs/2103.03399 (2021) - 2020
- [i6]Esther Rolf, Michael I. Jordan, Benjamin Recht:
Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information. CoRR abs/2003.05955 (2020) - [i5]Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock:
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning. CoRR abs/2003.06740 (2020) - [i4]Esther Rolf, Jonathan Proctor, Tamma Carleton, Ian Bolliger, Vaishaal Shankar, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang:
A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery. CoRR abs/2010.08168 (2020) - 2018
- [i3]Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt:
Delayed Impact of Fair Machine Learning. CoRR abs/1803.04383 (2018) - [i2]Esther Rolf, David Fridovich-Keil, Max Simchowitz, Benjamin Recht, Claire J. Tomlin:
A Successive-Elimination Approach to Adaptive Robotic Sensing. CoRR abs/1809.10611 (2018) - 2017
- [i1]Ian Bolliger, Tamma Carleton, Solomon Hsiang, Jonathan Kadish, Jonathan Proctor, Benjamin Recht, Esther Rolf, Vaishaal Shankar:
Ground Control to Major Tom: the importance of field surveys in remotely sensed data analysis. CoRR abs/1710.09342 (2017)
Coauthor Index
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