| Near optimal behavior via approximate state abstraction D Abel, D Hershkowitz, M Littman International Conference on Machine Learning, 2915-2923, 2016 | 103 | 2016 |
| Goal-based action priors D Abel, D Hershkowitz, G Barth-Maron, S Brawner, K O'Farrell, ... Proceedings of the International Conference on Automated Planning and …, 2015 | 44 | 2015 |
| Round-and message-optimal distributed graph algorithms B Haeupler, DE Hershkowitz, D Wajc Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing …, 2018 | 37* | 2018 |
| Broadcasting in Noisy Radio Networks K Censor-Hillel, B Haeupler, DE Hershkowitz, G Zuzic arXiv preprint arXiv:1705.07369, 2017 | 12 | 2017 |
| Finding options that minimize planning time Y Jinnai, D Abel, D Hershkowitz, M Littman, G Konidaris International Conference on Machine Learning, 3120-3129, 2019 | 10 | 2019 |
| Erasure correction for noisy radio networks K Censor-Hillel, B Haeupler, DE Hershkowitz, G Zuzic arXiv preprint arXiv:1805.04165, 2018 | 9 | 2018 |
| District-fair participatory budgeting DE Hershkowitz, A Kahng, D Peters, AD Procaccia arXiv preprint arXiv:2102.06115, 2021 | 5 | 2021 |
| Tree embeddings for hop-constrained network design B Haeupler, DE Hershkowitz, G Zuzic Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021 | 4 | 2021 |
| Learning propositional functions for planning and reinforcement learning DE Hershkowitz, J MacGlashan, S Tellex 2015 AAAI Fall Symposium Series, 2015 | 4 | 2015 |
| Near-optimal schedules for simultaneous multicasts B Haeupler, DE Hershkowitz, D Wajc arXiv preprint arXiv:2001.00072, 2019 | 3 | 2019 |
| Deterministic Tree Embeddings with Copies for Algorithms Against Adaptive Adversaries B Haeupler, DE Hershkowitz, G Zuzic arXiv preprint arXiv:2102.05168, 2021 | 1 | 2021 |
| Reverse greedy is bad for k-center DE Hershkowitz, G Kehne Information Processing Letters 158, 105941, 2020 | 1 | 2020 |
| Prepare for the expected worst: Algorithms for reconfigurable resources under uncertainty DE Hershkowitz, R Ravi, S Singla arXiv preprint arXiv:1811.11635, 2018 | 1 | 2018 |
| Fast Algorithms for Hop-Constrained Flows and Moving Cuts B Haeupler, DE Hershkowitz, T Saranurak arXiv preprint arXiv:2111.01422, 2021 | | 2021 |
| Bad-Policy Density: A Measure of Reinforcement Learning Hardness D Abel, C Allen, D Arumugam, DE Hershkowitz, ML Littman, LLS Wong arXiv preprint arXiv:2110.03424, 2021 | | 2021 |
| Steiner Point Removal in Series-Parallel Graphs DE Hershkowitz, J Li arXiv preprint arXiv:2104.00750, 2021 | | 2021 |
| An optimal rounding for half-integral weighted minimum strongly connected spanning subgraph DE Hershkowitz, G Kehne, R Ravi Information Processing Letters 167, 106067, 2021 | | 2021 |
| Computation-Aware Data Aggregation B Haeupler, DE Hershkowitz, A Kahng, AD Procaccia arXiv preprint arXiv:1806.05701, 2018 | | 2018 |
| Leveraging and Learning Propositional Functions for Large State Spaces in Planning and Reinforcement Learning DE Hershkowitz | | 2015 |
| SKILL DISCOVERY WITH WELL-DEFINED OBJECTIVES Y Jinnai, D Abel, JW Park, DE Hershkowitz, ML Littman, G Konidaris | | |
Bernhard HaeuplerAssociate Professor, CMUVerified email at cs.cmu.edu
