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Andrew Jacobsen
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Journal Articles
- 2021
- [j1]Matthew Schlegel, Andrew Jacobsen, Zaheer Abbas, Andrew Patterson, Adam White, Martha White:
General Value Function Networks. J. Artif. Intell. Res. 70: 497-543 (2021)
Conference and Workshop Papers
- 2023
- [c4]Andrew Jacobsen, Ashok Cutkosky:
Unconstrained Online Learning with Unbounded Losses. ICML 2023: 14590-14630 - 2022
- [c3]Andrew Jacobsen, Ashok Cutkosky
:
Parameter-free Mirror Descent. COLT 2022: 4160-4211 - 2021
- [c2]Matthew McLeod, Chunlok Lo, Matthew Schlegel, Andrew Jacobsen, Raksha Kumaraswamy, Martha White, Adam White:
Continual Auxiliary Task Learning. NeurIPS 2021: 12549-12562 - 2019
- [c1]Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, Martha White:
Meta-Descent for Online, Continual Prediction. AAAI 2019: 3943-3950
Informal and Other Publications
- 2024
- [i7]Andrew Jacobsen, Ashok Cutkosky:
Online Linear Regression in Dynamic Environments via Discounting. CoRR abs/2405.19175 (2024) - [i6]Andrew Jacobsen, Francesco Orabona:
An Equivalence Between Static and Dynamic Regret Minimization. CoRR abs/2406.01577 (2024) - 2023
- [i5]Andrew Jacobsen, Ashok Cutkosky
:
Unconstrained Online Learning with Unbounded Losses. CoRR abs/2306.04923 (2023) - 2022
- [i4]Matthew McLeod, Chunlok Lo, Matthew Schlegel, Andrew Jacobsen, Raksha Kumaraswamy, Martha White, Adam White:
Continual Auxiliary Task Learning. CoRR abs/2202.11133 (2022) - [i3]Andrew Jacobsen, Ashok Cutkosky
:
Parameter-free Mirror Descent. CoRR abs/2203.00444 (2022) - 2021
- [i2]Andrew Jacobsen, Alan Chan:
Parameter-free Gradient Temporal Difference Learning. CoRR abs/2105.04129 (2021) - 2019
- [i1]Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, Martha White:
Meta-descent for Online, Continual Prediction. CoRR abs/1907.07751 (2019)
Coauthor Index
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