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2020 – today
- 2024
[c12]Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini:
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity. ICLR 2024- [i12]Benjamin Howson, Sarah Filippi, Ciara Pike-Burke:
QuACK: A Multipurpose Queuing Algorithm for Cooperative k-Armed Bandits. CoRR abs/2410.23867 (2024) - 2023
- [j2]Gábor Lugosi, Ciara Pike-Burke, Pierre-André Savalle:
Bandit problems with fidelity rewards. J. Mach. Learn. Res. 24: 328:1-328:44 (2023) - [c11]Benjamin Howson, Ciara Pike-Burke, Sarah Filippi:
Optimism and Delays in Episodic Reinforcement Learning. AISTATS 2023: 6061-6094 - [c10]Benjamin Howson, Ciara Pike-Burke, Sarah Filippi:
Delayed Feedback in Generalised Linear Bandits Revisited. AISTATS 2023: 6095-6119 - [c9]Sattar Vakili, Danyal Ahmed, Alberto Bernacchia, Ciara Pike-Burke:
Delayed Feedback in Kernel Bandits. ICML 2023: 34779-34792 - [c8]Dirk van der Hoeven, Ciara Pike-Burke, Hao Qiu, Nicolò Cesa-Bianchi:
Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts. ICML 2023: 34809-34830 - [c7]Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini:
Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes. NeurIPS 2023 - [c6]Arnaud Robert, Ciara Pike-Burke, Aldo A. Faisal:
Sample Complexity of Goal-Conditioned Hierarchical Reinforcement Learning. NeurIPS 2023 - [i11]Sattar Vakili, Danyal Ahmed, Alberto Bernacchia, Ciara Pike-Burke:
Delayed Feedback in Kernel Bandits. CoRR abs/2302.00392 (2023) - [i10]Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini:
Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes. CoRR abs/2302.11381 (2023) - [i9]Dirk van der Hoeven, Ciara Pike-Burke, Hao Qiu, Nicolò Cesa-Bianchi:
Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts. CoRR abs/2307.00836 (2023) - [i8]Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini:
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity. CoRR abs/2310.01616 (2023) - 2022
- [j1]Michele Monaci, Ciara Pike-Burke
, Alberto Santini:
Exact algorithms for the 0-1 Time-Bomb Knapsack Problem. Comput. Oper. Res. 145: 105848 (2022) - [i7]Benjamin Howson, Ciara Pike-Burke, Sarah Filippi:
Delayed Feedback in Generalised Linear Bandits Revisited. CoRR abs/2207.10786 (2022) - 2021
- [c5]Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta:
Local Differential Privacy for Regret Minimization in Reinforcement Learning. NeurIPS 2021: 10561-10573 - [i6]Benjamin Howson, Ciara Pike-Burke, Sarah Filippi:
Delayed Feedback in Episodic Reinforcement Learning. CoRR abs/2111.07615 (2021) - [i5]Gábor Lugosi, Ciara Pike-Burke, Pierre-André Savalle:
Bandit problems with fidelity rewards. CoRR abs/2111.13026 (2021) - 2020
- [c4]Gergely Neu, Ciara Pike-Burke:
A Unifying View of Optimism in Episodic Reinforcement Learning. NeurIPS 2020 - [i4]Gergely Neu, Ciara Pike-Burke:
A Unifying View of Optimism in Episodic Reinforcement Learning. CoRR abs/2007.01891 (2020) - [i3]Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta:
Local Differentially Private Regret Minimization in Reinforcement Learning. CoRR abs/2010.07778 (2020)
2010 – 2019
- 2019
- [c3]Ciara Pike-Burke, Steffen Grünewälder:
Recovering Bandits. NeurIPS 2019: 14122-14131 - [i2]Ciara Pike-Burke, Steffen Grünewälder:
Recovering Bandits. CoRR abs/1910.14354 (2019) - 2018
- [c2]Ciara Pike-Burke, Shipra Agrawal, Csaba Szepesvári, Steffen Grünewälder:
Bandits with Delayed, Aggregated Anonymous Feedback. ICML 2018: 4102-4110 - 2017
- [c1]Ciara Pike-Burke, Steffen Grünewälder:
Optimistic Planning for the Stochastic Knapsack Problem. AISTATS 2017: 1114-1122 - [i1]Ciara Pike-Burke, Shipra Agrawal, Csaba Szepesvári, Steffen Grünewälder:
Bandits with Delayed Anonymous Feedback. CoRR abs/1709.06853 (2017)
Coauthor Index
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last updated on 2024-12-01 00:11 CET by the dblp team
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