Abbas Kazerouni

Management Science and Operations Research · 2017

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Management Science and Operations Research — 32 citations into it
• Artificial Intelligence — 31 citations into it; #18,628 of 35,345 by trust here, #16,166 by citations
• Reinforcement Learning — 21 citations into it; #1,356 of 2,242 by trust here, #1,415 by citations
• Probabilistic & Bayesian Methods — 8 citations into it

Whom Abbas Kazerouni trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Daniel Russo
2. Malcolm J. A. Strens
3. Ian Osband
4. Shipra Agrawal
5. Benjamin Van Roy
6. Emilie Kaufmann
7. Olivier Chapelle
8. Richard S. Sutton

Who trusts Abbas Kazerouni overall

1. Brendan O'Donoghue
2. Maria Dimakopoulou

Papers from Abbas Kazerouni's perspective

Ordered by how strongly the researchers Abbas Kazerouni trusts endorse each paper. Same corpus, a different order for every researcher.

1. Asymptotically efficient adaptive allocation rules
2. Finite-time Analysis of the Multiarmed Bandit Problem
3. ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES
4. A contextual-bandit approach to personalized news article recommendation
5. Near-optimal Regret Bounds for Reinforcement Learning
6. A Bayesian Framework for Reinforcement Learning
7. Stochastic Linear Optimization under Bandit Feedback
8. Deep Exploration via Bootstrapped DQN
9. Multi-armed Bandit Allocation Indices
10. (More) Efficient Reinforcement Learning via Posterior Sampling

Their papers

• A Tutorial on Thompson Sampling (2017) — 1,218 citations