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Ian Osband

20 papers · 2013–2023 · 5 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+9 more ↓ πŸ—ΊοΈ Taxonomy Completionist (34) πŸƒ Academic Marathon Β· Half 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
🀝 Dynamic Duo (14) πŸ”¬ Deep Specialist (10) πŸ‘‘ Triple Crown πŸš€ Conference Pioneer πŸ”₯ Unstoppable Β· Bronze ❓ The Questioner πŸ’Ž Century Club Β· Bronze πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (75)

Venues

NeurIPS (8) ICLR (4) ICML (4) UAI (3) JMLR (1)

Top co-authors

Benjamin Van Roy (14) Zheng Wen (7) Xiuyuan Lu (5) Vikranth Dwaracherla (5) Morteza Ibrahimi (4) Seyed Mohammad Asghari (4) RΓ©mi Munos (3) Tor Lattimore (2) Charles Blundell (2) Brendan O'Donoghue (2)

Research topics

Machine Learning (15) Reinforcement Learning (14) Methods (13) Optimization & Theory (13) Artificial Intelligence (11) Core AI (7) Learning Types Β· Machine Learning (6) Deep Learning (5) Bayesian & Probabilistic Β· Artificial Intelligence (5) Applications (3) Learning Paradigms (2) Learning Types Β· Deep Learning (2) Techniques (2) Mathematics & Optimization (1) Bayesian & Probabilistic Β· Machine Learning (1)

Keywords

reinforcement learning (7) regret bound (7) neural network (4) posterior sampling (4) markov decision process (4) randomized value function (3) joint prediction (3) deep reinforcement learning (3) exploration-exploitation tradeoff (3) thompson sampling (3) uncertainty estimation (3) epistemic neural network (2) predictive distribution (2) ensemble method (2) exploration strategy (2) posterior distribution (2) bayesian inference (2) value iteration (2) supervised learning (1) markov decision processes (1)

Papers

Approximate Thompson Sampling via Epistemic Neural Networks UAI 2023 Epistemic Neural Networks NeurIPS 2023 Evaluating high-order predictive distributions in deep learning UAI 2022 The Neural Testbed: Evaluating Joint Predictions NeurIPS 2022 Matrix games with bandit feedback UAI 2021 Behaviour Suite for Reinforcement Learning ICLR 2020 Hypermodels for Exploration ICLR 2020 Making Sense of Reinforcement Learning and Probabilistic Inference ICLR 2020 Deep Exploration via Randomized Value Functions JMLR 2019 Noisy Networks For Exploration ICLR 2018 Randomized Prior Functions for Deep Reinforcement Learning NeurIPS 2018 Scalable Coordinated Exploration in Concurrent Reinforcement Learning NeurIPS 2018 The Uncertainty Bellman Equation and Exploration ICML 2018 Minimax Regret Bounds for Reinforcement Learning ICML 2017 Why is Posterior Sampling Better than Optimism for Reinforcement Learning? ICML 2017 Deep Exploration via Bootstrapped DQN NeurIPS 2016 Generalization and Exploration via Randomized Value Functions ICML 2016 Model-based Reinforcement Learning and the Eluder Dimension NeurIPS 2014 Near-optimal Reinforcement Learning in Factored MDPs NeurIPS 2014 (More) Efficient Reinforcement Learning via Posterior Sampling NeurIPS 2013