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Jack Parker-Holder

31 papers · 2019–2025 · 8 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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+12 more ↓ πŸ—ΊοΈ Taxonomy Completionist (49) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (12) 🀝 Dynamic Duo (12) πŸ† Keyword Champion πŸ† Grand Slam πŸ‘₯ Mega-Team Β· Squad 🧬 Topic Evolution ⚑ Prolific Year Β· Productive πŸ”₯ Unstoppable Β· Bronze πŸ’Ž Century Club Β· Bronze 🌈 Renaissance Researcher (5) πŸ—ƒοΈ Keyword Collector (138)

Venues

NeurIPS (12) ICML (10) ICLR (3) AISTATS (2) AAAI (1) AutoML (1) CoRL (1) UAI (1)

Top co-authors

Aldo Pacchiano (12) Tim RocktΓ€schel (10) Krzysztof Choromanski (7) Jakob Foerster (6) Minqi Jiang (6) Philip Ball (6) Stephen J. Roberts (5) Yunhao Tang (4) Edward Grefenstette (4) Cong Lu (4)

Research topics

Machine Learning (23) Reinforcement Learning (23) Methods (20) Artificial Intelligence (13) Learning Types Β· Machine Learning (13) Core AI (11) Optimization & Theory (10) Deep Learning (5) Applications (5) Mathematics & Optimization (3) Learning Paradigms (3) Learning Types Β· Deep Learning (3) Application Areas (2) Bayesian & Probabilistic (2) Models (2)

Keywords

reinforcement learning (12) curriculum learning (5) model-based reinforcement learning (4) deep reinforcement learning (3) continuous control (3) policy optimization (3) unsupervised environment design (3) hyperparameter optimization (3) offline reinforcement learning (3) population-based training (3) world model (3) policy gradient (3) black-box optimization (3) sample efficiency (3) bayesian optimization (2) minimax regret (2) multi-armed bandit (2) active learning (2) attention mechanism (2) data augmentation (2)

Papers

BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games ICLR 2025 Genie: Generative Interactive Environments ICML 2024 Position: Open-Endedness is Essential for Artificial Superhuman Intelligence ICML 2024 Position: Video as the New Language for Real-World Decision Making ICML 2024 Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts NeurIPS 2024 Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design NeurIPS 2023 Human-Timescale Adaptation in an Open-Ended Task Space ICML 2023 MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning ICLR 2023 Synthetic Experience Replay NeurIPS 2023 Bayesian Generational Population-Based Training AutoML 2022 Evolving Curricula with Regret-Based Environment Design ICML 2022 From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers ICML 2022 Grounding Aleatoric Uncertainty for Unsupervised Environment Design NeurIPS 2022 Learning General World Models in a Handful of Reward-Free Deployments NeurIPS 2022 Revisiting Design Choices in Offline Model Based Reinforcement Learning ICLR 2022 Same State, Different Task: Continual Reinforcement Learning without Interference AAAI 2022 Towards an Understanding of Default Policies in Multitask Policy Optimization AISTATS 2022 Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment ICML 2021 Replay-Guided Adversarial Environment Design NeurIPS 2021 Tactical Optimism and Pessimism for Deep Reinforcement Learning NeurIPS 2021 Towards tractable optimism in model-based reinforcement learning UAI 2021 Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL NeurIPS 2021 Effective Diversity in Population Based Reinforcement Learning NeurIPS 2020 Learning to Score Behaviors for Guided Policy Optimization ICML 2020 Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes AISTATS 2020 Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits NeurIPS 2020 Ready Policy One: World Building Through Active Learning ICML 2020 Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian NeurIPS 2020 Stochastic Flows and Geometric Optimization on the Orthogonal Group ICML 2020 From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization NeurIPS 2019 Provably Robust Blackbox Optimization for Reinforcement Learning CoRL 2019