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Maximilian Balandat

21 papers · 2015–2026 · 6 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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+6 more ↓ πŸ—ΊοΈ Taxonomy Completionist (33) πŸƒ Academic Marathon Β· Half 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
🀝 Dynamic Duo (15) πŸ‘₯ Mega-Team Β· Squad πŸ”¬ Deep Specialist (15) πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (87) πŸ”₯ Unstoppable Β· Bronze

Venues

NeurIPS (10) ICML (7) ACL (1) AISTATS (1) AutoML (1) UAI (1)

Top co-authors

Eytan Bakshy (15) Samuel Daulton (8) David Eriksson (8) Sebastian Ament (5) Daniel Jiang (3) Bernard Beckerman (2) Andrew G Wilson (2) Brian Karrer (2) Sam Daulton (2) Alexandre Bayen (2)

Research topics

Machine Learning (20) Optimization & Theory (19) Mathematics & Optimization (15) Optimization (15) Bayesian & Probabilistic Β· Machine Learning (7) Artificial Intelligence (6) Core AI (4) Learning Types Β· Machine Learning (3) Deep Learning (2) Application Areas (2) Bayesian & Probabilistic Β· Artificial Intelligence (2) Learning Types Β· Deep Learning (2) Probability (2) Data Science & Analytics (1) Core Methods (1)

Keywords

bayesian optimization (15) acquisition function (8) multi-objective optimization (5) gaussian process (5) sample efficiency (4) surrogate model (3) expected improvement (3) online learning (2) hypervolume improvement (2) expected hypervolume improvement (2) regret bound (2) knowledge gradient (2) black-box optimization (2) parallel optimization (2) dual averaging (2) embedding learning (1) uncertainty quantification (1) gradient-based optimization (1) hyperparameter optimization (1) robust regression (1)

Papers

MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale Deployment ACL 2026 Ax: A Platform for Adaptive Experimentation AutoML 2025 Scalable Gaussian Processes with Latent Kronecker Structure ICML 2025 Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need ICML 2024 Bayesian Optimization of Function Networks with Partial Evaluations ICML 2024 Joint Composite Latent Space Bayesian Optimization ICML 2024 Robust Gaussian Processes via Relevance Pursuit NeurIPS 2024 Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings AISTATS 2023 Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information ICML 2023 Unexpected Improvements to Expected Improvement for Bayesian Optimization NeurIPS 2023 Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization NeurIPS 2022 Multi-objective Bayesian optimization over high-dimensional search spaces UAI 2022 Robust Multi-Objective Bayesian Optimization Under Input Noise ICML 2022 Bayesian Optimization with High-Dimensional Outputs NeurIPS 2021 Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs NeurIPS 2021 Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement NeurIPS 2021 BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization NeurIPS 2020 Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization NeurIPS 2020 Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees NeurIPS 2020 Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games NeurIPS 2016 The Hedge Algorithm on a Continuum ICML 2015