On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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7 results for “BoTorch”

BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimizationcs.LG

BoTorch optimizes Bayesian optimization with MC methods and auto-differentiation.

problem Efficient global optimization for various applications.

method Monte-Carlo acquisition functions, sample average approximation, auto-differentiation, variance reduction.

result Improved sample efficiency compared to other libraries.

Bayesian optimization Monte-Carlo methods Auto-differentiation Knowledge Gradient Hardware acceleration

2019-10-14abs ↗pdf ↗

Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Axcs.LG

Bayesian optimization finds best hyperparameters for deep learning models.

problem Finding optimal hyperparameters in high-dimensional space.

method Bayesian optimization, Gaussian processes, and adaptive experimentation.

result Ax, BoTorch, and GPyTorch provide a powerful and simple framework for hyperparameter optimization.

Bayesian optimization hyperparameter tuning Gaussian processes Ax BoTorch

2019-12-11abs ↗pdf ↗

Efficient computation of the Knowledge Gradient for Bayesian Optimizationcs.LG

A new method for efficient computation of Knowledge Gradient in Bayesian optimization.

problem Efficient computation of the Knowledge Gradient for Bayesian optimization.

method One-shot Hybrid KG, a new approach combining previous ideas.

result The new method is cheap to compute and preserves theoretical properties of previous methods.

Bayesian optimization Knowledge Gradient Hybrid KG Efficient computation BOTorch

2022-09-30abs ↗pdf ↗

BoTier: Multi-Objective Bayesian Optimization with Tiered Composite Objectivescs.LG

BoTier optimizes experiments by balancing multiple objectives hierarchically.

problem Balancing multiple competing objectives in scientific experiments.

method Composite objective that flexibly represents a hierarchy of preferences over outcomes and parameters.

result Demonstrates robust applicability across various use cases and seamless integration.

Bayesian optimization multi-objective hierarchical preferences experiment planning auto-differentiable

2025-01-26abs ↗pdf ↗

A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Liftingcs.LG

SOBER framework optimizes Bayesian optimization tasks efficiently.

problem Challenges in parallel Bayesian optimization.

method Probabilistic Lifting with Kernel Quadrature.

result Versatile and flexible batch Bayesian optimization.

Bayesian optimization batch optimization kernel quadrature probabilistic lifting parallelization

2024-04-18abs ↗pdf ↗

Fair and Green Hyperparameter Optimization via Multi-objective and Multiple Information Source Bayesian Optimizationcs.LG

FanG-HPO optimizes machine learning models for fairness and low energy consumption.

problem Bias in machine learning models and high energy consumption in hyperparameter optimization.

method Combines multi-objective and multiple information source Bayesian optimization.

result FanG-HPO identifies fair and energy-efficient machine learning models.

hyperparameter optimization fairness energy efficiency Bayesian optimization multi-objective

2022-05-18abs ↗pdf ↗

Alpha Entropy Search for New Information-based Bayesian Optimizationstat.ML

AES uses α-divergence to select informative points for BO, improving optimization performance.

problem Optimizing complex functions with limited evaluations.

method AES uses α-divergence to select points based on dependency with global maximum.

result AES outperforms other information-based acquisition functions in various experiments.

Bayesian optimization Alpha entropy search Information theory KL divergence α-divergence

2024-11-25abs ↗pdf ↗