Conquer the Curse of Dimensionality with EOG-HPO

The only optimization engine built specifically for ultra-high-dimensional search spaces where traditional HPO methods fail. Achieve state-of-the-art results in hyperparameter spaces of $D>100$.

Why EOG-HPO is Different

We don't compete where $D<50$. We dominate where others fail.

Active Dimensions Detection

Automatically identifies the 5-10 truly impactful parameters in spaces of 100+ dimensions, reducing effective search space by 90-95%.

Exponential Efficiency

Achieves superior results with 10x fewer evaluations compared to Bayesian Optimization in high-dimensional spaces ($D>50$).

Quality Guarantee

Consistently finds solutions orders of magnitude closer to the global optimum in complex, multi-modal search spaces.

Built for Complex AI/ML Challenges

Where traditional HPO fails spectacularly

Neural Architecture Search
D: 80-150+ Discrete/Continuous

Optimize entire neural network architectures including:

  • Cell structure decisions
  • Connection patterns
  • Operation types
  • Training hyperparameters
Sample Applications:
Vision Transformers CNN Architectures Attention Mechanisms
AutoML Pipeline Optimization
D: 75+ Mixed Spaces

End-to-end ML pipeline optimization including:

  • Feature selection (50+ dimensions)
  • Preprocessing choices
  • Model selection
  • Hyperparameter tuning
Sample Applications:
Financial Risk Models Healthcare Analytics Supply Chain Optimization
Reinforcement Learning Tuning
D: 30-50+ Sensitive Parameters

Complex RL agent optimization including:

  • Policy network architecture
  • Training algorithm parameters
  • Reward shaping parameters
  • Environment interactions
Sample Applications:
Autonomous Systems Robotics Control Game AI

Proven Performance in High-Dimensional Spaces

$D=100$ synthetic benchmark on Rastrigin function

Optimization Performance Comparison
Method Best Value Evaluations Improvement
EOG-HPO -14.2 1,000 62x Better
Bayesian Optimization -896.4 10,000 Baseline
Random Search -954.7 10,000 -6.5%
Grid Search -1,234.5 100,000* -37.7%
*Grid search extrapolated - computationally infeasible
Active Dimensions Discovery

Key Insight: EOG-HPO identified only 7 active dimensions out of 100 total dimensions, reducing effective search complexity by 93%.

Active (7)
Inactive (93)

Value-Based Pricing

Pay for results, not just compute time

Dimensionality-Based Pricing Model

Search Space Size Base Price Active Dimension Fee Evaluation Credits Best For
D < 50
Standard Problems
$199/month - 1,000 evaluations Basic model tuning
50 ≤ D ≤ 100
Complex Problems
$999/month $50/active dimension 5,000 evaluations NAS, Complex Pipelines
D > 100
Ultra-High-Dimensional
Custom Quote $75/active dimension Unlimited* Research, Enterprise NAS
Success-Based Pricing

For enterprise clients: Pay 20% of the compute cost savings achieved compared to traditional HPO methods.

Volume Discounts

Annual commitments receive 20% discount. Research institutions receive special academic pricing.

Seamless Integration

Works with your existing ML workflow

Python SDK

Simple pip install and API integration

AWS SageMaker

Native integration with SageMaker jobs

Google Vertex AI

Direct plugin for Vertex pipelines

Azure ML

Azure Machine Learning integration

Ready to Conquer High-Dimensional Optimization?

Join leading AI research labs and enterprises who trust EOG-HPO for their most complex optimization challenges.