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Research

Our research team is constantly developing new optimization techniques for real-world problems.

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Our team’s peer-reviewed research.

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Research from our academic users.

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Publications

optimization

Are You Tampering With My Data?

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Stealing Hyperparameters in Machine Learning

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Bayesian Optimization
On the Role of Model Uncertainties in Bayesian Optimization
Bayesian Optimization, Hyperparameter Optimization
Fragment-Based T-SMILES for De Novo Molecular Generation
Aluminum Design, Bayesian Optimization
Novelis Taps HPC and SigOpt Platform To Optimize Products for Strength and Safety
Bayesian Optimization, Hyperparameter Optimization, Robotics
Vastus and Gastrocnemius Improve Hopping Efficiency and Joints Synchronicity at Different Frequencies: A Robotic Study
Materials Science
Engineering of Surface Oxygen Vacancies in Co-free Concentration-Gradient Li-Rich Cathodes for High-Capacity Batteries
Aluminum Design, Machine Learning
A Machine Learning Model to Predict Yield Surfaces from Crystal Plasticity Simulations
CNN, Materials Science
Graph Neural Networks for Efficient Learning of Mechanical Properties of Polycrystals
CNN, Hyperparameter Optimization
Hyperparameter Tuning in Convolutional Neural Network for Face Touching Activity Recognition using Accelerometer Data
Machine Learning, Materials Science, Materials Science
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science
Hyperparameter Optimization
A Self-evolving Agent System for Power System Online Corrective Control
Hyperparameter Optimization, Training & Tuning
SIHG4SR: Side Information Heterogeneous Graph for Session Recommender
Biology
Mesenchymal Cell Migration within 3D Microenvironments: an Integrative Perspective from the Membrane to the Nucleus
Deep Learning, Machine Learning
A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing
Unified GRF-based control for adjusting hopping frequency with various robot configurations
LSTM
iHearken: Chewing sound signal analysis based food intake recognition system using Bi-LSTM softmax network
Biology
Temperature elevation detection in migrating cells
Bayesian Optimization
Sample-efficient Search for Satisfactory OLED Designs
Biology, Hyperparameter Optimization, Materials Science, Supervised, Unsupervised
Chemistry-informed macromolecule graph representation for similarity computation, unsupervised and supervised learning
Applied, Deep Learning, Gradient Boosting, Machine Learning, Prediction
Explainable long-term building energy consumption prediction using QLattice
Graph Neural Networks
Dimensionality Reduction Meets Message Passing for Graph Node Embeddings
BERT, Biology, Hyperparameter Optimization, Prediction
SignalP 6.0 predicts all five types of signal peptides using protein language models
Deep Learning, Graph Neural Networks, Machine Learning, Materials Science, Prediction, Research
Crystal graph convolutional neural networks for per-site property prediction
BERT, Natural Language, Transformers
Dynamic-TinyBERT: Boost TinyBERT’s Inference Efficiency by Dynamic Sequence Length
Deep Learning, Machine Learning, Materials Science, Prediction
Multi-fidelity prediction of molecular optical peaks with deep learning
Hyperparameter Optimization, Machine Learning
Automated Machine Learning for Multimedia
Deep Learning, Experiment Management, Hyperparameter Optimization, Materials Science
Deep learning to design nuclear-targeting abiotic miniproteins
Bayesian Optimization, Hyperparameter Optimization, Machine Learning, Materials Science, Pytorch
Sampling Lattices in Semi-Grand Canonical Ensemble with Autoregressive Machine Learning
Bayesian Optimization, Experiment Management, Robotics, Simulations & Backtests
Adjustable Compliance and Force Feedback as Key Elements for Stable and Efficient Hopping
Experiment Management, Hyperparameter Optimization, Knowledge Graphs, Natural Language, Research
Semantic Question Answering Over Knowledge Graphs: Pitfalls and Pearls
Activity Recognition, Applied, Biology, Human Activity Recognition, Time Series
Short Term Blood Glucose Prediction based on Continuous Glucose Monitoring Data
Biology, Deep Learning, Hyperparameter Optimization, Recurrent Neural Network, RNN
Prediction of GPI-anchored proteins with pointer neural networks
Company news, Research
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
Applied AI Insights, Healthcare, Hyperparameter Optimization, Materials Science
Chemistry-informed Macromolecule Graph Representation for Similarity Computation and Supervised Learning
CNN, Deep Learning, Human Activity Recognition, Hyperparameter Optimization, LSTM
Smartwatch-based Human Activity Recognition Using Hybrid LSTM Network
Healthcare, Hyperparameter Optimization, Machine Learning
An Efficacy of Spectral Features with Boosted Decision Tree Algorithm for Automatic Heart Sound Classification
Applied AI Insights, Convolutional Neural Networks, Deep Learning, Vision
3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis
Deep Learning, Hyperparameter Optimization, LSTM, Training & Tuning
Enhanced Hand-Oriented Activity Recognition Based on Smartwatch Sensor Data Using LSTMs
Applied, Convolutional Neural Networks, Research, Speech
Exploring Swedish and English fastText Embeddings with the Transformer
Advanced Optimization Techniques, Applied, Applied AI Insights, Deep Learning, Healthcare
Deep Learning for Prediction and Optimization of Fast-Flow Peptide Synthesis
Applied, Applied AI Insights, Deep Learning, Healthcare, Materials Science
GEOM: Energy-annotated molecular conformations for property prediction and molecular generation
Methodology, Research
On Variable and Random Shape Gaussian Interpolations
Advanced Optimization Techniques, Methodology, Research
Bayesian Optimization for Adaptive Experimental Design: A Review
Advanced Optimization Techniques, Augmented ML Workflow, Convolutional Neural Networks, Deep Learning, Modeling Best Practices, Research, Training & Tuning
Trainable Spectrally Initializable Matrix Transformations in Convolutional Neural Networks
MDP-based Shallow Parsing in Distantly Supervised QA Systems
Deep Learning, SigOpt 101
Deep Learning: The Revolution in AI
Deep Learning, Methodology
Hybrid Stochastic GA-Bayesian Search for Deep Convolutional Neural Network Model Selection
Activity Recognition, Convolutional Neural Networks, Data Augmentation, Deep Learning, Research
Improving CNN-based activity recognition by data augmentation and transfer learning
Applied, Methodology
Improving Reproducible Deep Learning Workflows with DeepDIVA
Recognizing Physical Activity of Older People from Wearable Sensors and Inconsistent Data
E2E NLG Challenge Submission: Towards Controllable Generation of Diverse Natural Language
Global Optimization in Machine Learning: The Design of a Predictive Analytics Application
Advanced Optimization Techniques, All Model Types
Tutorials in Optimization Research: Bayesian Optimization
Convolutional Neural Network Based Human Identification Using Outer Ear Images
All Model Types, Applied AI Insights
Integration of in vitro and in silico Models Using Bayesian Optimization With an Application to Stochastic Modeling of Mesenchymal 3D Cell Migration
Machine Learning, Training & Tuning
Stealing Hyperparameters in Machine Learning
Applied AI Insights, Deep Learning
An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties
Applied AI Insights, Deep Learning
Are You Tampering With My Data?
Applied AI Insights, Deep Learning
Development of Convolutional Neural Network Based Instance Segmentation Algorithm to Acquire Quantitative Criteria of Mouse Development
Applied AI Insights, Deep Learning
Applying Neural Networks for Tire Pressure Monitoring Systems
Applied AI Insights, Simulations & Backtests
Bayesian optimization of pump operations in water distribution systems
Applied AI Insights, Deep Learning
Generating High-Quality Surface Realizations Using Data Augmentation and Factored Sequence Models
Applied AI Insights, Deep Learning
Preferred Answer Selection in Stack Overflow
Deep Learning, Modeling Best Practices
A Modern Take on the Bias-Variance Tradeoff in Neural Networks
Machine Learning, Modeling Best Practices
Advances in Using GPs with Derivative Observations
Augmented ML Workflow, Machine Learning
Artificial Intelligence in Value Creation: Improving Competitive Advantage
Advanced Optimization Techniques, All Model Types
Metis: Robustly Optimizing Tail Latencies of Cloud Systems
Advanced Optimization Techniques, Deep Learning
MONAS: Multi-Objective Neural Architecture Search using Reinforcement Learning
Augmented ML Workflow, Machine Learning
Oríon: Experiment Version Control for Efficient Hyperparameter Optimization
Augmented ML Workflow, Deep Learning
DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments
All Model Types, Applied AI Insights
How AI Is Transforming Financial Services
Advanced Optimization Techniques, All Model Types
Low-Level Augmented Bayesian Optimization for Finding the Best Cloud VM
Applied AI Insights, Deep Learning
SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties
Machine Learning, Training & Tuning
Deep Mining: Scaling Bayesian Auto-tuning of Data Science Pipelines
Advanced Optimization Techniques, Deep Learning
Convolutional Neural Networks for Atomistic Systems
Applied AI Insights, Machine Learning
Gradient Boosted Trees to Predict Store Sales
Applied AI Insights, Machine Learning
A Semi-supervised Approach for the CLPsych 2016 Shared Task