BayesOpt: A Bayesian Optimization Library for Nonlinear Optimization, Experimental Design and Bandits
BayesOpt is a library with state-of-the-art Bayesian optimization methods to solve nonlinear optimization, stochastic bandits or sequential experimental design problems.
A Meta-Analysis of the Anomaly Detection Problem
The intended contributions of this article are many; in addition to providing a large publicly-available corpus of anomaly detection benchmarks, we provide an ontology for describing anomaly detection contexts, a methodology for controlling various aspects of benchmark creation, guidelines for future experimental design and a discussion of the many potential pitfalls of trying to measure success in this field.
Sequential Bayesian optimal experimental design via approximate dynamic programming
wgshen/sOED
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Advantages over batch and greedy design are then demonstrated on a nonlinear source inversion problem where we seek an optimal policy for sequential sensing.
Testing separability and independence of perceptual dimensions with general recognition theory: A tutorial and new R package (grtools)
We describe the software and provide a practical tutorial on how to perform each of the analyses available in grtools.
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
Our guarantees are characterized by a combination of the (generalized) curvature $\alpha$ and the submodularity ratio $\gamma$.
Quadratic Unconstrained Binary Optimization Problem Preprocessing: Theory and Empirical Analysis
The Quadratic Unconstrained Binary Optimization problem (QUBO) has become a unifying model for representing a wide range of combinatorial optimization problems, and for linking a variety of disciplines that face these problems.
Variational online learning of neural dynamics
catniplab/vjf
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It brings the challenge of learning both latent neural state and the underlying dynamical system because neither is known for neural systems a priori.
A Capacity Scaling Law for Artificial Neural Networks
First, we derive the calculation of what we call the lossless memory (LM) dimension.
Information Assisted Dictionary Learning for fMRI data analysis
The new method allows the incorporation of a priori knowledge associated both with the experimental design as well as with available brain Atlases.
RankME: Reliable Human Ratings for Natural Language Generation
Human evaluation for natural language generation (NLG) often suffers from inconsistent user ratings.