Search Results for author: Javier Gonzalez

Found 16 papers, 6 papers with code

Some strategies for the improvement of a Spanish WordNet

no code implementations GWC 2016 Matias Herrera, Javier Gonzalez, Luis Chiruzzo, Dina Wonsever

Although there are currently several versions of Princeton WordNet for different languages, the lack of development of some of these versions does not make it possible to use them in different Natural Language Processing applications.

AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires

no code implementations26 Apr 2023 Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Max Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier Gonzalez, Julia Greissl, Edward Meeds

Recent advances in immunomics have shown that T-cell receptor (TCR) signatures can accurately predict active or recent infection by leveraging the high specificity of TCR binding to disease antigens.

Specificity

Invariant Priors for Bayesian Quadrature

no code implementations2 Dec 2021 Masha Naslidnyk, Javier Gonzalez, Maren Mahsereci

Bayesian quadrature (BQ) is a model-based numerical integration method that is able to increase sample efficiency by encoding and leveraging known structure of the integration task at hand.

Numerical Integration

RKHS-SHAP: Shapley Values for Kernel Methods

no code implementations18 Oct 2021 Siu Lun Chau, Robert Hu, Javier Gonzalez, Dino Sejdinovic

Feature attribution for kernel methods is often heuristic and not individualised for each prediction.

GIBBON: General-purpose Information-Based Bayesian OptimisatioN

no code implementations5 Feb 2021 Henry B. Moss, David S. Leslie, Javier Gonzalez, Paul Rayson

This paper describes a general-purpose extension of max-value entropy search, a popular approach for Bayesian Optimisation (BO).

Bayesian Optimisation Point Processes

Polarization calibration techniques for new-generation VLBI

no code implementations10 Dec 2020 Ivan Marti-Vidal, Alejandro Mus, Michael Janssen, Pablo de Vicente, Javier Gonzalez

The calibration and analysis of polarization observations in Very Long Baseline Interferometry (VLBI) requires the use of specific algorithms that suffer from several limitations, closely related to assumptions in the data properties that may not hold in observations taken with new-generation VLBI equipment.

Instrumentation and Methods for Astrophysics

BOSS: Bayesian Optimization over String Spaces

1 code implementation NeurIPS 2020 Henry B. Moss, Daniel Beck, Javier Gonzalez, David S. Leslie, Paul Rayson

This article develops a Bayesian optimization (BO) method which acts directly over raw strings, proposing the first uses of string kernels and genetic algorithms within BO loops.

Bayesian Optimization

BINOCULARS for Efficient, Nonmyopic Sequential Experimental Design

1 code implementation ICML 2020 Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett

Finite-horizon sequential experimental design (SED) arises naturally in many contexts, including hyperparameter tuning in machine learning among more traditional settings.

Bayesian Optimization Experimental Design

Meta-Surrogate Benchmarking for Hyperparameter Optimization

1 code implementation NeurIPS 2019 Aaron Klein, Zhenwen Dai, Frank Hutter, Neil Lawrence, Javier Gonzalez

Despite the recent progress in hyperparameter optimization (HPO), available benchmarks that resemble real-world scenarios consist of a few and very large problem instances that are expensive to solve.

Benchmarking Hyperparameter Optimization

Active Multi-Information Source Bayesian Quadrature

no code implementations27 Mar 2019 Alexandra Gessner, Javier Gonzalez, Maren Mahsereci

Bayesian quadrature (BQ) is a sample-efficient probabilistic numerical method to solve integrals of expensive-to-evaluate black-box functions, yet so far, active BQ learning schemes focus merely on the integrand itself as information source, and do not allow for information transfer from cheaper, related functions.

Active Learning

Preferential Bayesian Optimization

no code implementations12 Apr 2017 Javier Gonzalez, Zhenwen Dai, Andreas Damianou, Neil D. Lawrence

Bayesian optimization (BO) has emerged during the last few years as an effective approach to optimizing black-box functions where direct queries of the objective are expensive.

Bayesian Optimization Recommendation Systems

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