Joaquin Quiñonero Candela

Publication Activity (10 Years)

Years Active: 2002-2023
Publications (10 Years): 3

Top Topics

Markov Decision

Computational Advertising

General Intelligence

Knowledge Representation And Reasoning

Top Venues

J. Mach. Learn. Res.

Publications

Joaquin Quiñonero Candela, Yuwen Wu, Brian Hsu, Sakshi Jain, Jennifer Ramos, Jon Adams, Robert Hallman, Kinjal Basu
Disentangling and Operationalizing AI Fairness at LinkedIn. FAccT (2023)
Joaquin Quiñonero Candela, Yuwen Wu, Brian Hsu, Sakshi Jain, Jen Ramos, Jon Adams, Robert Hallman, Kinjal Basu
Disentangling and Operationalizing AI Fairness at LinkedIn. CoRR (2023)
Chloé Bakalar, Renata Barreto, Stevie Bergman, Miranda Bogen, Bobbie Chern, Sam Corbett-Davies, Melissa Hall, Isabel Kloumann, Michelle Lam, Joaquin Quiñonero Candela, Manish Raghavan, Joshua Simons, Jonathan Tannen, Edmund Tong, Kate Vredenburgh, Jiejing Zhao
Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems. CoRR (2021)
Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu, Tao Xu, Yanxin Shi, Antoine Atallah, Ralf Herbrich, Stuart Bowers, Joaquin Quiñonero Candela
Practical Lessons from Predicting Clicks on Ads at Facebook. ADKDD@KDD (2014)
Léon Bottou, Jonas Peters, Joaquin Quiñonero Candela, Denis Xavier Charles, Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Y. Simard, Ed Snelson
Counterfactual reasoning and learning systems: the example of computational advertising. J. Mach. Learn. Res. 14 (1) (2013)
Léon Bottou, Jonas Peters, Joaquin Quiñonero Candela, Denis Xavier Charles, Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Y. Simard, Ed Snelson
Counterfactual Reasoning and Learning Systems CoRR (2012)
Thore Graepel, Joaquin Quiñonero Candela, Thomas Borchert, Ralf Herbrich
Web-Scale Bayesian Click-Through rate Prediction for Sponsored Search Advertising in Microsoft's Bing Search Engine. ICML (2010)
Miguel Lázaro-Gredilla, Joaquin Quiñonero Candela, Carl Edward Rasmussen, Aníbal R. Figueiras-Vidal
Sparse Spectrum Gaussian Process Regression. J. Mach. Learn. Res. 11 (2010)
Anton Schwaighofer, Joaquin Quiñonero Candela, Thomas Borchert, Thore Graepel, Ralf Herbrich
Scalable clustering and keyword suggestion for online advertisements. KDD Workshop on Data Mining and Audience Intelligence for Advertising (2009)
Neil D. Lawrence, Joaquin Quiñonero Candela
Local distance preservation in the GP-LVM through back constraints. ICML (2006)
Joaquin Quiñonero Candela, Carl Edward Rasmussen
A Unifying View of Sparse Approximate Gaussian Process Regression. J. Mach. Learn. Res. 6 (2005)
Joaquin Quiñonero Candela, Carl Edward Rasmussen, Fabian H. Sinz, Olivier Bousquet, Bernhard Schölkopf
Evaluating Predictive Uncertainty Challenge. MLCW (2005)
Carl Edward Rasmussen, Joaquin Quiñonero Candela
Healing the relevance vector machine through augmentation. ICML (2005)
Alexander Zien, Joaquin Quiñonero Candela
Large margin non-linear embedding. ICML (2005)
Fabian H. Sinz, Joaquin Quiñonero Candela, Gökhan H. Bakir, Carl Edward Rasmussen, Matthias O. Franz
Learning Depth from Stereo. DAGM-Symposium (2004)
Joaquin Quiñonero Candela, Carl Edward Rasmussen
Analysis of Some Methods for Reduced Rank Gaussian Process Regression. European Summer School on Multi-AgentControl (2003)
Joaquin Quiñonero Candela, Agathe Girard, Jan Larsen, Carl Edward Rasmussen
Propagation of uncertainty in Bayesian kernel models - application to multiple-step ahead forecasting. ICASSP (2) (2003)
Joaquin Quiñonero Candela, Ole Winther
Incremental Gaussian Processes. NIPS (2002)
Joaquin Quiñonero Candela, Lars Kai Hansen
Time series prediction based on the Relevance Vector Machine with adaptive kernels. ICASSP (2002)
Agathe Girard, Carl Edward Rasmussen, Joaquin Quiñonero Candela, Roderick Murray-Smith
Gaussian Process Priors with Uncertain Inputs - Application to Multiple-Step Ahead Time Series Forecasting. NIPS (2002)