Sean B. Holden

According to our database, Sean B. Holden authored at least 43 papers between 1991 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Integrating Structure and Sequence: Protein Graph Embeddings via GNNs and LLMs.

Francesco Ceccarelli, Lorenzo Giusti, Sean B. Holden, Pietro Liò

Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods, 2024

2023

Neural Embeddings for Protein Graphs.

Francesco Ceccarelli, Lorenzo Giusti, Sean B. Holden, Pietro Liò

CoRR, 2023

Connections: Markov Decision Processes for Classical, Intuitionistic and Modal Connection Calculi.

Fredrik Rømming, Jens Otten, Sean B. Holden

Proceedings of the 1st International Workshop on Automated Reasoning with Connection Calculi (AReCCa 2023) affiliated with the 32nd International Conference on Automated Reasoning with Analytic Tableaux and Related Methods (TABLEAUX 2023), 2023

A Syntax for Connection Proofs.

Jens Otten, Sean B. Holden

Proceedings of the 1st International Workshop on Automated Reasoning with Connection Calculi (AReCCa 2023) affiliated with the 32nd International Conference on Automated Reasoning with Analytic Tableaux and Related Methods (TABLEAUX 2023), 2023

Connect++: A New Automated Theorem Prover Based on the Connection Calculus.

Sean B. Holden

Proceedings of the 1st International Workshop on Automated Reasoning with Connection Calculi (AReCCa 2023) affiliated with the 32nd International Conference on Automated Reasoning with Analytic Tableaux and Related Methods (TABLEAUX 2023), 2023

2022

Building a 3-Player Mahjong AI using Deep Reinforcement Learning.

Xiangyu Zhao, Sean B. Holden

CoRR, 2022

Towards a Competitive 3-Player Mahjong AI using Deep Reinforcement Learning.

Xiangyu Zhao, Sean B. Holden

Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

Bayesian Ranking for Strategy Scheduling in Automated Theorem Provers.

Chaitanya Mangla, Sean B. Holden, Lawrence C. Paulson

Proceedings of the Automated Reasoning - 11th International Joint Conference, 2022

On the Relation between Distributionally Robust Optimization and Data Curation (Student Abstract).

Agnieszka Slowik, Léon Bottou, Sean B. Holden, Mateja Jamnik

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Machine Learning for Automated Theorem Proving: Learning to Solve SAT and QSAT.

Sean B. Holden

Found. Trends Mach. Learn., 2021

Structural Inductive Biases in Emergent Communication.

Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Chris Pal

Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

2020

Exploring Structural Inductive Biases in Emergent Communication.

Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Christopher J. Pal

CoRR, 2020

Towards Graph Representation Learning in Emergent Communication.

Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden

CoRR, 2020

Bayesian Optimisation of Solver Parameters in CBMC.

Chaitanya Mangla, Sean B. Holden, Lawrence C. Paulson

Proceedings of the 18th International Workshop on Satisfiability Modulo Theories co-located with the 10th International Joint Conference on Automated Reasoning (IJCAR 2020), 2020

Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract).

Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Bayesian Optimisation with Gaussian Processes for Premise Selection.

Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson

CoRR, 2019

Bayesian Optimisation for Heuristic Configuration in Automated Theorem Proving.

Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson

Proceedings of the Vampire 2018 and Vampire 2019. The 5th and 6th Vampire Workshops, 2019

2018

Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.

Irina M. Armean, Kathryn S. Lilley, Matthew W. B. Trotter, Nicholas Charles Victor Pilkington, Sean B. Holden

Bioinform., 2018

2016

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics.

Lisa M. Breckels, Sean B. Holden, David Wojnar, Claire M. Mulvey, Andy Christoforou, Arnoud Groen, Matthew W. B. Trotter, Oliver Kohlbacher, Kathryn S. Lilley, Laurent Gatto

PLoS Comput. Biol., 2016

2015

Beyond location check-ins: Exploring physical and soft sensing to augment social check-in apps.

Kiran K. Rachuri, Theus Hossmann, Cecilia Mascolo, Sean B. Holden

Proceedings of the 2015 IEEE International Conference on Pervasive Computing and Communications, 2015

Learning Dynamic Systems from Time-series Data - An Application to Gene Regulatory Networks.

Ivo J. P. M. Timóteo, Sean B. Holden

Proceedings of the ICPRAM 2015, 2015

2014

Machine Learning for First-Order Theorem Proving - Learning to Select a Good Heuristic.

James P. Bridge, Sean B. Holden, Lawrence C. Paulson

J. Autom. Reason., 2014

2013

First-order theorem proving.

James P. Bridge, Sean B. Holden, Lawrence C. Paulson

Dataset, April, 2013

2010

Handling Goal Utility Dependencies in a Satisfiability Framework.

Richard Anthony Russell, Sean B. Holden

Proceedings of the 20th International Conference on Automated Planning and Scheduling, 2010

2008

Modeling the Model Athlete: Automatic Coaching of Rowing Technique.

Simon Fothergill, Robert Harle, Sean B. Holden

Proceedings of the Structural, 2008

2007

The Generalized FITC Approximation.

Andrew Naish-Guzman, Sean B. Holden

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Robust Regression with Twinned Gaussian Processes.

Andrew Naish-Guzman, Sean B. Holden

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2005

Bayesian Hierarchical Ordinal Regression.

Ulrich Paquet, Sean B. Holden, Andrew Naish-Guzman

Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

On the Explicit Use of Example Weights in the Construction of Classifiers.

Andrew Naish-Guzman, Sean B. Holden, Ulrich Paquet

Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

2002

Drug Design by Machine Learning: Support Vector Machines for Pharmaceutical Data Analysis.

Robert Burbidge, Matthew W. B. Trotter, Bernard F. Buxton, Sean B. Holden

Comput. Chem., 2002

2001

Performance Degradation in Boosting.

Jeevani Wickramaratna, Sean B. Holden, Bernard F. Buxton

Proceedings of the Multiple Classifier Systems, Second International Workshop, 2001

STAR - Sparsity through Automated Rejection.

Robert Burbidge, Matthew W. B. Trotter, Bernard F. Buxton, Sean B. Holden

Proceedings of the Connectionist Models of Neurons, 2001

1998

Cross-Validation for Binary Classification by Real-Valued Functions: Theoretical Analysis.

Martin Anthony, Sean B. Holden

Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

1997

Average-Case Learning Curves for Radial Basis Function Networks.

Sean B. Holden, Mahesan Niranjan

Neural Comput., 1997

1996

PAC-Like Upper Bounds for the Sample Complexity of Leave-one-Out Cross-Validation.

Sean B. Holden

Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995

Generalization and PAC learning: some new results for the class of generalized single-layer networks.

Sean B. Holden, Peter J. W. Rayner

IEEE Trans. Neural Networks, 1995

On the statistical physics of radial basis function networks.

Sean B. Holden, Mahesan Niranjan

Neural Process. Lett., 1995

On the practical applicability of VC dimension bounds.

Sean B. Holden, Mahesan Niranjan

Neural Comput., 1995

1994

Quantifying Generalization in Linearly Weighted Neural Networks.

Martin Anthony, Sean B. Holden

Complex Syst., 1994

1993

On the theory of generalization and self-structuring in linearly weighted connectionist networks.

Sean B. Holden

PhD thesis, 1993

On the Power of Polynomial Discriminators and Radial Basis Function Networks.

Martin Anthony, Sean B. Holden

Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

1992

Generalization and learning in Volterra and radial basis function networks: a theoretical analysis.

Sean B. Holden, Peter J. W. Rayner

Proceedings of the 1992 IEEE International Conference on Acoustics, 1992

1991

Removal of degeneracy in adaptive Volterra networks by dynamic structuring.

Michael R. Lynch, Peter J. W. Rayner, Sean B. Holden

Proceedings of the 1991 International Conference on Acoustics, 1991