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Books and Theses
- 1993
[b1]Sean B. Holden:
On the theory of generalization and self-structuring in linearly weighted connectionist networks. University of Cambridge, UK, 1993
Journal Articles
- 2021
- [j10]Sean B. Holden:
Machine Learning for Automated Theorem Proving: Learning to Solve SAT and QSAT. Found. Trends Mach. Learn. 14(6): 807-989 (2021) - 2018
- [j9]Irina M. Armean, Kathryn S. Lilley, Matthew W. B. Trotter
, Nicholas Charles Victor Pilkington, Sean B. Holden:
Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation. Bioinform. 34(11): 1884-1892 (2018) - 2016
- [j8]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:
Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics. PLoS Comput. Biol. 12(5) (2016) - 2014
- [j7]James P. Bridge, Sean B. Holden, Lawrence C. Paulson:
Machine Learning for First-Order Theorem Proving - Learning to Select a Good Heuristic. J. Autom. Reason. 53(2): 141-172 (2014) - 2002
- [j6]Robert Burbidge, Matthew W. B. Trotter, Bernard F. Buxton, Sean B. Holden:
Drug Design by Machine Learning: Support Vector Machines for Pharmaceutical Data Analysis. Comput. Chem. 26(1): 5-14 (2002) - 1997
- [j5]Sean B. Holden, Mahesan Niranjan:
Average-Case Learning Curves for Radial Basis Function Networks. Neural Comput. 9(2): 441-460 (1997) - 1995
- [j4]Sean B. Holden, Mahesan Niranjan:
On the practical applicability of VC dimension bounds. Neural Comput. 7(6): 1265-1288 (1995) - [j3]Sean B. Holden, Mahesan Niranjan:
On the statistical physics of radial basis function networks. Neural Process. Lett. 2(4): 16-19 (1995) - [j2]Sean B. Holden, Peter J. W. Rayner:
Generalization and PAC learning: some new results for the class of generalized single-layer networks. IEEE Trans. Neural Networks 6(2): 368-380 (1995) - 1994
- [j1]Martin Anthony, Sean B. Holden:
Quantifying Generalization in Linearly Weighted Neural Networks. Complex Syst. 8(2) (1994)
Conference and Workshop Papers
- 2024
- [c27]Francesco Ceccarelli, Lorenzo Giusti, Sean B. Holden, Pietro Liò:
Integrating Structure and Sequence: Protein Graph Embeddings via GNNs and LLMs. ICPRAM 2024: 582-593 - [c26]Francesco Ceccarelli, Francesco Prinzi, Pietro Liò, Salvatore Vitabile, Sean B. Holden:
MUGI-MRI: Enhancing Breast Cancer Classification through Multiplex Graph Neural Networks in DCE-MRI. IJCNN 2024: 1-8 - 2023
- [c25]Jens Otten, Sean B. Holden:
A Syntax for Connection Proofs. AReCCa@TABLEAUX 2023: 84-94 - [c24]Sean B. Holden:
Connect++: A New Automated Theorem Prover Based on the Connection Calculus. AReCCa@TABLEAUX 2023: 95-106 - [c23]Fredrik Rømming, Jens Otten, Sean B. Holden:
Connections: Markov Decision Processes for Classical, Intuitionistic and Modal Connection Calculi. AReCCa@TABLEAUX 2023: 107-118 - 2022
- [c22]Agnieszka Slowik, Léon Bottou, Sean B. Holden, Mateja Jamnik:
On the Relation between Distributionally Robust Optimization and Data Curation (Student Abstract). AAAI 2022: 13053-13054 - [c21]Chaitanya Mangla, Sean B. Holden, Lawrence C. Paulson:
Bayesian Ranking for Strategy Scheduling in Automated Theorem Provers. IJCAR 2022: 559-577 - [c20]Xiangyu Zhao, Sean B. Holden:
Towards a Competitive 3-Player Mahjong AI using Deep Reinforcement Learning. CoG 2022: 524-527 - 2021
- [c19]Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Chris Pal:
Structural Inductive Biases in Emergent Communication. CogSci 2021 - 2020
- [c18]Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson:
Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract). AAAI 2020: 13919-13920 - [c17]Chaitanya Mangla, Sean B. Holden, Lawrence C. Paulson:
Bayesian Optimisation of Solver Parameters in CBMC. SMT 2020: 37-47 - 2019
- [c16]Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson:
Bayesian Optimisation for Heuristic Configuration in Automated Theorem Proving. Vampire 2019: 45-51 - 2015
- [c15]Ivo J. P. M. Timóteo, Sean B. Holden:
Learning Dynamic Systems from Time-series Data - An Application to Gene Regulatory Networks. ICPRAM (2) 2015: 324-332 - [c14]Kiran K. Rachuri, Theus Hossmann, Cecilia Mascolo, Sean B. Holden:
Beyond location check-ins: Exploring physical and soft sensing to augment social check-in apps. PerCom 2015: 123-130 - 2010
- [c13]Richard Anthony Russell, Sean B. Holden:
Handling Goal Utility Dependencies in a Satisfiability Framework. ICAPS 2010: 145-152 - 2008
- [c12]Simon Fothergill, Robert Harle, Sean B. Holden:
Modeling the Model Athlete: Automatic Coaching of Rowing Technique. SSPR/SPR 2008: 372-381 - 2007
- [c11]Andrew Naish-Guzman, Sean B. Holden:
The Generalized FITC Approximation. NIPS 2007: 1057-1064 - [c10]Andrew Naish-Guzman, Sean B. Holden:
Robust Regression with Twinned Gaussian Processes. NIPS 2007: 1065-1072 - 2005
- [c9]Ulrich Paquet, Sean B. Holden, Andrew Naish-Guzman:
Bayesian Hierarchical Ordinal Regression. ICANN (2) 2005: 267-272 - [c8]Andrew Naish-Guzman, Sean B. Holden, Ulrich Paquet:
On the Explicit Use of Example Weights in the Construction of Classifiers. ICANN (2) 2005: 307-312 - 2001
- [c7]Robert Burbidge, Matthew W. B. Trotter, Bernard F. Buxton, Sean B. Holden:
STAR - Sparsity through Automated Rejection. IWANN (1) 2001: 653-660 - [c6]Jeevani Wickramaratna, Sean B. Holden, Bernard F. Buxton:
Performance Degradation in Boosting. Multiple Classifier Systems 2001: 11-21 - 1998
- [c5]Martin Anthony, Sean B. Holden:
Cross-Validation for Binary Classification by Real-Valued Functions: Theoretical Analysis. COLT 1998: 218-229 - 1996
- [c4]Sean B. Holden:
PAC-Like Upper Bounds for the Sample Complexity of Leave-one-Out Cross-Validation. COLT 1996: 41-50 - 1993
- [c3]Martin Anthony, Sean B. Holden:
On the Power of Polynomial Discriminators and Radial Basis Function Networks. COLT 1993: 158-164 - 1992
- [c2]Sean B. Holden, Peter J. W. Rayner:
Generalization and learning in Volterra and radial basis function networks: a theoretical analysis. ICASSP 1992: 273-276 - 1991
- [c1]Michael R. Lynch, Peter J. W. Rayner, Sean B. Holden:
Removal of degeneracy in adaptive Volterra networks by dynamic structuring. ICASSP 1991: 2069-2072
Data and Artifacts
- 2013
- [d1]James P. Bridge, Sean B. Holden, Lawrence C. Paulson:
First-order theorem proving. UCI Machine Learning Repository, 2013
Informal and Other Publications
- 2023
- [i5]Francesco Ceccarelli, Lorenzo Giusti, Sean B. Holden, Pietro Liò:
Neural Embeddings for Protein Graphs. CoRR abs/2306.04667 (2023) - 2022
- [i4]Xiangyu Zhao, Sean B. Holden:
Building a 3-Player Mahjong AI using Deep Reinforcement Learning. CoRR abs/2202.12847 (2022) - 2020
- [i3]Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden:
Towards Graph Representation Learning in Emergent Communication. CoRR abs/2001.09063 (2020) - [i2]Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Christopher J. Pal:
Exploring Structural Inductive Biases in Emergent Communication. CoRR abs/2002.01335 (2020) - 2019
- [i1]Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson:
Bayesian Optimisation with Gaussian Processes for Premise Selection. CoRR abs/1909.09137 (2019)
Coauthor Index
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