James Cussens
13 papers · 2000–2026 · 7 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (22) 🏃 Academic Marathon · Ultra 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Topic Evolution
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Conference Pioneer
🔥
Unstoppable · Bronze
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Prolific Year · Productive
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Century Club · Bronze
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Keyword Collector
(54)
Top co-authors
Research topics
Machine Learning
(11)
Artificial Intelligence
(7)
Bayesian & Probabilistic · Machine Learning
(7)
Core Methods
(7)
Mathematics & Optimization
(6)
Optimization
(6)
Optimization & Theory
(6)
Bayesian & Probabilistic · Artificial Intelligence
(5)
Computer Science
(2)
Knowledge & Reasoning
(2)
Core AI
(2)
Foundations
(2)
Reasoning
(2)
Mathematics
(1)
Keywords
graphical model
(6)
structure learning
(6)
integer programming
(5)
bayesian network
(5)
combinatorial optimization
(4)
chordal graph polytope
(2)
chordal graph
(2)
cutting plane
(2)
causal discovery
(2)
integer linear programming
(2)
bayesian network structure learning
(2)
markov random field
(1)
gradient descent
(1)
model averaging
(1)
conditional independence
(1)
probability distribution
(1)
convex hull
(1)
graph cut
(1)
probabilistic graphical model
(1)
bayesian network structure
(1)
Papers
Learning Bayesian Network Classifiers to Minimize Class Variable Parameters
JMLR 2026
Branch-Price-and-Cut for Causal Discovery
CLeaR 2023
A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations
PGM 2020
Dual Formulation of the Chordal Graph Conjecture
PGM 2020
GOBNILP: Learning Bayesian network structure with integer programming
PGM 2020
Kernel-based Approach for Learning Causal Graphs from Mixed Data
PGM 2020
On Pruning for Score-Based Bayesian Network Structure Learning
AISTATS 2020
Finding All Bayesian Network Structures within a Factor of Optimal
AAAI 2019
Markov Random Field MAP as Set Partitioning
PGM 2018
Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract)
IJCAI 2017
The Chordal Graph Polytope for Learning Decomposable Models
PGM 2016
Introduction to the Special Issue on Inductive Logic Programming
JMLR 2003
Incorporating Linguistics Constraints into Inductive Logic Programming
CoNLL 2000