pete's name in bib

docs/refs.bib

@@ -214,7 +214,7 @@ @article{4b54ed2e79924712bcf8e6fea3211d72
   title = {How people visually represent discrete constraint problems},
   abstract = {Problems such as timetabling or personnel allocation can be modeled and solved using discrete constraint programming languages. However, while existing constraint solving software solves such problems quickly in many cases, these systems involve specialized languages that require significant time and effort to learn and apply. These languages are typically text-based and often difficult to interpret and understand quickly, especially for people without engineering or mathematics backgrounds. Visualization could provide an alternative way to model and understand such problems. Although many visual programming languages exist for procedural languages, visual encoding of problem specifications has not received much attention. Future problem visualization languages could represent problem elements and their constraints unambiguously, but without unnecessary cognitive burdens for those needing to translate their problem's mental representation into diagrams. As a first step towards such languages, we executed a study that catalogs how people represent constraint problems graphically. We studied three groups with different expertise: non-computer scientists, computer scientists and constraint programmers and analyzed their marks on paper (e.g., arrows), gestures (e.g., pointing) and the mappings to problem concepts (e.g., containers, sets). We provide foundations to guide future tool designs allowing people to effectively grasp, model and solve problems through visual representations.},
   keywords = {Problem visualization, Problem modeling, Problem solving, Constraint programming, Visual programming languages},
-  author = {Xu Zhu and Miguel Nacenta and {\"O}zg{\"u}r Akg{\"u}n and Nightingale, {Peter William}},
+  author = {Xu Zhu and Miguel Nacenta and {\"O}zg{\"u}r Akg{\"u}n and Nightingale, {Peter}},
   year = {2019},
   month = {jan},
   day = {24},
@@ -266,7 +266,7 @@ @inproceedings{921a03b374654acdb3cf8b608e1ef86a
   title = {Closed frequent itemset mining with arbitrary side constraints},
   abstract = {Frequent itemset mining (FIM) is a method for finding regularities in transaction databases. It has several application areas, such as market basket analysis, genome analysis, and drug design. Finding frequent itemsets allows further analysis to focus on a small subset of the data. For large datasets the number of frequent itemsets can also be very large, defeating their purpose. Therefore, several extensions to FIM have been studied, such as adding high-utility (or low-cost) constraints and only finding closed (or maximal) frequent itemsets. This paper presents a constraint programming based approach that combines arbitrary side constraints with closed frequent itemset mining. Our approach allows arbitrary side constraints to be expressed in a high level and declarative language which is then translated automatically for efficient solution by a SAT solver. We compare our approach with state-of-the-art algorithms via the MiningZinc system (where possible) and show significant contributions in terms of performance and applicability.},
   keywords = {Data mining, Pattern mining, Frequent itemset mining, Closed frequent itemset mining, Constraint modelling},
-  author = {Gokberk Kocak and {\"O}zg{\"u}r Akg{\"u}n and Miguel, {Ian} and Nightingale, {Peter William}},
+  author = {Gokberk Kocak and {\"O}zg{\"u}r Akg{\"u}n and Miguel, {Ian} and Nightingale, {Peter}},
   year = {2018},
   month = {nov},
   day = {17},
@@ -310,7 +310,7 @@ @inproceedings{413b9d1324cf4826b5ea1a130eb96159
   title = {A framework for constraint based local search using ESSENCE},
   abstract = {Structured Neighbourhood Search (SNS) is a framework for constraint-based local search for problems expressed in the Essence abstract constraint specification language. The local search explores a structured neighbourhood, where each state in the neighbourhood preserves a high level structural feature of the problem. SNS derives highly structured problem-specific neighbourhoods automatically and directly from the features of the ESSENCE specification of the problem. Hence, neighbourhoods can represent important structural features of the problem, such as partitions of sets, even if that structure is obscured in the low-level input format required by a constraint solver. SNS expresses each neighbourhood as a constrained optimisation problem, which is solved with a constraint solver. We have implemented SNS, together with automatic generation of neighbourhoods for high level structures, and report high quality results for several optimisation problems.},
   keywords = {Constraints and SAT: constraint satisfaction, Constraints and SAT: modeling; formulation, Constraints and SAT: constraint ptimisation, Constraints and SAT: Constraints: solvers and tools},
-  author = {{\"O}zg{\"u}r Akg{\"u}n and Attieh, {Saad Wasim A} and Gent, {Ian Philip} and Jefferson, {Christopher} and Miguel, {Ian} and Nightingale, {Peter William} and Salamon, {Andr{\'a}s Z.} and Patrick Spracklen and Wetter, {James Patrick}},
+  author = {{\"O}zg{\"u}r Akg{\"u}n and Attieh, {Saad Wasim A} and Gent, {Ian Philip} and Jefferson, {Christopher} and Miguel, {Ian} and Nightingale, {Peter} and Salamon, {Andr{\'a}s Z.} and Patrick Spracklen and Wetter, {James Patrick}},
   year = {2018},
   month = {jul},
   day = {13},
@@ -401,7 +401,7 @@ @misc{0ef98e79e0bd426eb92227f281f4ee4e
 
 @inproceedings{ec7a3b357c8b4af4ba335c281ea87ba3,
   title = {An Automated Constraint Modelling and Solving Toolchain},
-  author = {{\"O}zg{\"u}r Akg{\"u}n and Frisch, {Alan M} and Gent, {Ian Philip} and Hussain, {Bilal Syed} and Jefferson, {Christopher} and Lars Kotthoff and Miguel, {Ian} and Nightingale, {Peter William}},
+  author = {{\"O}zg{\"u}r Akg{\"u}n and Frisch, {Alan M} and Gent, {Ian Philip} and Hussain, {Bilal Syed} and Jefferson, {Christopher} and Lars Kotthoff and Miguel, {Ian} and Nightingale, {Peter}},
   year = {2013},
   language = {English},
   booktitle = {ARW 2013 - 20th Automated Reasoning Workshop},
@@ -421,7 +421,7 @@ @inproceedings{dfc0e4b721844d9d801fb27c264086ff
 @inproceedings{066dfdbd563a40c68df2eaae83a342cd,
   title = {Automated Symmetry Breaking and Model Selection in Conjure},
   abstract = {Constraint modelling is widely recognised as a key bottleneck in applying constraint solving to a problem of interest. The Conjure automated constraint modelling system addresses this problem by automatically refining constraint models from problem specifications written in the Essence language. Essence provides familiar mathematical concepts like sets, functions and relations nested to any depth. To date, Conjure has been able to produce a set of alternative model kernels (i.e. without advanced features such as symmetry breaking or implied constraints) for a given specification. The first contribution of this paper is a method by which Conjure can break symmetry in a model as it is introduced by the modelling process. This works at the problem class level, rather than just individual instances, and does not require an expensive detection step after the model has been formulated. This allows Conjure to produce a higher quality set of models. A further limitation of Conjure has been the lack of a mechanism to select among the models it produces. The second contribution of this paper is to present two such mechanisms, allowing effective models to be chosen automatically.},
-  author = {{\"O}zg{\"u}r Akg{\"u}n and Frisch, {Alan M} and Gent, {Ian Philip} and Hussain, {Bilal Syed} and Jefferson, {Christopher} and Lars Kotthoff and Miguel, {Ian} and Nightingale, {Peter William}},
+  author = {{\"O}zg{\"u}r Akg{\"u}n and Frisch, {Alan M} and Gent, {Ian Philip} and Hussain, {Bilal Syed} and Jefferson, {Christopher} and Lars Kotthoff and Miguel, {Ian} and Nightingale, {Peter}},
   year = {2013},
   doi = {10.1007/978-3-642-40627-0_11},
   language = {English},