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Learning Optimal Decision Trees using Constraint Programming (Extended Abstract)

Hélène Verhaeghe, Siegfried Nijssen, Gilles Pesant, Claude-Guy Quimper, Pierre Schaus
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
In this paper, we introduce a new approach to learn decision trees using constraint programming.  ...  Decision trees are among the most popular classification models in machine learning. Traditionally, they are learned using greedy algorithms.  ...  decision-making.  ... 
doi:10.24963/ijcai.2020/654 dblp:conf/ijcai/FosterS20 fatcat:rpphxfbtebatzgb6zn5sjwizku

What's Hot at CPAIOR (Extended Abstract)

Claude-Guy Quimper
2017 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
The 13th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming (CPAIOR 2016), was held in Banff, Canada, May 29 - June 1, 2016.  ...  In order to trigger exchanges between the constraint programming and the operations research community, CPAIOR was co-located with CORS 2016, the Canadian Operational Research society's conference.  ...  letting mathematical programming lead the optimization process. submitted to the Constraint Journal while still be presented at the conference.  ... 
doi:10.1609/aaai.v31i1.10640 fatcat:nsvn7tyaznb6pnsakg75myszri

Query strategies for priced information (extended abstract)

Moses Charikar, Ronald Fagin, Venkatesan Guruswami, Jon Kleinberg, Prabhakar Raghavan, Amit Sahai
2000 Proceedings of the thirty-second annual ACM symposium on Theory of computing - STOC '00  
We provide algorithms that achieve the optimal competitive ratio for functions that include arbitrary Boolean AND/OR trees, and for the problem of searching in a sorted array.  ...  The algorithm queries inputs sequentially, trying to learn the value of the function for the minimum cost.  ...  Acknowledgments We thank Ravi Kumar for useful discussions and for suggesting the generalization to threshold trees.  ... 
doi:10.1145/335305.335382 dblp:conf/stoc/CharikarFGKRS00 fatcat:kbpwyz7ttbahrbqgr4vrxovoxe

Symbolic mathematics system evaluators (extended abstract)

Richard J. Fateman
1996 Proceedings of the 1996 international symposium on Symbolic and algebraic computation - ISSAC '96  
Evaluation" of expressions and programs in a computer algebra system is central to every system, but inevitably fails to provide complete satisfaction.  ...  In traversing the tree downward, the first phase of evaluation imposes the constraint that the types of its arguments must (at least) be objects that can be added.  ...  In spite of the plethora of eval-programs, a serious programmer would be well advised to learn of yet additional commands with "evaluation-like" features in Maple.  ... 
doi:10.1145/236869.236907 dblp:conf/issac/Fateman96 fatcat:bzwdnup5ifh6jjgzcfpsyffy5y

Variable Elimination in Binary CSPs (Extended Abstract)

Martin C. Cooper, Achref El Mouelhi, Cyril Terrioux
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
Using our variable-elimination rules in preprocessing allowed us to solve more benchmark problems than without.  ...  We investigate rules which allow variable elimination in binary CSP (constraint satisfaction problem) instances while conserving satisfiability.  ...  It was recently shown that an agent's best response can be computed in polynomial time for any bounded number of agents using dynamic programming [Xiao and Ling, 2020] .  ... 
doi:10.24963/ijcai.2020/691 dblp:conf/ijcai/Walsh20 fatcat:i4h3p6o2tvcl7iu4ah33hk2nr4

Using an Explicit Teamwork Model and Learning in RoboCup: An Extended Abstract [chapter]

Stacy Marsella, Jafar Adibi, Yaser Al-Onaizan, Ali Erdem, Randall Hill, Gal A. Kaminka, Zhun Qiu, Milind Tambe
1999 Lecture Notes in Computer Science  
This extended abstract focuses on teamwork and learning, two of the multiagent research c hallenges highlighted in RoboCup.  ...  For instance, Luke et al. 8 use genetic programming to build agents that learn to use their basic individual skills in coordination.  ... 
doi:10.1007/3-540-48422-1_19 fatcat:bxshrtmkmvdeflm7f6m46nlapu

Innovation and Global Issues 1: Extended Abstracts Book [article]

Nurettin Bilici, Ragıp Pehlivanlı, Selçuk Demirkılınç
2021 figshare.com  
The Prophet could not learn anything about him and said, "If the woman had allowed, he would have explained his situation to us."  ...  This could affect the design decisions and exposes similarities in the design phase by interacting people.  ...  In analysis of data, SPSS program was used.  ... 
doi:10.6084/m9.figshare.13634555.v1 fatcat:q5mkgjq3jrh5jn4ualb2pshj5u

Classy Trash Monster: An Educational Game for Teaching Machine Learning to Non-major Students

Joonhyung Bae, Karam Eum, Haram Kwon, Seolhee Lee, Juhan Nam, Young Yim Doh
2022 CHI Conference on Human Factors in Computing Systems Extended Abstracts  
We tried to make ML in the game usable without programming knowledge, just like using calculators without knowledge in electronic circuits.  ...  Lowering Barriers to Playing the Game We believed that making the game playable for a wide range of students, regardless of their game skills, is essential to provide optimal learning experience for all  ... 
doi:10.1145/3491101.3516487 fatcat:fvrpe3nsmberppyersi47c3obq

Lowering the barrier to applying machine learning

Kayur Patel
2010 Proceedings of the 28th of the international conference extended abstracts on Human factors in computing systems - CHI EA '10  
I examine how data affects the way we program. Specifically, this dissertation focuses on using machine learning algorithms to train a model.  ...  Lowering the Barrier to Applying Machine Learning Data is driving the future of computation: analysis, visualization, and learning algorithms power systems that help us diagnose cancer, live sustainably  ...  The constraint would assert that for all future experiments, the accuracy of Naïve Bayes and decision trees should be lower than support vector machines.  ... 
doi:10.1145/1753846.1753882 dblp:conf/chi/Patel10 fatcat:ctphoo6owzfnpf53ihq7kjix3e

Grand challenges: companies and universities working for a better society (Extended Abstracts)

MARTA UGOLINI
2021 Sinergie Italian Journal of Management  
Gli Extended Abstract racconti in questo volume affrontano la tematica con una varietà di argomenti, punti di vista, prospettive.  ...  ., HUSE M. (2010), "Women directors' contribution to board decision-making and strategic involvement: The role of equality perception", European Management Review, vol. 7, n. 1, pp. 16-29. OECD (2009)  ...  Some of such Industry 4.0 technologies affect the manufacturing processes and outputs, from a higher optimization of the overall production process through an effective use of inputs, less waste, lower  ... 
doi:10.7433/srecp.ea.2020.01 fatcat:7tu5ulmovbauzc744x5nxjx2by

Case study

Yu-Chung Chen, Sangyoon Lee, HyeJung Hur, Jason Leigh, Andrew Johnson, Luc Renambot
2010 Proceedings of the 28th of the international conference extended abstracts on Human factors in computing systems - CHI EA '10  
This approach can be a useful example to HCI practitioners  ...  Through in-situ observation and interview evaluations from on-going expeditions, we present the system and the lesson learned in the process.  ...  Due to the time-shift and space constraints, the lighting conditions may not be optimal for core description, and that results in differences in the interpretations.  ... 
doi:10.1145/1753846.1754206 dblp:conf/chi/ChenLHLJR10 fatcat:mppf74pjhzag3imypvxpy5p4te

Exploring iterative and parallel human computation processes

Greg Little
2010 Proceedings of the 28th of the international conference extended abstracts on Human factors in computing systems - CHI EA '10  
Decision Tasks If we have two descriptions for the same image, we can use a decision task to let the process know which is best. Decision tasks solicit opinions about existing content.  ...  The goal of a decision task is to solicit an accurate response. Toward this end, decision tasks may ask for multiple responses, and use the aggregate.  ... 
doi:10.1145/1753846.1754145 dblp:conf/chi/Little10 fatcat:4iptf3yvzzeubdxvq6k2n56ave

Explanation Perspectives from the Cognitive Sciences---A Survey

Ramya Srinivasan, Ajay Chander
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
With growing adoption of AI across fields such as healthcare, finance, and the justice system, explaining an AI decision has become more important than ever before.  ...  This includes the cognitive behavioral purpose that the explanation serves for its recipients, and the structure that the explanation uses to reach those ends.  ...  While in practice these methods obtain a good * This paper is an extended abstract of Learning Optimal Decision Trees using Constraint Programming presented at The 25th International Conference on Principles  ... 
doi:10.24963/ijcai.2020/662 dblp:conf/ijcai/VerhaegheNPQS20 fatcat:56qqoyj2qjbalou3au3q6c5v7u

Improving user interaction with spoken dialog systems via shaping

Stefanie Tomko
2005 CHI '05 extended abstracts on Human factors in computing systems - CHI '05  
One problem is that users often speak beyond the bounds of what the computer is programmed to understand.  ...  However, many factors conspire to make user communication with such a system less than optimally efficient.  ...  When a back-off to the SLM was triggered, a decision tree was used to classify the utterance as to what user was most likely trying to do.  ... 
doi:10.1145/1056808.1056846 dblp:conf/chi/Tomko05 fatcat:dumficbtfjbmnig7kz3vw7g5um

CoReJava: Learning Functions Expressed as Object-Oriented Programs

Alexander Brodsky, Juan Luo, Hadon Nash
2008 2008 Seventh International Conference on Machine Learning and Applications  
Proposed and implemented is the language CoReJava (Constraint Optimization Regression in Java), which extends the programming language Java with regression analysis, i.e., the capability to do parameter  ...  To implement regression learning, the CoReJava compiler (1) analyses the structure of the parameterized Java program that represent a functional form, (2) automatically generates a constraint optimization  ...  CoReJava Constraint Compiler CoReJava translates a standard Java program into a decision problem that can be solved by various existing optimization engines.  ... 
doi:10.1109/icmla.2008.144 dblp:conf/icmla/BrodskyLN08 fatcat:7c2ivkrmlnhkfptzp2awbvnmca
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