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Open-world Machine Learning: Applications, Challenges, and Opportunities [article]

Jitendra Parmar, Satyendra Singh Chouhan, Santosh Singh Rathore
2021 arXiv   pre-print
Traditional machine learning especially supervised learning follows the assumptions of closed-world learning i.e., for each testing class a training class is available.  ...  Moreover, traditional machine learning is static learning which is not appropriate for an active environment where the perspective and sources, and/or volume of data are changing rapidly.  ...  NNO is a combination of two open-space risks for model combination and open-space risk for threshold space.  ... 
arXiv:2105.13448v1 fatcat:y5u3uixeijgdxpybibivpatmaa

Gray-box optimization and factorized distribution algorithms: where two worlds collide [article]

Roberto Santana
2017 arXiv   pre-print
The paper also elaborates on some of the questions that arise when extending the use of problem structure in EAs, such as the question of evolvability, high cardinality of the variables and large definition  ...  Finally, emergent approaches that exploit neural models to capture the problem structure are covered.  ...  Both the process of identifying those building blocks (learning), and the process of combining them by sampling, are two essential ingredients of the automatic method for problem decomposition as implemented  ... 
arXiv:1707.03093v1 fatcat:3roizdmzuvai7k6ksmuy4avhcq

Effective World Modeling: Multisensor Data Fusion Methodology for Automated Driving

Jos Elfring, Rein Appeldoorn, Sjoerd van den Dries, Maurice Kwakkernaat
2016 Sensors  
A series of real-world experiments involving different sensors and algorithms demonstrates the methodology and the software architecture.  ...  As an alternative, this work presents a methodology that can be used to effectively come up with an implementation to build a consistent model of a vehicle's surroundings.  ...  ., R.A. and S.D. designed and implemented the software, M.K. coordinated the project. Conflicts of Interest: The authors declare no conflict of interest. Sensors 2016, 16, 1668  ... 
doi:10.3390/s16101668 pmid:27727171 pmcid:PMC5087456 fatcat:6bmajh7uczfjxos5efweuh7dea


Qian Zhao, Yue Shi, Liangjie Hong
2017 Proceedings of the 26th International Conference on World Wide Web - WWW '17  
Since in real-world applications we usually have both abundant numerical features and categorical features with large cardinality (e.g. geolocations, IDs, tags etc.), we design a new model, called GB-CENT  ...  Latent factor models and decision tree based models are widely used in tasks of prediction, ranking and recommendation.  ...  [8] on combining wide and deep learning in recommender systems.  ... 
doi:10.1145/3038912.3052668 dblp:conf/www/ZhaoSH17 fatcat:7khc2ozfofeudaock5bhhscxhi

Detecting Real-World Influence through Twitter

Jean-Valere Cossu, Nicolas Dugue, Vincent Labatut
2015 2015 Second European Network Intelligence Conference  
We thus propose several Machine Learning approaches based on Natural Language Processing and Social Network Analysis to label Twitter users as Influencers or not.  ...  We propose an overview of common Twitter features used to characterize such accounts and their activity, and show that these are inefficient in this context.  ...  We take advantage of these manual annotations to train several Machine Learning (ML) tools and assess their performance on classification and ranking issues.  ... 
doi:10.1109/enic.2015.20 dblp:conf/enic/CossuDL15 fatcat:2zh7xm5ltjgnvoszcmax3tzqh4

Goal Agnostic Planning using Maximum Likelihood Paths in Hypergraph World Models [article]

Christopher Robinson
2021 arXiv   pre-print
Together, these form a goal agnostic automated planning engine for an autonomous learning agent which incorporates beneficial properties of both classical Machine Learning and traditional Artificial Intelligence  ...  In this paper, we present a hypergraph--based machine learning algorithm, a datastructure--driven maintenance method, and a planning algorithm based on a probabilistic application of Dijkstra's algorithm  ...  It applies components of classical machine learning algorithms (reinforcement learning in particular) to develop an empirical world model relating observed states, actions, and the results of those actions  ... 
arXiv:2110.09442v1 fatcat:ggy2zatcnfbd3iadmpmaenlgda

Holistic aggregates in a networked world

Graham Cormode, Minos Garofalakis, S. Muthukrishnan, Rajeev Rastogi
2005 Proceedings of the 2005 ACM SIGMOD international conference on Management of data - SIGMOD '05  
In a nutshell, our algorithms employ a combination of local tracking at remote sites and simple prediction models for local site behavior in order to produce highly communication-and space-efficient solutions  ...  While traditional database systems optimize for performance on one-shot queries, emerging large-scale monitoring applications require continuous tracking of complex aggregates and data-distribution summaries  ...  , or even more sophisticated machine-learning techniques (e.g., linear or higher-order regression).  ... 
doi:10.1145/1066157.1066161 dblp:conf/sigmod/CormodeGMR05 fatcat:4znyqjnwzjemzoxnxsvo36sdzy

An Overproduce-and-Choose Strategy to Create Classifier Ensembles with Tuned SVM Parameters Applied to Real-World Fault Diagnosis [chapter]

Estefhan Dazzi Wandekokem, Flávio M. Varejão, Thomas W. Rauber
2010 Lecture Notes in Computer Science  
We present a supervised learning classification method for model-free fault detection and diagnosis, aiming to improve the maintenance quality of motor pumps installed on oil rigs.  ...  We investigate our generic fault diagnosis method on 2000 examples of real-world vibrational signals obtained from operational faulty industrial machines.  ...  Introduction The detection and diagnosis of faults in industrial machines is advantageos for economical and security reasons.  ... 
doi:10.1007/978-3-642-16687-7_66 fatcat:cmiuncvmzfb33agxm42z3suhye

The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection

Paul Bergmann, Kilian Batzner, Michael Fauser, David Sattlegger, Carsten Steger
2021 International Journal of Computer Vision  
This benchmark indicates that methods that leverage descriptors of pretrained networks outperform all other approaches and deep-learning-based generative models show considerable room for improvement.  ...  We highlight the advantages and disadvantages of multiple performance metrics as well as threshold estimation techniques.  ...  For the more traditional methods, i.e., the Variation Model and the Texture Inspection Model, we use optimized implementations of the HALCON machine vision library that entirely run on the CPU and achieve  ... 
doi:10.1007/s11263-020-01400-4 fatcat:zyzfhe2jize2fku3sdra4p57j4

Explore, Exploit or Listen: Combining Human Feedback and Policy Model to Speed up Deep Reinforcement Learning in 3D Worlds [article]

Zhiyu Lin, Brent Harrison, Aaron Keech, Mark O. Riedl
2021 arXiv   pre-print
and consistency of human feedback.  ...  We describe a method to use discrete human feedback to enhance the performance of deep learning agents in virtual three-dimensional environments by extending deep-reinforcement learning to model the confidence  ...  Acknowledgments This material is based upon work supported by the Office of Naval Research (ONR) under Grant #N00014-14-1-0003.  ... 
arXiv:1709.03969v2 fatcat:inras67hrzdbrbdzbdrmrcpety

Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects [chapter]

Jianing Zhao, Daniel M. Runfola, Peter Kemper
2017 Lecture Notes in Computer Science  
Recent research by Athey and Imbens has illustrated the potential for hybrid machine learning and causal inferential techniques which may be able to capture such heterogeneity.  ...  We use this information in conjunction with causal tree (CT) and causal forest (CF) approaches to contrast 'control' and 'treatment' geographic locations to estimate the impact of World Bank projects on  ...  Second, there is little literature in the machine learning space regarding how to cope with spatial spillover between treated and control cases.  ... 
doi:10.1007/978-3-319-71273-4_17 fatcat:6c5ouwhkujcbpl57lwf2yeivfu

Sample Debiasing in the Themis Open World Database System (Extended Version) [article]

Laurel Orr, Magda Balazinska, Dan Suciu
2020 arXiv   pre-print
We leverage apriori population aggregate information to develop and combine two different approaches for automatic debiasing: sample reweighting and Bayesian network probabilistic modeling.  ...  We build a prototype of Themis and demonstrate that Themis achieves higher query accuracy than the default AQP approach, an alternative sample reweighting technique, and a variety of Bayesian network models  ...  This work is supported by NSF AITF 1535565, NSF IIS 1907997, and a gift from Intel.  ... 
arXiv:2002.09799v2 fatcat:2pyct6ektfdkjlbsmdngeuzasi

Flexible Operator Embeddings via Deep Learning [article]

Ryan Marcus, Olga Papaemmanouil
2019 arXiv   pre-print
Experimentally, we show that our flexible operator embeddings perform well across a number of data management tasks, using both synthetic and real-world datasets.  ...  Integrating machine learning into the internals of database management systems requires significant feature engineering, a human effort-intensive process to determine the best way to represent the pieces  ...  some machine learning models), (2) how to combine available information into useful features (many models desirable for their fast inference time are unable to learn arbitrary combinations of features  ... 
arXiv:1901.09090v2 fatcat:qdkutgv4gfegthn5hwlrx7foim

Vatican Policy in the Second World War and Those Responsible for the Second World War

1947 International Affairs  
This plan of the highest Catholic authorities in the U~ited States as of 1940, called for "the necessity of Government mtervention" in economic and social matters, according to a Fascist pattern; it also  ...  mment Ca~ olic prelates and laymen and has for 1~s subtitle: _An E~onomzc Program for the Unit.ed States,, applym~ P~pe 11 frtus XI s great Encyclical, 'Quadragesrmo Anno, on Sacral Life.  ...  The purge was carried out for both purposes according to the traditional methods of Jesuit strategy.  ... 
doi:10.2307/3017285 fatcat:vdf6ljwhhnaklnng4ncbewip5m

Classifying real-world data with the DDα-procedure [article]

Pavlo Mozharovskyi, Karl Mosler, Tatjana Lange
2015 arXiv   pre-print
The $DD\alpha$-classifier, a nonparametric fast and very robust procedure, is described and applied to fifty classification problems regarding a broad spectrum of real-world data.  ...  With the Tukey depth, which fits the distributions' shape best and is most robust, 'outsiders', that is data points having zero depth in all classes, need an additional treatment for classification.  ...  We are also grateful to Oleksii Pokotylo, master student at the National Technical University of Ukraine, for his help in preparation and maintaining the R-package ddalpha.  ... 
arXiv:1407.5185v2 fatcat:rsppu6vdv5grfjxocpwnzk2l6q
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