Results 11 to 20 of about 8,233,255 (298)
Classification via an Embedded Approach [PDF]
Designs, 2017 This paper presents the results of an automated volatile organic compound (VOC) classification process implemented by embedding a machine learning algorithm into an Arduino Uno board.
José de Jesús Rubio +5 more
doaj +4 more sources
Glomerulus Classification via an Improved GoogLeNet [PDF]
IEEE Access, 2020 Glomerulosclerosis is a pathomorphological feature of glomerular lesions. Early detection, accurate judgement and effective prevention of the glomeruli is crucial not only for people with kidney disease, but also for the general population. We proposed a
Xujing Yao +4 more
doaj +3 more sources
Pattern classification via unsupervised learners [PDF]
We consider classification problems in a variant of the Probably Approximately Correct (PAC)-learning framework, in which an unsupervised learner creates a discriminant function over each class and observations are labeled by the learner returning the highest value associated with that observation.
Palmer, Nicholas James
openaire +4 more sources
Trading via selective classification [PDF]
Proceedings of the Second ACM International Conference on AI in Finance, 2021 (8 pages, 6 figures, 4 tables, ICAIF'21)
Nestoras Chalkidis, Rahul Savani
openaire +3 more sources
Text classification method review [PDF]
, 2007 With the explosion of information fuelled by the growth of the World Wide Web it is no longer feasible for a human observer to understand all the data coming in or even classify it into categories.
Tiwari, Ashutosh +3 more
core +7 more sources
Likelihood-free inference via classification. [PDF]
Stat Comput, 2018 Increasingly complex generative models are being used across disciplines as they allow for realistic characterization of data, but a common difficulty with them is the prohibitively large computational cost to evaluate the likelihood function and thus to perform likelihood-based statistical inference.
Gutmann MU +3 more
europepmc +10 more sources
Trading via image classification [PDF]
Proceedings of the First ACM International Conference on AI in Finance, 2020 The art of systematic financial trading evolved with an array of approaches, ranging from simple strategies to complex algorithms all relying, primary, on aspects of time-series analysis. Recently, after visiting the trading floor of a leading financial institution, we noticed that traders always execute their trade orders while observing images of ...
Naftali Cohen +2 more
openaire +4 more sources
Robust cross-network node classification via constrained graph mutual information
, 2022 Robust cross-network node classification via constrained graph mutual ...
J Jiang (9552179) +6 more
core +3 more sources
Robust Adversarial Classification via Abstaining [PDF]
2021 60th IEEE Conference on Decision and Control (CDC), 2021 In this work, we consider a binary classification problem and cast it into a binary hypothesis testing framework, where the observations can be perturbed by an adversary. To improve the adversarial robustness of a classifier, we include an abstain option, where the classifier abstains from making a decision when it has low confidence about the ...
Abed AlRahman Al Makdah +2 more
openaire +2 more sources
Approximate Bayesian Computation via Classification
J. Mach. Learn. Res., 2021 Approximate Bayesian Computation (ABC) enables statistical inference in simulator-based models whose likelihoods are difficult to calculate but easy to simulate from. ABC constructs a kernel-type approximation to the posterior distribution through an accept/reject mechanism which compares summary statistics of real and simulated data.
Yuexi Wang +2 more
openaire +4 more sources