[PDF] Top 20 On learning discontinuous dependencies from positive data
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On learning discontinuous dependencies from positive data
... symbolic learning, positive results are known exclusively for projective DGs: Moreau (2001), Besombes and Marion (2001), Bechet ...DGs from positive ...unlearnability from strings of ... Voir le document complet
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Learning spatiotemporal trajectories from manifold-valued longitudinal data
... missing data z knowing y and θ (t) , denoted by q(z | y, θ (t) ...us from resorting to sampling methods as in [10] as they would require heavy computations, such as the Fisher information ... Voir le document complet
10
Learning from positive and unlabeled examples in biology
... PU LEARNING negative examples turn out to be less accurate and very sensitive to the prior identification ...unlabeled data available in many situations are still under-exploited and that PU learning ... Voir le document complet
143
Learning from biomedical linked data to suggest valid pharmacogenes
... of data, i.e., data about one gene–drug pair is represented in the feature matrix by several lines ...more data about pos- itive examples than data about negatives, it results that if we ... Voir le document complet
13
Discovery of "Interesting" Data Dependencies from a Workload of SQL Statements
... properties from current biological data? In both cases the answer is ...results. From the point of view of the water quality domain, some insight has been gained in the interdependencies of ... Voir le document complet
10
ProDiGe: PRioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples
... and data mining ...the data they use to perform gene ...machine learning techniques to integrate heterogeneous information and rank the candidate genes by decreasing similarity to known disease ... Voir le document complet
22
Grand challenges in altmetrics : heterogeneity, data quality and dependencies
... different from saving it to a reference manager and blogging about a dataset differs from tweeting it (Taylor, ...derived from these ...high positive correlations were found between citations ... Voir le document complet
9
Learning Rules from Multisource Data for Cardiac Monitoring
... The hypotheses in H are searched in a so-called hypothesis space. A gener- alization relation, usually the θ-subsumption [7], can be defined on hypotheses. This relation induces a lattice structure on L H which enables ... Voir le document complet
11
Learning From Missing Data Using Selection Bias in Movie Recommendation
... significant positive association between the rating of items in a given population and the natural propensity of this population to select these ...extrapolated from the popu- lation of users that are ... Voir le document complet
12
Operator-valued Kernels for Learning from Functional Response Data
... machine learning problems such as collaborative filtering (Abernethy et ...context, learning the operator- valued kernel would be interesting to find the right model of dependencies between ... Voir le document complet
55
Positive and unlabeled learning in categorical data
... both positive and negative ex- amples in training data is needed to build an efficient ...learn from Posi- tive and Unlabeled (PU) ...PU learning approach for categorical data: ...the ... Voir le document complet
25
Multiple instance learning for sequence data with across bag dependencies
... S4 7670 93.5 Both ABClass and ABSim approaches provide good overall accuracy results compared to those obtained using the naive approach (see Figure 3). This shows that our proposed approaches are efficient. The results ... Voir le document complet
16
Learning Lexicographic Preference Trees From Positive Examples
... of learning the preferences of users on a combinatorial set of alternatives, as it can be the case for example with online ...of positive examples of alternatives that have been selected during past ...of ... Voir le document complet
9
Logical time at work: capturing data dependencies and platform constraints
... the data-flow languages, use a component-based approach for specifying the functionality of a ...of data (“tokens”) from its input ports and produces a fixed amount of data on its output ... Voir le document complet
9
Learning spatio-temporal trajectories from manifold-valued longitudinal data
... • Longitudinal measurements sometimes belong to Riemannian manifolds (non-Euclidean spaces). ⟹ statistical models for such longitudinal data should be defined for manifold-valued measurements. Linear mixed-effects ... Voir le document complet
2
Fuzzy Rule Learning for Material Classification from Imprecise Data
... We tested existing algorithms and adapted them to the fuzzy case by the use of dissimilarities between distributions able to take into account the whole distri- bution of the data and not only an aggregated value. ... Voir le document complet
13
The Big Data Newsvendor: Practical Insights from Machine Learning
... Our data comes from the emergency room of a large UK teaching hospital from July 2008 to June ...The data include the total number of patients in the emergency room at 2-hour ...the ... Voir le document complet
35
Online learning of acyclic conditional preference networks from noisy data
... online learning of acyclic Conditional Preference networks (CP-nets) from data streams, possibly cor- rupted with ...corrupted data in a principled way, and on (ii) the Hoeffding bound to ... Voir le document complet
10
Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data
... [3] Schiratti, Allassonniere, Colliot, and Durrleman, Learning spatiotemporal trajectories from manifold-valued longitudinal data, Neural Information Processing Systems 28, 2015. [4] Therasse, ... Voir le document complet
2
The Big Data Newsvendor: Practical Insights from Machine Learning Analysis
... “big data” (p/n = O(1)) as well as small data (p/n = ...small data, we provide a linear programming machine learning algorithm that yields an asymptotically optimal order ...big data, ... Voir le document complet
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