Results 311 to 320 of about 2,151,300 (377)

Extreme fire severity interacts with seed traits to moderate post‐fire species assemblages

American Journal of Botany, EarlyView.
Abstract Premise Climate change is globally pushing fire regimes to new extremes, with unprecedented large‐scale severe fires. Persistent soil seed banks are a key mechanism for plant species recovery after fires, but extreme fire severity may generate soil temperatures beyond thresholds seeds are adapted to.
Michi Sano, Ryan Tangney, Alexandria Thomsen, Mark K. J. Ooi   +3 more
wiley   +1 more source

Broadcast Channel Cooperative Gain: An Operational Interpretation of Partial Information Decomposition. [PDF]

Entropy (Basel)
Tian C, Shamai Shitz S.
europepmc   +1 more source

Phragmén's voting methods and justified representation. [PDF]

Math Program
Brill M, Freeman R, Janson S, Lackner M.
europepmc   +1 more source

Multi-attribute decision-making method based on complex T-spherical fuzzy frank prioritized aggregation operators. [PDF]

Heliyon
Rizwan Khan M, Ullah K, Raza A, Senapati T, Moslem S.   +4 more
europepmc   +1 more source

Classification of artificial intelligence tools for civil engineering under the notion of complex fuzzy rough Frank aggregation operators. [PDF]

Sci Rep
Emam W, Ahmmad J, Mahmood T, Ur Rehman U, Yin S.   +4 more
europepmc   +1 more source

Discussion comments on "Exponentiated Teissier distribution with increasing, decreasing and bathtub hazard functions". [PDF]

J Appl Stat
Sharma VK, Singh SV, Shekhawat K.
europepmc   +1 more source

User-Perceived Capacity: Theory, Computation, and Achievable Policies. [PDF]

Entropy (Basel)
Liu Y, Zhao X, Chen W.
europepmc   +1 more source

Weighted nonnegative tensor factorization: on monotonicity of multiplicative update rules and application to user-guided audio source separation

, 2013
Alexey Ozerov, Ngoc Q. K. Duong, Louis Chevallier   +2 more
openalex   +1 more source

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Rule learning with monotonicity constraints

Proceedings of the 26th Annual International Conference on Machine Learning, 2009
In classification with monotonicity constraints, it is assumed that the class label should increase with increasing values on the attributes. In this paper we aim at formalizing the approach to learning with monotonicity constraints from statistical point of view.
W. Kotłowski, R. Słowiński
semanticscholar   +3 more sources