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Subjects / keywords: Computer science; Mathematics; Set theory; Problems, exercises, etc; Algorithms; Logic, Symbolic and mathematical; Problems and exercises; Electronic books

Subjects / keywords: Local optimum; Algorithm; Mathematical optimization; Trigonometric functions; Optimization problem; Convergence (economics); Mathematics; Sine; Set (abstract data type); Global optimization; Computer science; Economics

Subjects / keywords: Whale; Optimization algorithm; Meta heuristic; Computer science; Mathematical optimization; Heuristic; Algorithm; Artificial intelligence; Mathematics; Fishery; Biology

The popular Q-learning algorithm is known to overestimate action values under certain conditions. It was not previously known whether, in practice, such overestimations are common, whether they harm performance, and whet...

Subjects / keywords: Residual; Computer science; Convergence (economics); Residual neural network; Block (permutation group theory); Identity (music); Generalization; Code (set theory); Algorithm; Layer (electronics); Theoretical computer sc...

Least-squares means are predictions from a linear model, or averages thereof. They are useful in the analysis of experimental data for summarizing the effects of factors, and for testing linear contrasts among prediction...

Subjects / keywords: Monte Carlo tree search; Computer science; Champion; Artificial neural network; Reinforcement learning; Artificial intelligence; Game tree; Value (mathematics); Search algorithm; Tree (set theory); Deep neural networks; ...

Subjects / keywords: Laptop; RNA-Seq; Computer science; Bottleneck; Probabilistic logic; RNA; Computational biology; Algorithm; Artificial intelligence; Biology; Genetics; Gene

Subjects / keywords: TREMBLAY, JEAN-PAUL; MCGRAW-HILL; 005.113 T789in

Subjects / keywords: Python (Computer program language); Data structures (Computer science); Computer algorithms

Subjects / keywords: Text processing (Computer science); Genetic algorithms; Computational linguistics

Subjects / keywords: Computer algorithms; Databases; Data structures (Computer science); Structured programming

State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced the running time of these detection networks, expo...

TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. Tensor-Flow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. ...

BACKGROUND: VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to...

Tree boosting is a highly effective and widely used machine learning method. In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-...

Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progres...