Pages that link to "Item:Q2753374"
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The following pages link to Bioinformatics. The machine learning approach. (Q2753374):
Displaying 50 items.
- Direct importance estimation for covariate shift adaptation (Q144623) (← links)
- Multi-criterion Pareto based particle swarm optimized polynomial neural network for classification: a review and state-of-the-art (Q458473) (← links)
- Self-organizing hidden Markov model map (SOHMMM) (Q460684) (← links)
- The complete realization problem for hidden Markov models: a survey and some new results (Q661032) (← links)
- Data mining in bioinformatics (Q704866) (← links)
- Newtonian clustering: an approach based on molecular dynamics and global optimization (Q877118) (← links)
- Dimensionality reduction and topographic mapping of binary tensors (Q903112) (← links)
- Through a barn owl's eyes: interactions between scene content and visual attention (Q936109) (← links)
- Probabilistic modelling in bioinformatics and medical informatics. (Q945948) (← links)
- On statistically meaningful geometric properties of digital three-dimensional structures of proteins (Q949527) (← links)
- Semi-supervised speaker identification under covariate shift (Q985576) (← links)
- On comparing two sequences of numbers and its applications to clustering analysis (Q1006752) (← links)
- Protein secondary structure prediction using three neural networks and a segmental semi-Markov model (Q1010247) (← links)
- Entropy of hidden Markov processes via cycle expansion (Q1012654) (← links)
- The evolution of stochastic regular motifs for protein sequences (Q1396010) (← links)
- Chaos automata: iterated function systems with memory (Q1396638) (← links)
- A discrete autoregressive process as a model for short-range correlations in DNA sequences (Q1407987) (← links)
- Statistical challenges in functional genomics. (With comments and a rejoinder). (Q1431220) (← links)
- Bayesian predictiveness, exchangeability and sufficientness in bacterial taxonomy (Q1602623) (← links)
- On the state of the art in machine learning: A personal review (Q1606331) (← links)
- Physics and chemistry-driven artificial neural network for predicting bioactivity of peptides and proteins and their design (Q1617368) (← links)
- Membership-margin based feature selection for mixed type and high-dimensional data: theory and applications (Q1750036) (← links)
- Of bits and wows: a Bayesian theory of surprise with applications to attention (Q1784575) (← links)
- Analysis of the IJCNN 2007 agnostic learning vs. prior knowledge challenge (Q1932020) (← links)
- Pool-based active learning in approximate linear regression (Q1959485) (← links)
- A perceptually optimised bivariate visualisation scheme for high-dimensional fold-change data (Q2036175) (← links)
- A comprehensive survey and analysis of generative models in machine learning (Q2065961) (← links)
- Learning probabilistic automata using residuals (Q2119983) (← links)
- Statistical mechanical modeling of a DNA nanobiostructure at the base-pair level (Q2156628) (← links)
- The measure on the original space from a product measure (Q2195186) (← links)
- Statistical modelling and machine learning principles for bioinformatics techniques, tools, and applications (Q2212833) (← links)
- Network exploration via the adaptive LASSO and SCAD penalties (Q2270657) (← links)
- Unsupervised empirical Bayesian multiple testing with external covariates (Q2271346) (← links)
- The Baum-Welch algorithm with limiting distribution constraints (Q2294238) (← links)
- Techniques for dealing with incomplete data: a tutorial and survey (Q2337405) (← links)
- Design principles for inductive inference procedures (Q2371720) (← links)
- Discriminating membrane proteins using the joint distribution of length sums of success and failure runs (Q2404624) (← links)
- Predicting protein secondary structure based on Bayesian classification procedures on Markovian chains (Q2458044) (← links)
- On a 3D-matrix representation of the tertiary structure of a protein (Q2473220) (← links)
- Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms (Q2485074) (← links)
- Connectionist computations of intuitionistic reasoning (Q2503271) (← links)
- Bioinformatics: organisms from Venus, technology from Jupiter, algorithms from Mars (Q2512284) (← links)
- Double linear regressions for single labeled image per person face recognition (Q2629788) (← links)
- On Binomial Observations of Continuous-Time Markovian Population Models (Q2949848) (← links)
- Learning the Language of Biological Sequences (Q2963599) (← links)
- Machine Learning Approaches to Bioinformatics (Q3405495) (← links)
- NONLINEAR TIME SERIES PREDICTION BASED ON A POWER-LAW NOISE MODEL (Q3532382) (← links)
- Rough-Fuzzy Granular Computing, Case Based Reasoning and Data Mining (Q3593172) (← links)
- A new efficient statistical test for detecting variability in the gene expression data (Q3597114) (← links)
- Optimal instruments and models for noisy chaos (Q3636695) (← links)
