The following pages link to UCI-ml (Q16261):
Displaying 50 items.
- Nonparametric estimation of the measure of functional dependence (Q2142917) (← links)
- A robust deterministic affine-equivariant algorithm for multivariate location and scatter (Q2142999) (← links)
- Adaptive primal-dual stochastic gradient method for expectation-constrained convex stochastic programs (Q2146450) (← links)
- Ranking with submodular functions on a budget (Q2147409) (← links)
- An opinion formation based binary optimization approach for feature selection (Q2148602) (← links)
- Sampling Kaczmarz-Motzkin method for linear feasibility problems: generalization and acceleration (Q2149567) (← links)
- Knowledge cores in large formal contexts (Q2149803) (← links)
- Robust covariance estimation for distributed principal component analysis (Q2150893) (← links)
- Inversion-free subsampling Newton's method for large sample logistic regression (Q2151694) (← links)
- An integrated local depth measure (Q2151990) (← links)
- A biased least squares support vector machine based on Mahalanobis distance for PU learning (Q2153189) (← links)
- Enhanced prediction of anti-tubercular peptides from sequence information using divergence measure-based intuitionistic fuzzy-rough feature selection (Q2157067) (← links)
- A stochastic subgradient method for distributionally robust non-convex and non-smooth learning (Q2159458) (← links)
- Hybrid semiparametric Bayesian networks (Q2161014) (← links)
- An extended delayed weighted gradient algorithm for solving strongly convex optimization problems (Q2161068) (← links)
- Estimating parameters of mixtures of multivariate \(t\)-populations and application to classification of observations (Q2161073) (← links)
- FOLD-R++: a scalable toolset for automated inductive learning of default theories from mixed data (Q2163174) (← links)
- A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning (Q2163207) (← links)
- Embedding and extraction of knowledge in tree ensemble classifiers (Q2163234) (← links)
- JGPR: a computationally efficient multi-target Gaussian process regression algorithm (Q2163240) (← links)
- The backbone method for ultra-high dimensional sparse machine learning (Q2163249) (← links)
- Verification of classification model and dendritic neuron model based on machine learning (Q2163605) (← links)
- Least squares approach to K-SVCR multi-class classification with its applications (Q2163855) (← links)
- Two-sample test for equal distributions in separate metric space: New maximum mean discrepancy based approaches (Q2169833) (← links)
- Shattering inequalities for learning optimal decision trees (Q2170186) (← links)
- Leveraging integer linear programming to learn optimal fair rule lists (Q2170192) (← links)
- Conclusive local interpretation rules for random forests (Q2172632) (← links)
- Robust support vector regression with generic quadratic nonconvex \(\varepsilon\)-insensitive loss (Q2174697) (← links)
- A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics (Q2174980) (← links)
- Comparing clusterings using combination of the kappa statistic and entropy-based measure (Q2175381) (← links)
- Accelerated sampling Kaczmarz Motzkin algorithm for the linear feasibility problem (Q2176283) (← links)
- Envelope-based sparse partial least squares (Q2176612) (← links)
- Interface between logical analysis of data and formal concept analysis (Q2178106) (← links)
- Profit driven decision trees for churn prediction (Q2178124) (← links)
- Subsampled nonmonotone spectral gradient methods (Q2178981) (← links)
- ASD+M: automatic parameter tuning in stochastic optimization and on-line learning (Q2179079) (← links)
- Robust spike-train learning in spike-event based weight update (Q2179081) (← links)
- Kernel Bayesian ART and ARTMAP (Q2179293) (← links)
- Merging weighted SVMs for parallel incremental learning (Q2179798) (← links)
- Laplacian-optimized diffusion for semi-supervised learning (Q2180649) (← links)
- Testing for independence of high-dimensional variables: \(\rho V\)-coefficient based approach (Q2181735) (← links)
- Subset selection for multiple linear regression via optimization (Q2182858) (← links)
- Scalable holistic linear regression (Q2183189) (← links)
- Modified hybrid discriminant analysis methods and their applications in machine learning (Q2183236) (← links)
- Joint consensus and diversity for multi-view semi-supervised classification (Q2183582) (← links)
- Data clustering based on principal curves (Q2183657) (← links)
- How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models (Q2183660) (← links)
- Optimal arrangements of hyperplanes for SVM-based multiclass classification (Q2183661) (← links)
- Optimizing predictive precision in imbalanced datasets for actionable revenue change prediction (Q2184072) (← links)
- Tightening big Ms in integer programming formulations for support vector machines with ramp loss (Q2184093) (← links)
