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Machine Learning （ML） - April 2017, issue 4 论文列表

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卷期号： April 2017, issue 4
发布时间：
卷期年份： 2017
卷期官网： https://link.springer.com/journal/10994/volumes-and-issues/106-4
本期论文列表
Introduction: special issue of selected papers from ACML 2015

Class-prior estimation for learning from positive and unlabeled data

Geometry-aware principal component analysis for symmetric positive definite matrices

Preference Relation-based Markov Random Fields for Recommender Systems

Erratum to: Preference Relation-based Markov Random Fields for Recommender Systems

Surrogate regret bounds for generalized classification performance metrics

Maximum margin partial label learning

Proximal average approximated incremental gradient descent for composite penalty regularized empirical risk minimization

Introduction to the special issue on dynamic networks and knowledge discovery

Scalable computational techniques for centrality metrics on temporally detailed social network

Exceptional contextual subgraph mining

Tiles: an online algorithm for community discovery in dynamic social networks

Special issue on inductive logic programming

Relational data factorization

Planning in hybrid relational MDPs

kProbLog: an algebraic Prolog for machine learning

Soft quantification in statistical relational learning

Fast rates by transferring from auxiliary hypotheses

On the use of stochastic local search techniques to revise first-order logic theories from examples

An empirical study of on-line models for relational data streams

Boosted multivariate trees for longitudinal data

Adaptive edge weighting for graph-based learning algorithms

Improving probabilistic inference in graphical models with determinism and cycles

Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors

Generalization bounds for non-stationary mixing processes

Optimal learning with Bernstein online aggregation

A family of admissible heuristics for A* to perform inference in probabilistic classifier chains

Feature-weighted clustering with inner product induced norm based dissimilarity measures: an optimization perspective

Projected estimators for robust semi-supervised classification

Homotopy continuation approaches for robust SV classification and regression

Optimal classification trees

The mechanism of additive composition

Special issue on discovery science

Multi-label classification via multi-target regression on data streams

Stream-based semi-supervised learning for recommender systems

Memory-adaptive high utility sequential pattern mining over data streams

Big Data: from collection to visualization

High-probability minimax probability machines

An evaluation of linear and non-linear models of expressive dynamics in classical piano and symphonic music

Confidence curves: an alternative to null hypothesis significance testing for the comparison of classifiers

QCC: a novel clustering algorithm based on Quasi-Cluster Centers

Nearest neighbors distance ratio open-set classifier

Hierarchical Dirichlet scaling process

Online optimization for max-norm regularization

Foreword: special issue for the journal track of the 8th Asian conference on machine learning (ACML 2016)

A unified probabilistic framework for robust manifold learning and embedding

Collaborative topic regression for online recommender systems: an online and Bayesian approach

Progressive random k-labelsets for cost-sensitive multi-label classification

Non-redundant multiple clustering by nonnegative matrix factorization

Multi-view kernel completion

Asymptotic properties of Turing’s formula in relative error

A Bayesian nonparametric model for multi-label learning

Statistical comparison of classifiers through Bayesian hierarchical modelling

A note on model selection for small sample regression

Introduction to the special issue dedicated to the Journal Track of ECML PKDD 2017

Learning deep kernels in the space of dot product polynomials

Gaussian conditional random fields extended for directed graphs

Efficient parameter learning of Bayesian network classifiers

Vine copulas for mixed data : multi-view clustering for mixed data beyond meta-Gaussian dependencies

Graph-based predictable feature analysis

A constrained \(\ell \)1 minimization approach for estimating multiple sparse Gaussian or nonparanormal graphical models

Varying-coefficient models for geospatial transfer learning

Learning constraints in spreadsheets and tabular data

Adaptive random forests for evolving data stream classification

Constraint-based clustering selection

An expressive dissimilarity measure for relational clustering using neighbourhood trees

Weightless neural networks for open set recognition

Offline reinforcement learning with task hierarchies

Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction

Sparse probit linear mixed model

Robust regression using biased objectives

Preserving differential privacy in convolutional deep belief networks

Generalized exploration in policy search

Cost-sensitive label embedding for multi-label classification

Group online adaptive learning