A Competitive Strategy for Function Approximation in Q-Learning

A Fast Dual Projected Newton Method for L1-Regularized Least Squares

A Framework for Incorporating General Domain Knowledge into Latent Dirichlet Allocation using First-Order Logic

A general MCMC method for Bayesian inference in logic-based probabilistic modeling

A Hidden Markov Model variant for sequence classification

Active online classification via information maximization

Active Surveying: A Probabilistic Approach for Identifying Key Opinion Leaders

Activity Recognition with Finite State Machines

Adaptation of a mixture of multivariate Bernoulli distributions

Agent-oriented incremental activity recognition for human teams

An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics

Angular Decomposition

Approximation-Guided Evolutionary Multi-Objective Optimization

Automatic State Abstraction from Demonstration

Ball Ranking Machine for Content-Based Multimedia Retrieval

Bayesian Policy Search with Policy Priors

Bi-Weighting Domain Adaptation for Cross-Language Text Classification

Biclustering-Driven Ensemble of Bayesian Belief Network Classifiers for Underdetermined Problems

Classification of Emerging Extreme Event Tracks in Multi-Variate Spatio-Temporal Physical Systems Using Dynamic Network Structures: Application to Hurricane Track Prediction

Cluster Indicator Decomposition for Efficient Matrix Factorization

Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding

Concept Labeling: Building Text Classifiers with Minimal Supervision

Consistency Measures for Feature Selection

Constituent Grammatical Evolution

Continuous Correlated Beta Processes

Dealing with Concept Drift and Class Imbalance in Multi-label Stream Classification

Discerning Linkage-Based Algorithms Among Hierarchical Clustering Methods

Discovering deformable shape templates in continuous time-series data

Distance Metric Learning Under Covariate Shift

Distribution-Aware Online Classifiers

Diversity Regularized Machine

Domain Adaptation with Ensemble of Feature Groups

Extracting temporal patterns from interval-based sequences

Fast Anomaly Detection for Streaming Data

Fast Approximate Nearest-Neighbor Search using k-Nearest Neighbor Graph

Fast Nonnegative Matrix Tri-Factorization for Large-Scale Data Co-Clustering

Feature Selection via Joint Embedding Learning and Sparse Regression

Flexible, High Performance Convolutional Neural Networks for Image Classification

Gaussianity Measures for Detecting the Direction of Causal Time Series

Generative Structure Learning for Markov Logic Network Based on Graph of Predicates

Heterogeneous Domain Adaptation using Manifold Alignment

Heuristic Rule-Based Regression via Dynamic Reduction to Classification

Imitation Learning in Relational Words: A Functional Gradient Boosting Approach

Improving performance of topic models by variable grouping

Increasing the Scalability of the Fitting of Generalised Block Models for Social Networks

Incremental Slow Feature Analysis

Integrating Task Planning and Interactive Learning for Robots to Work in Human Environments

Joint Feature Selection and Subspace Learning

Jointly Learning Data-Dependent Label and Locality-Preserving Projections

Kernel-based Selective Ensemble Learning for Streams of Trees

Kinship Verification through Transfer Learning

L21-Norm Regularized Discriminative Feature Selection for Unsupervised Learning

Learning a Distance Metric by Empirical Loss Minimization

Learning Decision Rules from Data Streams

Learning Driving Behavior By Timed Syntactic Pattern Recognition

Learning Hash Functions for Cross-View Similarity Search

Learning to Rank under Multiple Annotators

LIFT: Multi-Label Learning with Label-Specific Features

Local and Structural Consistency for Multi-manifold Clustering

Locality-constrained Concept Factorization

Matrix Co-Factorization on Compressed Sensing

Modular Community Detection in Networks

Multi-Evidence Lifted Message Passing

Multi-Kernel Gaussian Processes

Multi-kernel Multi-Label Learning with Max-Margin Concept Network

Multi-label Classification using Conditional Dependency Networks

On Trivial Solution and Scale Transfer Problems in Graph Regularized NMF

Pattern Field Classification with Style Normalized Transformation

Positive Unlabeled Leaning for Time Series Classification

Principal Component Analysis with Non-Greedy L1-Norm Maximization

Probit Classifiers with a Generalized Gaussian Scale Mixture Prior

Q-error as a Selection Mechanism in Modular Reinforcement-Learning Systems

Revisiting Numerical Pattern Mining with Formal Concept Analysis

Semi-supervised learning from a translation model between data distributions

Similarity-Based Approach for Positive and Unlabeled learning

Simulation-based Data Mining Solution to the Structure of Water Surrounding Proteins

Strategy Learning for Autonomous Agents in Smart Grid Markets

Unsupervised Grammar Learning with a Curriculum

Unsupervised Learning of Patterns in Data Streams using Compression and Edit Distance

Using Cases as Heuristics in Reinforcement Learning: a Transfer Learning application

Utility-based Fraud Detection