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Image Anomaly Detection with Generative Adversarial Networks

Neural Article Pair Modeling for Wikipedia Sub-article Matching

Temporally Evolving Community Detection and Prediction in Content-Centric Networks

Image-to-Markup Generation via Paired Adversarial Learning

Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies

<bold>LinNet</bold>: Probabilistic Lineup Evaluation Through Network Embedding

Toward an Understanding of Adversarial Examples in Clinical Trials

Improving Emotion Detection with Sub-clip Boosting

Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery

ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector

Machine Learning for Targeted Assimilation of Satellite Data

Dynamic Hierarchies in Temporal Directed Networks

From Empirical Analysis to Public Policy: Evaluating Housing Systems for Homeless Youth

<sc>GridWatch</sc>: Sensor Placement and Anomaly Detection in the Electrical Grid

Risk-Averse Matchings over Uncertain Graph Databases

Discovering Groups of Signals in In-Vehicle Network Traces for Redundancy Detection and Functional Grouping

Incorporating Privileged Information to Unsupervised Anomaly Detection

Discovering Urban Travel Demands Through Dynamic Zone Correlation in Location-Based Social Networks

L1-Depth Revisited: A Robust Angle-Based Outlier Factor in High-Dimensional Space

Social-Affiliation Networks: Patterns and the <sc>SOAR</sc> Model

SPEEDING Up the Metabolism in E-commerce by Reinforcement Mechanism DESIGN

Discovering Bayesian Market Views for Intelligent Asset Allocation

Beyond Outlier Detection: <sc>LookOut</sc> for Pictorial Explanation

<sc>ONE-M</sc>: Modeling the Co-evolution of Opinions and Network Connections

Intent-Aware Audience Targeting for Ride-Hailing Service

<sc>ConOut</sc>: <sc>Con</sc>textual <sc>Out</sc>lier Detection with Multiple Contexts: Application to Ad Fraud

Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions

A Recurrent Neural Network Survival Model: Predicting Web User Return Time

Scalable and Interpretable One-Class SVMs with Deep Learning and Random Fourier Features

Semi-supervised Blockmodelling with Pairwise Guidance

Implicit Linking of Food Entities in Social Media

Group Anomaly Detection Using Deep Generative Models

Large-Scale Nonlinear Variable Selection via Kernel Random Features

A Practical Deep Online Ranking System in E-commerce Recommendation

Detecting Autism by Analyzing a Simulated Social Interaction

Fast and Provably Effective Multi-view Classification with Landmark-Based SVM

Helping Your Docker Images to Spread Based on Explainable Models

A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements

Nyström-SGD: Fast Learning of Kernel-Classifiers with Conditioned Stochastic Gradient Descent

ST-DenNetFus: A New Deep Learning Approach for Network Demand Prediction

Face-Cap: Image Captioning Using Facial Expression Analysis

Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds

On Optimizing Operational Efficiency in Storage Systems via Deep Reinforcement Learning

Pedestrian Trajectory Prediction with Structured Memory Hierarchies

Deep Learning Architecture Search by Neuro-Cell-Based Evolution with Function-Preserving Mutations

Automating Layout Synthesis with Constructive Preference Elicitation

Multiple Instance Learning with Bag-Level Randomized Trees

VC-Dimension Based Generalization Bounds for Relational Learning

Configuration of Industrial Automation Solutions Using Multi-relational Recommender Systems

One-Class Quantification

Robust Super-Level Set Estimation Using Gaussian Processes

Learning Cheap and Novel Flight Itineraries

Deep F-Measure Maximization in Multi-label Classification: A Comparative Study

Scalable Nonlinear AUC Maximization Methods

Towards Resource-Efficient Classifiers for Always-On Monitoring

Ordinal Label Proportions

Lambert Matrix Factorization

AWX: An Integrated Approach to Hierarchical-Multilabel Classification

Uncertainty Modelling in Deep Networks: Forecasting Short and Noisy Series

Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition

Clustering in the Presence of Concept Drift

Using Reinforcement Learning to Conceal Honeypot Functionality

MASAGA: A Linearly-Convergent Stochastic First-Order Method for Optimization on Manifolds

Flexible Inference for Cyberbully Incident Detection

Time Warp Invariant Dictionary Learning for Time Series Clustering: Application to Music Data Stream Analysis

Block CUR: Decomposing Matrices Using Groups of Columns

Solving the False Positives Problem in Fraud Prediction Using Automated Feature Engineering

How Your Supporters and Opponents Define Your Interestingness

<inline-formula><alternatives><tex-math>\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathtt{SpectralLeader}$$\end{document}</tex-math><inline-graphic></inline-graphic></alternatives></inline-formula>: Online Spectral Learning for Single Topic Models

Learning Tensor-Based Representations from Brain-Computer Interface Data for Cybersecurity

Efficient Decentralized Deep Learning by Dynamic Model Averaging

Online Learning of Weighted Relational Rules for Complex Event Recognition

Can We Assess Mental Health Through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation

Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems

Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees

AMIE: Automatic Monitoring of Indoor Exercises

Towards Efficient Forward Propagation on Resource-Constrained Systems

Online Feature Selection by Adaptive Sub-gradient Methods

Rough Set Theory as a Data Mining Technique: A Case Study in Epidemiology and Cancer Incidence Prediction

Auxiliary Guided Autoregressive Variational Autoencoders

Frame-Based Optimal Design

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies

Cooperative Multi-agent Policy Gradient

Hierarchical Active Learning with Proportion Feedback on Regions

Hypotensive Episode Prediction in ICUs via Observation Window Splitting

Parametric t-Distributed Stochastic Exemplar-Centered Embedding

An Efficient Algorithm for Computing Entropic Measures of Feature Subsets

Equipment Health Indicator Learning Using Deep Reinforcement Learning

Joint Autoencoders: A Flexible Meta-learning Framework

Anytime Subgroup Discovery in Numerical Domains with Guarantees

PBE: Driver Behavior Assessment Beyond Trajectory Profiling

Privacy Preserving Synthetic Data Release Using Deep Learning

Discovering Spatio-Temporal Latent Influence in Geographical Attention Dynamics

Accurate WiFi-Based Indoor Positioning with Continuous Location Sampling

On Finer Control of Information Flow in LSTMs

Mining Periodic Patterns with a MDL Criterion

Human Activity Recognition with Convolutional Neural Networks

MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes

Revisiting Conditional Functional Dependency Discovery: Splitting the “C” from the “FD”

Urban Sensing for Anomalous Event Detection: