Program
Preliminary Program
Tuesday 12 May: Graduate Student Symposium, Tutorials
Wednesday 13 May: Main conference day 1, one keynote speaker, oral and poster sessions
Thursday 14 May: Main conference day 2, one keynote speaker, oral and poster sessions
Friday 15 May: Main conference day 3, one keynote speaker, oral and poster sessions, closing remarks
More details are forthcoming.
Accepted Papers for the Conference
Full Papers
A deeper look at Bongard Problems
Anomaly Detection and Prototype Selection Using Polyhedron Curvature
Wise Sliding Window Segmentation: A classification-aided approach for trajectory segmentation
Mixing ICI and CSI Models for More Efficient Probabilistic Inference
Locating influential agents in social networks: Budget-constrained seed set selection
Unsupervised Monocular Depth Estimation CNN Robust to Training Data Diversity
An Energy-Efficient Method with Dynamic GPS Sampling Rate for Transport Mode Detection and Trip Reconstruction
Automatic Polyp Segmentation Using Convolutional Neural Networks
VecHGrad for solving accurately tensor decomposition
Sensitivity to risk profiles of users when developing AI systems
Topological Data Analysis for Arrhythmia Detection through Modular Neural Networks
A Deep Neural Network for Counting the Number of Vessels using Sonar Signals
Big Players: Emotion in Twitter Communities Tweeting about Global Warming
Improving classification using topic correlation and Expectation Propagation
Using Deep Reinforcement Learning Methods for Autonomous Vessels in 2D Environments
Empirical Confidence Models for Supervised Machine Learning
Reinforcement Learning in a Physics-Inspired Semi-Markov Environment
Adversarial Models for Deterministic Finite Automata
Exploring Deep Anomaly Detection Methods Based on Capsule Net
Attending knowledge facts with BERT-like models in Question-Answering : disappointing results and some explanations
Classification of Rare Recipes Requires Linguistic Features as Special Ingredients
FASTT: Team formation using fair division
Amalgamated Models for Detecting Duplicate Bug Reports
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Network
Investigating Citation Linkage as a Sentence Similarity Measurement Task using Deep Learning
A Scheme for Generating A Dataset for Anomalous Activity Detection in Internet of Things
Incremental Sequential Rule Mining with Streaming Input Traces
Forecasting Seat Counts in the 2019 Canadian Federal Election Using Twitter
Deep Multi Agent Reinforcement Learning for Autonomous Driving
Question-Worthy Sentence Selection for Question Generation
Predicting the Number of Reported Bugs in a Software Repository
Short Papers
A Cost Skew Aware Predictive System for Chest Drain Management
Personalized Multi-Faceted Trust Modeling in Social Networks
RideSafe: Detecting Sexual Harassment in Rideshares
Happiness Analysis with Fisher information of Dirichlet-multinomial mixture model
Adapting Ensemble Neural Networks to Clinical Prediction in High-Dimensional Settings
Selection Driven Query Focused Abstractive Document Summarization
Lexical Data Augmentation for Text Classification in Deep Learning
Evaluation of A Failure Prediction Model for Large Scale Cloud Applications
Investigating Relational Recurrent Neural Networks with Variable Length Memory Pointer in Sentence Pair Modelling Tasks
Query Focused Abstractive Summarization via Incorporating Query Relevance and Transfer Learning with Transformer Models
Similarity Matching of Temporal Event-Interval Sequences
Machine Learning the Donor Journey
Ethical Requirements for AI Systems
Challenges in vessel behavior and anomaly detection: from classical machine learning to deep learning
Seed Lexicons, Word Representations, Mapping Procedure, and Evaluation Lists: What Matters in Bilingual Lexicon Induction from Comparable Corpora?
The K-Closest Resemblance Classifier for remote sensing data sets
CB-DBSCAN: A Novel Clustering Algorithm for Adjacent Clusters with Different Densities
Detection and Diagnosis of Breast Cancer Using a Bayesian Approach
Partial Label Learning by Entropy Minimization
Customer Segmentation And Churn Prediction In Online Retail
Low-dimensional dynamics of encoding and learning in recurrent neural networks
Using Topic Modelling to Improve Prediction of Financial Report Commentary Classes
Augmented Out-of-sample Comparison Method for Time Series Forecasting Techniques
From Explicit to Implicit Entity Linking: A Learn to Rank Framework
