Advances in Artificial Intelligence : 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020, Ottawa, on, Canada, May 13-15, 2020, Proceedings

Advances in Artificial Intelligence : 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020, Ottawa, on, Canada, May 13-15, 2020, Proceedings / Cyril Goutte, Xiaodan Zhu (eds.).

This book constitutes the refereed proceedings of the 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020, which was planned to take place in Ottawa, ON, Canada. Due to the COVID-19 pandemic, however, it was held virtually during May 13-15, 2020. The 31 regular papers and 24 short...

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Bibliographic Details
Corporate Author: Canadian Conference on Artificial Intelligence Ottawa, Ont.
Other Authors: Goutte, Cyril, Zhu, Xiaodan
Format: eBook
Language:English
Published: Cham : Springer, 2020.
Series:Lecture notes in computer science ; 12109.
Lecture notes in computer science. Lecture notes in artificial intelligence.
LNCS sublibrary. Artificial intelligence.
Subjects:
Artificial intelligence > Congresses.
Artificial intelligence
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Online Access:Click for online access
Table of Contents:
  • Toward adversarial robustness by diversity in an ensemble of specialized deep neural networks
  • Locating influential agents in social networks : budget-constrained seed set selection
  • Investigating relational recurrent neural networks with variable length memory pointer
  • Unsupervised monocular depth estimation NN robust to training data diversity
  • The K-closest resemblance classifier for remote sensing data
  • Reinforcement learning in a physics-inspired semi-Markov environment
  • Deep multi agent reinforcement learning for autonomous driving
  • Incremental sequential rule mining with streaming input traces
  • FASTT : team formation using fair division
  • Empirical confidence models for supervised machine learning
  • Selection driven query focused abstractive document summarization
  • VecHGrad for solving accurately tensor decomposition
  • Sensitivity to risk prpofiles of users when developing AI systems
  • Forecasting seat counts in the 2019 Canadian Federal Election using Twitter
  • Adapting ensemble neural networks to clinical prediction in high-dimensional settings
  • A cost skew aware predictive system for chest drain management
  • Topological data analysis for arrhythmia detection through modular neural networks
  • Big players : emotion in Twitter communities tweeting about global warming
  • Using topic modelling to improve prediction of financial report commentary classes
  • Wise sliding window segmentation : a classification-aided approach for trajectory segmentation
  • Using deep reinforcement learning methods for autonomous vessels in 2D environments
  • CB-DBSCAN : a novel clustering algorithm for adjacent clusters with different densities
  • Anoaly detection and prototype selection using polyhedron curvature
  • Ethical requirements for AI systems
  • A deep neural network for counting vessels in sonar signals
  • Partial label learning by entropy minimization
  • Low-dimensional dynamics of encoding and learning in recurrent neural networks
  • From explicit to implicit entity linking : a learn to rank framework
  • Automatic polyp segmentation using convolutional neural networks
  • Augmented out-of-sample comparison method for time series forecasting techniques
  • Predicting the number of reported bugs in a software repository
  • Evaluation of a failure prediction model for large scale cloud applications
  • Customer segmentation and churn prediction in online retail
  • Detection and diagnosis of breast cancer using a Bayesian approach
  • Query focused abstractive summarization via incorporating query relevance and transfer learning with transformer models
  • Word representation, seed lexicons, mapping procedures, and reference lists : what matters in bilingual lexicon induction from comparable corpora?
  • Attending knowledge facts with BERT-like models in question-answering : disappointing results and some explanations
  • Machine learning the donor journey
  • Exploring deep anomaly detection methods based on capsule net
  • Question-worthy sentence selection for question generation
  • Challenges in vessel behavior and anomaly detection : from classical machine learning to deep learning
  • An energy-efficient method with dynamic GPS sampling rate for transport mode detection and trip reconstruction
  • Similarity matching of temporal event-interval sequences
  • Classification of rare recipes requires linguistic features as special ingredients
  • Happiness analysis with Fisher information of DIrichlet-multinomial mixture model
  • Personalized multi-faceted trust modeling in social networks
  • Mixing ICI and CSI models for more efficient probabilistic inference
  • RideSafe : detecthing sexual harassment in rideshares
  • Amalgamated models for detecting duplicate bug reports
  • Investigating citation linkage as a sentence similarity measurement task using deep learning
  • Improving classification using topic correlation and expectation propagation
  • A scheme for generating a dataset for anomalous activity detection in IoT networks
  • Lexical data augmentation for text classification in deep learning
  • A deeper look at Bongard problems
  • Adversarial models for deterministic finite automata
  • Personalized student attribute inference
  • Vehicle traffic estimation using weather and calendar data
  • Predicting aggressive responsive behaviour among people with dementia
  • Towards analyzing the sentiments in the fields of automobiles and real-estates with specific focus on Arabic online reviews.

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