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35th AI 2022
- Iluju Kiringa, Sébastien Gambs:
35th Canadian Conference on Artificial Intelligence, Toronto, Ontario, Canada, May 30 - June 3, 2022. Canadian Artificial Intelligence Association 2022
Long papers
- Yang Xiang, Wanrong Sun:
Learning NAT-Modeled Bayesian Network Structures with Bayesian Approach. - Mansour Alqarni, Akramul Azim:
Low Level Source Code Vulnerability Detection Using Advanced BERT Language Model. - Mohammad Hamed Mozaffari, Yuchuan Li, Yoon Ko:
Detecting Flashover in a Room Fire based on the Sequence of Thermal Infrared Images using Convolutional Neural Networks. - Elham Parhizkar, Mohammad Hossein Nikravan, Robert C. Holte, Sandra Zilles:
Using Change Detection to Adapt to Dynamically Changing Trustees. - Colin Bellinger, Andriy Drozdyuk, Mark Crowley, Isaac Tamblyn:
Balancing Information with Observation Costs in Deep Reinforcement Learning. - Ci Lin, Tet Hin Yeap, Iluju Kiringa:
Stacked Bidirectional LSTM for Predicting Emission of Nitrous Oxide. - Dakota Soares, M. Ali Akber Dewan, Fuhua Oscar Lin:
A Hoeffding Decision Tree Based Approach for Soil Classification. - Mohammad Mehdi Afsar, Trafford Crump, Behrouz H. Far:
Sample Efficiency in Deep Reinforcement Learning based Recommender Systems with Imitation Learning. - Mahesh Ranaweera, Qusay H. Mahmoud:
Bridging Reality Gap Between Virtual and Physical Robot through Domain Randomization and Induced Noise. - Ali Abbasi Tadi, Luis Rueda, Dima Alhadidi:
NICASN: Non-negative Matrix Factorization and Independent Component Analysis for Clustering Social Networks. - Margaret H. McKay, Rene Richard:
Efficiency of Algorithmic Policing Tools: a nod to C.N. Parkinson. - Basile Tousside, Janis Mohr, Jörg Frochte:
Group and Exclusive Sparse Regularization-based Continual Learning of CNNs. - Xing Tan, Jimmy X. Huang, Kai Huang:
Complexity Analysis of Green Pickup-and-Delivery Problems on Ring Structures. - Jaël Champagne Gareau, Éric Beaudry, Vladimir Makarenkov:
Cache-Efficient Memory Representation of Markov Decision Processes. - Zhenyu A. Liao, Charupriya Sharma, Dongshu Luo, Peter van Beek:
An empirical study of scoring functions for learning Bayesian networks in model averaging. - Zhenyu Liao, Junyao Duan, Peter van Beek:
On identifying significant edges for structure learning in Bayesian networks. - Kiarash Zahirnia, Oliver Schulte, Ke Li, Ankita Sakhuja, Parmis Naddaf:
Deep Learning of Latent Edge Types from Relational Data. - Shainen M. Davidson, Vaibhav Kesarwani, Kenton White:
Forecasting and Understanding the 2021 Canadian Federal Election Using Twitter Conversations. - Vahid Reza Khazaie, Nicky Bayat, Yalda Mohsenzadeh:
Multi-Scale Identity-Preserving Image-to-Image Translation Network for Low-Resolution Face Recognition. - Shamir Khandaker, Aminul Islam:
Binary Classification with Minimum Observations. - Margaret H. McKay:
AI Transparency in a Real-World Context: What we can learn from past examples of algorithmic and statistical decision-making. - Dogan Altan, Mohammad Etemad, Dusica Marijan, Tetyana Kholodna:
Discovering Gateway Ports in Maritime Using Temporal Graph Neural Network Port Classification. - Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan, Xiaodan Zhu:
Evaluating Explanation Correctness in Legal Decision Making. - Ayesha Khader, Hamid Sajjadi, Faezeh Ensan:
Contextual Query Expansion for Conducting Technology-Assisted Biomedical Reviews. - Duncan Clelland, Gabriel Murray:
Computational Models of Linguistic Alignment for Clustering Group Participants and Predicting Task Outcomes. - Zakary Georgis-Yap, Milos R. Popovic, Shehroz S. Khan:
Preictal-Interictal Classification for Seizure Prediction. - Md. Mahbub Alam, Luís Torgo:
A Clustering-based Approach for Predicting the Future Location of a Vessel. - Garima Malik, Mucahit Cevik, Swayami Bera, Savas Yildirim, Devang Parikh, Ayse Basar:
Software requirement specific entity extraction using transformer models. - Hirad Daneshvar, Reza Samavi:
Heterogeneous Patient Graph Embedding in Readmission Prediction. - Salma Elgendy, Mayar Attawiya, Omar Haridy, Ahmed Farag, Paula Branco:
DTEXNet: Artificial Intelligence-Based Combination Scheme for DDoS Attacks Detection. - Syed Rafayal, Mucahit Cevik, Derya Kici:
An empirical study on probabilistic forecasting for predicting city-wide electricity consumption. - David Meger, Jonathan Pearce:
Adaptive Confidence Calibration. - Frédéric Piedboeuf, Philippe Langlais:
A working model for textual Membership Query Synthesis. - David Beauchemin, Julien Laumonier, Yvan Le Ster, Marouane Yassine:
"FIJO": a French Insurance Soft Skill Detection Dataset. - Mahtab Sarvmaili, Riccardo Guidotti, Anna Monreale, Amílcar Soares, Zahra Sadeghi, Fosca Giannotti, Dino Pedreschi, Stan Matwin:
A Modularized Framework for Explaining Black Box Classifiers for Text Data. - Vincent Primpied, David Beauchemin, Richard Khoury:
Quantifying French Document Complexity.
Short papers
- Anthony Bilodeau, Renaud Bernatchez, Albert Michaud-Gagnon, Flavie Lavoie-Cardinal, Audrey Durand:
Contextual bandit optimization of super-resolution microscopy. - Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Theoretical Connection between Locally Linear Embedding, Factor Analysis, and Probabilistic PCA. - Lily Wadoux, Nelly Barbot, Jonathan Chevelu, Damien Lolive:
Voice Cloning Applied to Voice Disorders: a Study of Extreme Phonetic Content in Speaker Embeddings. - Mohammad Sajjad Ghaemi, Karl Grantham, Isaac Tamblyn, Yifeng Li, Hsu Kiang Ooi:
Generative Enriched Sequential Learning (ESL) Approach for Molecular Design via Augmented Domain Knowledge. - Fanny Rancourt, Diego Maupomé, Marie-Jean Meurs:
On the Influence of Annotation Quality in Suicidal Risk Assessment from Text. - Marc Queudot, Louis Marceau, Raouf Moncef Belbahar, Eric Charton, Marie-Jean Meurs:
Dataset Augmentation Using Back-Translation to Improve Early Stage Dialog Systems.
Graduate Student Symposium
- Yashar Tavakoli:
Classification of Moving Objects Under the Spatial-Spatiotemporal Taxonomy of Descriptor. - Pratik K. Mishra:
Automatic Detection of Behaviours of Risk in People with Dementia using Unsupervised Deep Learning. - Rodrigo Brandão:
Artificial intelligence, human oversight, and public policies: facial recognition systems in Brazilian cities. - Omid Tarkhaneh:
Deep Convolutional Neural Network for Molecular EnergyPrediction. - Nima Barani Lonbani:
Prediction of Host-Pathogen RNA Interaction From RNA Sequences and Dual RNA-seq Data using Variational Autoencoders and Supervised Machine Learning Methods. - Shane Leonard:
Using Machine Learning Algorithms to Predict the Effects of Substituents on Molecular Properties and Structures.
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