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ORCID36th CANAI 2023: Montreal, QC, Canada
- Amílcar Soares, Farhana H. Zulkernine, Renata Dividino, Reihaneh Rabbany, Qiang Ye, David Beach, Karim Ali:
36th Canadian Conference on Artificial Intelligence, Canadian AI, CANAI 2023, Montreal, Canada, June 5-9, 2023, Proceedings. Canadian Artificial Intelligence Association 2023
Long papers
- Robert K. Helmeczi, Savas Yildirim, Mucahit Cevik, Sojin Lee:
Few shot learning approaches to essay scoring. - Mohammed Hassan, Mohamed Eid, Hossam Elnems, Eslam Ahmed, Ebraam Mesak, Paula Branco:
Detecting Malicious .NET Files Using CLR Header Features and Machine Learning. - Christian Nordahl, Veselka Boeva, Håkan Grahn:
MultiStream EvolveCluster. - Raian Rahman
, Rizvi Hasan, Abdullah Al Farhad, Md. Tahmid Rahman Laskar, Md. Hamjajul Ashmafee, Abu Raihan Mostofa Kamal:
ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short Summaries. - Md Mezbaur Rahman, Mohammed Saidul Islam, Md. Tahmid Rahman Laskar, Md Azam Hossain, Abu Raihan Mostofa Kamal:
Multihop Factual Claim Verification Using Natural Language Prompts. - Ericsson Chenebuah, Michel Nganbe, Alain Tchagang:
Target-learning the Latent Space of a Variational Autoencoder model for the Inverse Design of Stable Perovskites. - Sudipta Singha Roy, Robert E. Mercer, Souvik Kundu:
Personality Trait Detection using an Hierarchy of Tree-transformers and Graph Attention Network. - Stacey Taylor, Vlado Keselj:
Don't Worry Accountants, ChatGPT Won't Be Taking Your Job...Yet. - Hongzhi Zhang, Omair Shafiq:
Towards Improving Text Classification Tasks Based on Knowledge Graphs for Limited Labeled Data. - Mohammed Gasmallah, François Rivest, Farhana H. Zulkernine, Mélanie Breton:
Quantifying Path Smoothness in Video Object Tracking by Detection. - Melle Mendikowski, Benjamin Schindler, Thomas Schmid, Ralf Möller, Mattis Hartwig:
Improved Techniques for Training Tabular GANs Using Cramer's V Statistics. - Abder-Rahman Ali, Peng Guo, Anthony E. Samir:
Liver Segmentation in Ultrasound Images Using Self-Supervised Learning with Physics-inspired Augmentation and Global-Local Refinement. - Md. Al Maruf, Akramul Azim:
Optimizing DNNs Model Partitioning for Enhanced Performance on Edge Devices. - Gaurav Jariwala, Vlado Keselj:
Mimicking Electronic Gaming Machine Player Behavior Using Reinforcement Learning. - David Beauchemin, Richard Khoury:
RISC: Generating Realistic Synthetic Bilingual Insurance Contract. - Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos, Anna Norris, Kadence Meredith:
Upward Pass Semantics in Arithmetic Circuit Inference. - Louis Fortier-Dubois, Benjamin Leblanc, Gaël Letarte, François Laviolette, Pascal Germain:
PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations. - Valentin-Gabriel Soumah, Prashanth Rao, Philipp Eibl, Maite Taboada:
Radar de Parité: An NLP system to measure gender representation in French news stories. - Julien da Silva:
Looking the Part: The AI Zombie Problem and the Anti-Turing Test. - Gautam Vira, Samik Pal, Behdad Mansouri, Amirhossein Ghadami, Paula Branco:
TAVo: Tor Application Detection with Voting Critic. - Jonathan Winton, Francis Palma:
Improving Software Requirements Prioritization through the Lens of Constraint Satisfaction. - Tom Picherit, Louis-Philip Lampron, Michael Morin, Gabriel Caron-Guillemette, Jonathan Gaudreault:
Supervised recommendations of gas metal arc welding parameters. - Andrey Sobolevsky, Guillaume-Alexandre Bilodeau, Jinghui Cheng, Jin L. C. Guo:
GUILGET: GUI Layout GEneration with Transformer. - Muhammad Al-Digeil, Yuri Grinberg, Daniele Melati, Jens H. Schmid, Pavel Cheben, Siegfried Janz, Dan-Xia Xu:
PCA-Enhanced Autoencoders for Nonlinear Dimensionality Reduction in Low Data Regimes. - Paul Quinlan, Qingguo Li, Xiaodan Zhu:
Guided Learning of Human Sensor Models with Low-Level Grounding. - Paritosh Goyal, Chenyang Huang, Amine Trabelsi, Osmar Zaïane:
Exploring Preferential Label Smoothing for Neural Network-based Classifiers. - Michiel Dhont, Elena Tsiporkova:
Elucidating Transition State Behaviour from Mobility Data by Cascades of Markov Chains. - Ella Morgan, Christian Muise:
Learning to Recognize Reachable States from Visual Domains. - Garima Malik, Savas Yildirim, Mucahit Cevik, Ayse Bener:
An Empirical Study on Vagueness Detection in Privacy Policy Texts. - Ahmed Mabrouk:
Anomaly Detection and Explanation of Wind Turbine Main Bearings using Autoencoder and Bayesian Network Models.
Short papers
- Aaron Hunter, Richard Booth:
Joint Trust for Belief Revision. - Sepideh Nahali, Leila Safari, Alireza Khanteymoori, Hajer Ayadi, Jimmy X. Huang:
IsoGloVe: A New Count-based Graph Embedding Method based on Geodesic Distance. - Hang Hu, Hsu Kiang Ooi, Mohammad Sajjad Ghaemi, Anguang Hu:
Machine learning for the prediction of safe and biologically active organophosphorus molecules. - Davood Pirayesh Neghab, Mucahit Cevik, Ayse Basar:
Identifying the Factors Influencing IPO Underpricing using Explainable Machine Learning Techniques. - Ruikang Luo, François Rivest, Farhana H. Zulkernine:
I3D Light - A Simple Motion Information Stream for I3D. - Mahdi Mohammadizadeh, Arash Mozhdehi, Yani Ioannou, Xin Wang:
Meta-GCN: A Dynamically Weighted Loss Minimization Method for Dealing with the Data Imbalance in Graph Neural Networks. - Amirhossein Daneshpajouh, Megan Fowler, Kay C. Wiese:
Navitas/Optimus: A Novel Computational Tool for enhanced CRISPR/Cas Genome Editing. - Mohammad Al Ridhawi, Hussein Al Osman:
Stock Market Prediction from Sentiment and Financial Stock Data Using Machine Learning. - Maede Ashofteh Barabadi, Xiaodan Zhu, Wai-Yip Chan, Amber L. Simpson, Richard K. G. Do:
Parameter-Efficient Methods for Metastases Detection fromClinical Notes. - Jingjing Zheng, John Hawkin, Charles Robertson, Alexander J. M. Howse, Yuanzhu Chen, Xianta Jiang:
Unsupervised Financial Fraud Detection Using Low-rank Recovery.
Graduate Student Symposium
- Sharon Chee Yin Ho:
From Development to Dissemination: Social and Ethical Issues with Text-to-Image AI-Generated Art. - Emily Medema:
A Comprehensive Framework for the Development of Ethical Machine Learning in Medicine. - Xu Wang, Yuehan Qi:
A Communication-Efficient Protocol for Federated Learning in Energy Storage Systems. - Ali Ghaemmaghami:
Prediction of Sustaining Emerging Technology Terms Using Burst Detection and Deep Learning. - Kellin Pelrine:
Better Bridges Between Model and Real World. - Saeedeh Jamali:
An Explainable Deep Few-shot Network for Protein Family Classification. - Hamid Vosoughi:
Leveraging AI to investigate the impact of different research funding programs on research outcome. - Sazia Mahfuz:
An Empirical Analysis on Pattern Reconstruction for Optimal Storage of Wearable Sensor Data. - Mozhgan Salimiparsa:
Counterfactual Explanations for Rankings. - Callaghan Wilmott:
Exploring the Impact of Representation on Agent Learning. - Zachary Yang:
When does Continuous Learning for BERT make sense? - Vicky Kuo:
Machine Learning for Hotel Booking Cancellations Prediction. - Ruixin Song:
Network Analysis and Vessel Flow Prediction for Risk Assessment of Biological Invasion of Non-indigenous Aquatic Species. - Pratheeksha Nair:
Graph learning with programmatic weak supervision. - Daria Maltseva:
Heuristic Restart Methods for Optimal Surgery Scheduling. - Mateusz Ogrodowczyk, Joanna Kurczalska, Jakub Eichner, Adam Mickiewicz:
InDeSTra - system for interior design style transfer.
Industry Track
- Bahar Sateli, Fernanda Del Castillo, Rod Moshtagi:
Towards determining the criticality of AI applications: A model risk management perspective. - Dalia Shanshal:
Towards an Automated Framework of Root Cause Analysis in the Canadian Telecom Industry.
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