Colin Bellinger

69 papers A* 4A 1B 7C 3Journal 33Unranked 21

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	Dynamic Activation and Assignment of SDN Controllers in LEO Satellite Constellations. PIMRC Wafa Hasanain, Pablo G. Madoery, Halim Yanikomeroglu, Gunes Karabulut Kurt, Sameera Siddiqui, Stephane Martel, Khaled Ahmed, Colin Bellinger
2025	J	`jnl`	Dynamic Activation and Assignment of SDN Controllers in LEO Satellite Constellations. CoRR Wafa Hasanain, Pablo G. Madoery, Halim Yanikomeroglu, Gunes Karabulut Kurt, Sameera Siddiqui, Stephane Martel, Khaled Ahmed, Colin Bellinger
2025	—	`conf`	Energy-Efficient Satellite IoT Optical Downlinks Using Weather-Adaptive Reinforcement Learning. ICC Ethan Fettes, Pablo G. Madoery, Halim Yanikomeroglu, Gunes Karabulut Kurt, Abhishek Naik, Colin Bellinger, Stéphane Martel, Khaled Ahmed, Sameera Siddiqui
2025	J	`jnl`	Energy-Efficient Satellite IoT Optical Downlinks Using Weather-Adaptive Reinforcement Learning. CoRR Ethan Fettes, Pablo G. Madoery, Halim Yanikomeroglu, Gunes Karabulut-Kurt, Abhishek Naik, Colin Bellinger, Stephane Martel, Khaled Ahmed, Sameera Siddiqui
2025	J	`jnl`	General and Efficient Visual Goal-Conditioned Reinforcement Learning using Object-Agnostic Masks. CoRR Fahim Shahriar, Cheryl Wang, Alireza Azimi, Gautham Vasan, Hany Hamed Elanwar, A. Rupam Mahmood, Colin Bellinger
2025	—	`conf`	Stability Governor-guided RLMPC for Robot Manipulators. CDC Yufan Dai, Colin Bellinger, Yunli Wang, Chris Drummond, Yang Shi
2025	J	`jnl`	Versatile and Generalizable Manipulation via Goal-Conditioned Reinforcement Learning with Grounded Object Detection. CoRR Huiyi Wang, Fahim Shahriar, Alireza Azimi, Gautham Vasan, Rupam Mahmood, Colin Bellinger
2024	A*	`conf`	Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers. NeurIPS Gautham Vasan, Mohamed Elsayed, Seyed Alireza Azimi, Jiamin He, Fahim Shahriar, Colin Bellinger, Martha White, Rupam Mahmood
2024	J	`jnl`	Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers. CoRR Gautham Vasan, Mohamed Elsayed, Alireza Azimi, Jiamin He, Fahim Shahriar, Colin Bellinger, Martha White, A. Rupam Mahmood
2024	—	`conf`	Dynamic programming with incomplete information to overcome navigational uncertainty in POMDPs. Canadian AI Chris Beeler, Xinkai Li, Colin Bellinger, Mark Crowley, Maia Fraser, Isaac Tamblyn
2024	B	`conf`	Next-Generation Satellite IoT Networks: A HAPS-Enabled Solution to Enhance Optical Data Transfer. PIMRC Ethan Fettes, Pablo G. Madoery, Halim Yanikomeroglu, Gunes Karabulut Kurt, Colin Bellinger, Stéphane Martel, Khaled Ahmed, Sameera Siddiqui
2024	J	`jnl`	Next-Generation Satellite IoT Networks: A HAPS-Enabled Solution to Enhance Optical Data Transfer. CoRR Ethan Fettes, Pablo G. Madoery, Halim Yanikomeroglu, Gunes Karabulut Kurt, Colin Bellinger, Stéphane Martel, Khaled Ahmed, Sameera Siddiqui
2024	J	`jnl`	Reinforcement learning for in silico determination of adsorbate - substrate structures. J. Comput. Chem. Maicon Pierre Lourenço, Jirí Hostas, Colin Bellinger, Alain Tchagang, Dennis R. Salahub
2024	J	`jnl`	The class imbalance problem in deep learning. Mach. Learn. Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Paula Branco, Bartosz Krawczyk, Nathalie Japkowicz
2024	J	`jnl`	Understanding CNN fragility when learning with imbalanced data. Mach. Learn. Damien Dablain, Kristen N. Jacobson, Colin Bellinger, Mark Roberts, Nitesh V. Chawla
2024	J	`jnl`	Understanding imbalanced data: XAI & interpretable ML framework. Mach. Learn. Damien Dablain, Colin Bellinger, Bartosz Krawczyk, David W. Aha, Nitesh V. Chawla
2023	A	`conf`	An Interpretable Measure of Dataset Complexity for Imbalanced Classification Problems. SDM Jonatan Møller Nuutinen Gøttcke, Colin Bellinger, Paula Branco, Arthur Zimek
2023	J	`jnl`	Automated imbalanced classification via layered learning. Mach. Learn. Vítor Cerqueira, Luís Torgo, Paula Branco, Colin Bellinger
2023	J	`jnl`	ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry. CoRR Chris Beeler, Sriram Ganapathi Subramanian, Kyle Sprague, Nouha Chatti, Colin Bellinger, Mitchell Shahen, Nicholas Paquin, Mark Baula, Amanuel Dawit, Zihan Yang, Xinkai Li, Mark Crowley, Isaac Tamblyn
2023	A*	`conf`	Efficient Augmentation for Imbalanced Deep Learning. ICDE Damien A. Dablain, Colin Bellinger, Bartosz Krawczyk, Nitesh V. Chawla
2023	J	`jnl`	Learning Visual Tracking and Reaching with Deep Reinforcement Learning on a UR10e Robotic Arm. CoRR Colin Bellinger, Laurence Lamarche-Cliche
2023	—	`conf`	Learning When to Observe: A Frugal Reinforcement Learning Framework for a High-Cost World. PKDD/ECML Workshops (4) Colin Bellinger, Isaac Tamblyn, Mark Crowley
2023	J	`jnl`	Learning when to observe: A frugal reinforcement learning framework for a high-cost world. CoRR Colin Bellinger, Mark Crowley, Isaac Tamblyn
2023	—	`conf`	Performance Estimation bias in Class Imbalance with Minority Subconcepts. LIDTA Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
2023	J	`jnl`	Reinforcement Learning-based Wavefront Sensorless Adaptive Optics Approaches for Satellite-to-Ground Laser Communication. CoRR Payam Parvizi, Runnan Zou, Colin Bellinger, Ross Cheriton, Davide Spinello
2023	—	`conf`	Time and temporal abstraction in continual learning: tradeoffs, analogies and regret in an active measuring setting. CoLLAs Vincent Létourneau, Colin Bellinger, Isaac Tamblyn, Maia Fraser
2022	A*	`conf`	4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022. KDD Roberto Corizzo, Junfeng Ge, Colin Bellinger, Xiaoqiang Zhu, Paula Branco, Kuang-Chih Lee, Nathalie Japkowicz, Ruiming Tang, Tao Zhuang, Han Zhu, Biye Jiang, Jiaxin Mao, Weinan Zhang
2022	J	`jnl`	Automated Imbalanced Classification via Layered Learning. CoRR Vítor Cerqueira, Luís Torgo, Paula Branco, Colin Bellinger
2022	—	`conf`	Balancing Information with Observation Costs in Deep Reinforcement Learning. Canadian AI Colin Bellinger, Andriy Drozdyuk, Mark Crowley, Isaac Tamblyn
2022	J	`jnl`	Efficient Augmentation for Imbalanced Deep Learning. CoRR Damien Dablain, Colin Bellinger, Bartosz Krawczyk, Nitesh V. Chawla
2022	B	`conf`	Imbalanced Multi-layer Cloud Classification with Advanced Baseline Imager (ABI) and CloudSat/CALIPSO Data. IEEE Big Data Leah Ding, Roberto Corizzo, Colin Bellinger, Nancy Ching, Spencer Login, Rodrigo Yepez-Lopez, Jie Gong, Dong L. Wu
2022	J	`jnl`	Interpretable ML for Imbalanced Data. CoRR Damien A. Dablain, Colin Bellinger, Bartosz Krawczyk, David W. Aha, Nitesh V. Chawla
2022	J	`jnl`	Understanding CNN Fragility When Learning With Imbalanced Data. CoRR Damien Dablain, Kristen N. Jacobson, Colin Bellinger, Mark Roberts, Nitesh V. Chawla
2021	—	`conf`	Active Measure Reinforcement Learning for Observation Cost Minimization. Canadian AI Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn
2021	B	`conf`	Calibrated Resampling for Imbalanced and Long-Tails in Deep Learning. DS Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
2021	—	`conf`	Explainable image analysis for decision support in medical healthcare. IEEE BigData Roberto Corizzo, Yohan Dauphin, Colin Bellinger, Eftim Zdravevski, Nathalie Japkowicz
2021	—	`conf`	On the combined effect of class imbalance and concept complexity in deep learning. IEEE BigData Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Bartosz Krawczyk, Nathalie Japkowicz
2021	J	`jnl`	On the combined effect of class imbalance and concept complexity in deep learning. CoRR Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Bartosz Krawczyk, Nathalie Japkowicz
2021	B	`conf`	RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification. DSAA Michal Koziarski, Colin Bellinger, Michal Wozniak
2021	J	`jnl`	RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification. CoRR Michal Koziarski, Colin Bellinger, Michal Wozniak
2021	J	`jnl`	RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification. Mach. Learn. Michal Koziarski, Colin Bellinger, Michal Wozniak
2021	J	`jnl`	Scientific Discovery and the Cost of Measurement - Balancing Information and Cost in Reinforcement Learning. CoRR Colin Bellinger, Andriy Drozdyuk, Mark Crowley, Isaac Tamblyn
2021	B	`conf`	Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification. IJCNN Bartosz Krawczyk, Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
2020	J	`jnl`	Active Measure Reinforcement Learning for Observation Cost Minimization. CoRR Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn
2020	J	`jnl`	Framework for extreme imbalance classification: SWIM - sampling with the majority class. Knowl. Inf. Syst. Colin Bellinger, Shiven Sharma, Nathalie Japkowicz, Osmar R. Zaïane
2020	J	`jnl`	ReMix: Calibrated Resampling for Class Imbalance in Deep learning. CoRR Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz
2020	—	`conf`	Reinforcement Learning in a Physics-Inspired Semi-Markov Environment. Canadian AI Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn
2020	J	`jnl`	Reinforcement Learning in a Physics-Inspired Semi-Markov Environment. CoRR Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn
2020	J	`jnl`	SMOTEFUNA: Synthetic Minority Over-Sampling Technique Based on Furthest Neighbour Algorithm. IEEE Access Ahmad S. Tarawneh, Ahmad B. A. Hassanat, Khalid Almohammadi, Dmitry Chetverikov, Colin Bellinger
2019	B	`conf`	The CURE for Class Imbalance. DS Colin Bellinger, Paula Branco, Luís Torgo
2019	J	`jnl`	The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies. BMC Medical Informatics Decis. Mak. Khanh Vu, Rebecca A. Clark, Colin Bellinger, Graham Erickson, Alvaro Osornio-Vargas, Osmar R. Zaïane, Yan Yuan
2018	J	`jnl`	Discovering co-location patterns with aggregated spatial transactions and dependency rules. Int. J. Data Sci. Anal. Mohomed Shazan Mohomed Jabbar, Colin Bellinger, Osmar R. Zaïane, Alvaro Osornio-Vargas
2018	J	`jnl`	Manifold-based synthetic oversampling with manifold conformance estimation. Mach. Learn. Colin Bellinger, Christopher Drummond, Nathalie Japkowicz
2018	J	`jnl`	One-class classification - From theory to practice: A case-study in radioactive threat detection. Expert Syst. Appl. Colin Bellinger, Shiven Sharma, Nathalie Japkowicz
2018	A*	`conf`	Synthetic Oversampling with the Majority Class: A New Perspective on Handling Extreme Imbalance. ICDM Shiven Sharma, Colin Bellinger, Bartosz Krawczyk, Osmar R. Zaïane, Nathalie Japkowicz
2017	—	`conf`	Sampling a Longer Life: Binary versus One-class classification Revisited. LIDTA@PKDD/ECML Colin Bellinger, Shiven Sharma, Osmar R. Zaïane, Nathalie Japkowicz
2016	—	`conf`	Advantage of integration in big data: Feature generation in multi-relational databases for imbalanced learning. IEEE BigData Farrukh Ahmed, Michele Samorani, Colin Bellinger, Osmar R. Zaïane
2016	—	`conf`	Beyond the Boundaries of SMOTE - A Framework for Manifold-Based Synthetically Oversampling. ECML/PKDD (1) Colin Bellinger, Christopher Drummond, Nathalie Japkowicz
2015	C	`conf`	Active Learning for One-Class Classification. ICMLA Vincent Barnabe-Lortie, Colin Bellinger, Nathalie Japkowicz
2015	C	`conf`	Multi-label Classification of Anemia Patients. ICMLA Colin Bellinger, Ali Amid, Nathalie Japkowicz, Herna L. Viktor
2015	C	`conf`	Synthetic Oversampling for Advanced Radioactive Threat Detection. ICMLA Colin Bellinger, Nathalie Japkowicz, Christopher Drummond
2014	—	`conf`	Smoothing gamma ray spectra to improve outlier detection. CISDA Vincent Barnabe-Lortie, Colin Bellinger, Nathalie Japkowicz
2012	—	`conf`	Anomaly detection in gamma ray spectra: A machine learning perspective. CISDA Shiven Sharma, Colin Bellinger, Nathalie Japkowicz, Rodney Berg, R. Kurt Ungar
2012	—	`conf`	Clustering Based One-Class Classification for Compliance Verification of the Comprehensive Nuclear-Test-Ban Treaty. Canadian AI Shiven Sharma, Colin Bellinger, Nathalie Japkowicz
2012	J	`jnl`	On the Pattern Recognition and Classification of Stochastically Episodic Events. Trans. Comput. Collect. Intell. Colin Bellinger, B. John Oommen
2012	—	`conf`	One-Class versus Binary Classification: Which and When? ICMLA (2) Colin Bellinger, Shiven Sharma, Nathalie Japkowicz
2011	—	`conf`	A New Frontier in Novelty Detection: Pattern Recognition of Stochastically Episodic Events. ACIIDS (1) Colin Bellinger, B. John Oommen
2011	—	`conf`	Motivating the inclusion of meteorological indicators in the CTBT feature-space. CISDA Colin Bellinger, Nathalie Japkowicz
2010	—	`conf`	On simulating episodic events against a background of noise-like non-episodic events. SummerSim Colin Bellinger, B. John Oommen