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ORCIDMark Crowley 0001
Person information
- affiliation: University of Waterloo, ON, Canada
- affiliation: Oregon State University, Corvallis, OR, USA
- affiliation: UBC
Other persons with the same name
- Mark Crowley 0002 — Nottingham Trent University, UK
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2020 – today
- 2024
[i64]Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte, Mark Crowley:
Disentanglement in Implicit Causal Models via Switch Variable. CoRR abs/2402.11124 (2024)- 2023
- [b1]Benyamin Ghojogh
, Mark Crowley, Fakhri Karray, Ali Ghodsi:
Elements of Dimensionality Reduction and Manifold Learning. Springer 2023, ISBN 978-3-031-10601-9, pp. 1-596 - [j8]Sami Alperen Akgun, Moojan Ghafurian, Mark Crowley, Kerstin Dautenhahn:
Using Affect as a Communication Modality to Improve Human-Robot Communication in Robot-Assisted Search and Rescue Scenarios. IEEE Trans. Affect. Comput. 14(4): 3013-3030 (2023) - [c47]Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley:
Learning from Multiple Independent Advisors in Multi-agent Reinforcement Learning. AAMAS 2023: 1144-1153 - [c46]Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte, Mark Crowley:
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting. ICML 2023: 31596-31612 - [c45]Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley:
Multi-Agent Advisor Q-Learning (Extended Abstract). IJCAI 2023: 6884-6889 - [i63]Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley:
Learning from Multiple Independent Advisors in Multi-agent Reinforcement Learning. CoRR abs/2301.11153 (2023) - [i62]Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte, Mark Crowley:
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting. CoRR abs/2302.08635 (2023) - [i61]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:
ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry. CoRR abs/2305.14177 (2023) - [i60]Colin Bellinger, Mark Crowley, Isaac Tamblyn:
Learning when to observe: A frugal reinforcement learning framework for a high-cost world. CoRR abs/2307.02620 (2023) - 2022
- [j7]Ken Ming Lee, Sriram Ganapathi Subramanian, Mark Crowley:
Investigation of independent reinforcement learning algorithms in multi-agent environments. Frontiers Artif. Intell. 5 (2022) - [j6]Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley:
Multi-Agent Advisor Q-Learning. J. Artif. Intell. Res. 74: 1-74 (2022) - [c44]Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart:
Decentralized Mean Field Games. AAAI 2022: 9439-9447 - [c43]Colin Bellinger, Andriy Drozdyuk, Mark Crowley, Isaac Tamblyn:
Balancing Information with Observation Costs in Deep Reinforcement Learning. Canadian AI 2022 - [c42]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Theoretical Connection between Locally Linear Embedding, Factor Analysis, and Probabilistic PCA. Canadian AI 2022 - [c41]Shayan Shirahmad Gale Bagi, Behzad Moshiri, Hossein Gharaee Garakani, Mark Crowley, Pouya Mehrannia:
Real-Time Pedestrian Detection Using Enhanced Representations from Light-Weight YOLO Network. CoDIT 2022: 1524-1529 - [c40]Zehra Camlica, Jim Quesenberry, Daniel Carballo, Mark Crowley:
Aggressive Driver Behavior Detection using Parallel Convolutional Neural Networks on Simulated and Real Driving Data. IOTSMS 2022: 1-8 - [i59]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Spectral, Probabilistic, and Deep Metric Learning: Tutorial and Survey. CoRR abs/2201.09267 (2022) - [i58]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
On Manifold Hypothesis: Hypersurface Submanifold Embedding Using Osculating Hyperspheres. CoRR abs/2202.01619 (2022) - [i57]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Theoretical Connection between Locally Linear Embedding, Factor Analysis, and Probabilistic PCA. CoRR abs/2203.13911 (2022) - [i56]Sami Alperen Akgun, Moojan Ghafurian, Mark Crowley, Kerstin Dautenhahn:
Using Affect as a Communication Modality to Improve Human-Robot Communication in Robot-Assisted Search and Rescue Scenarios. CoRR abs/2208.09580 (2022) - 2021
- [j5]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Generative locally linear embedding: A module for manifold unfolding and visualization. Softw. Impacts 9: 100105 (2021) - [c39]Reza Godaz, Benyamin Ghojogh, Reshad Hosseini, Reza Monsefi, Fakhri Karray, Mark Crowley:
Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds. ACML 2021: 1-16 - [c38]Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn:
Active Measure Reinforcement Learning for Observation Cost Minimization. Canadian AI 2021 - [c37]Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart:
Partially Observable Mean Field Reinforcement Learning. AAMAS 2021: 537-545 - [c36]Aishwarya Krishna Allada, Yuanxin Wang, Veni Jindal, Morteza Babaie, Hamid R. Tizhoosh, Mark Crowley:
Analysis of Language Embeddings for Classification of Unstructured Pathology Reports. EMBC 2021: 2378-2381 - [c35]Moojan Ghafurian, Sami Alperen Akgun, Mark Crowley, Kerstin Dautenhahn:
Recognition of a Robot's Affective Expressions Under Conditions with Limited Visibility. INTERACT (3) 2021: 448-469 - [c34]Milad Sikaroudi, Benyamin Ghojogh, Fakhri Karray, Mark Crowley, Hamid R. Tizhoosh:
Magnification Generalization For Histopathology Image Embedding. ISBI 2021: 1864-1868 - [i55]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Factor Analysis, Probabilistic Principal Component Analysis, Variational Inference, and Variational Autoencoder: Tutorial and Survey. CoRR abs/2101.00734 (2021) - [i54]Milad Sikaroudi, Benyamin Ghojogh, Fakhri Karray, Mark Crowley, Hamid R. Tizhoosh:
Magnification Generalization for Histopathology Image Embedding. CoRR abs/2101.07757 (2021) - [i53]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Generative Locally Linear Embedding. CoRR abs/2104.01525 (2021) - [i52]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Laplacian-Based Dimensionality Reduction Including Spectral Clustering, Laplacian Eigenmap, Locality Preserving Projection, Graph Embedding, and Diffusion Map: Tutorial and Survey. CoRR abs/2106.02154 (2021) - [i51]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey. CoRR abs/2106.08443 (2021) - [i50]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Unified Framework for Spectral Dimensionality Reduction, Maximum Variance Unfolding, and Kernel Learning By Semidefinite Programming: Tutorial and Survey. CoRR abs/2106.15379 (2021) - [i49]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey. CoRR abs/2107.12521 (2021) - [i48]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey. CoRR abs/2108.04172 (2021) - [i47]Reza Godaz, Benyamin Ghojogh, Reshad Hosseini, Reza Monsefi, Fakhri Karray, Mark Crowley:
Vector Transport Free Riemannian LBFGS for Optimization on Symmetric Positive Definite Matrix Manifolds. CoRR abs/2108.11019 (2021) - [i46]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Uniform Manifold Approximation and Projection (UMAP) and its Variants: Tutorial and Survey. CoRR abs/2109.02508 (2021) - [i45]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
KKT Conditions, First-Order and Second-Order Optimization, and Distributed Optimization: Tutorial and Survey. CoRR abs/2110.01858 (2021) - [i44]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Sufficient Dimension Reduction for High-Dimensional Regression and Low-Dimensional Embedding: Tutorial and Survey. CoRR abs/2110.09620 (2021) - [i43]Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley:
Multi-Agent Advisor Q-Learning. CoRR abs/2111.00345 (2021) - [i42]Ken Ming Lee, Sriram Ganapathi Subramanian, Mark Crowley:
Investigation of Independent Reinforcement Learning Algorithms in Multi-Agent Environments. CoRR abs/2111.01100 (2021) - [i41]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey. CoRR abs/2111.13282 (2021) - [i40]Colin Bellinger, Andriy Drozdyuk, Mark Crowley, Isaac Tamblyn:
Scientific Discovery and the Cost of Measurement - Balancing Information and Cost in Reinforcement Learning. CoRR abs/2112.07535 (2021) - [i39]Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart:
Decentralized Mean Field Games. CoRR abs/2112.09099 (2021) - [i38]Chris Beeler, Xinkai Li, Mark Crowley, Maia Fraser, Isaac Tamblyn:
Dynamic programming with partial information to overcome navigational uncertainty in a nautical environment. CoRR abs/2112.14657 (2021) - 2020
- [c33]Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn:
Reinforcement Learning in a Physics-Inspired Semi-Markov Environment. Canadian AI 2020: 55-66 - [c32]Sushrut Bhalla, Sriram Ganapathi Subramanian, Mark Crowley:
Deep Multi Agent Reinforcement Learning for Autonomous Driving. Canadian AI 2020: 67-78 - [c31]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Anomaly Detection and Prototype Selection Using Polyhedron Curvature. Canadian AI 2020: 238-250 - [c30]Mohammad Hossein Basiri, Benyamin Ghojogh, Nasser L. Azad, Sebastian Fischmeister, Fakhri Karray, Mark Crowley:
Distributed Nonlinear Model Predictive Control and Metric Learning for Heterogeneous Vehicle Platooning with Cut-in/Cut-out Maneuvers. CDC 2020: 2849-2856 - [c29]Milad Sikaroudi, Amir Safarpoor, Benyamin Ghojogh, Sobhan Shafiei, Mark Crowley, Hamid R. Tizhoosh:
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study. EMBC 2020: 1400-1403 - [c28]Benyamin Ghojogh, Milad Sikaroudi, Hamid R. Tizhoosh, Fakhri Karray, Mark Crowley:
Weighted Fisher Discriminant Analysis in the Input and Feature Spaces. ICIAR (2) 2020: 3-15 - [c27]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces. ICIAR (2) 2020: 16-24 - [c26]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Theoretical Insights into the Use of Structural Similarity Index in Generative Models and Inferential Autoencoders. ICIAR (2) 2020: 112-117 - [c25]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Generalized Subspace Learning by Roweis Discriminant Analysis. ICIAR (1) 2020: 328-342 - [c24]Sami Alperen Akgun, Moojan Ghafurian, Mark Crowley, Kerstin Dautenhahn:
Using Emotions to Complement Multi-Modal Human-Robot Interaction in Urban Search and Rescue Scenarios. ICMI 2020: 575-584 - [c23]Milad Sikaroudi, Benyamin Ghojogh, Fakhri Karray, Mark Crowley, Hamid R. Tizhoosh:
Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem. ICPR 2020: 7080-7086 - [c22]Benyamin Ghojogh, Milad Sikaroudi, Sobhan Shafiei, Hamid R. Tizhoosh, Fakhri Karray, Mark Crowley:
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks. IJCNN 2020: 1-7 - [c21]Milad Sikaroudi, Benyamin Ghojogh, Amir Safarpoor, Fakhri Karray, Mark Crowley, Hamid R. Tizhoosh:
Offline Versus Online Triplet Mining Based on Extreme Distances of Histopathology Patches. ISVC (1) 2020: 333-345 - [c20]Haoran Ma, Benyamin Ghojogh, Maria N. Samad, Dongyu Zheng, Mark Crowley:
Isolation Mondrian Forest for Batch and Online Anomaly Detection. SMC 2020: 3051-3058 - [i37]Piyush Jain, Sean C. P. Coogan, Sriram Ganapathi Subramanian, Mark Crowley, Steve Taylor, Mike D. Flannigan:
A review of machine learning applications in wildfire science and management. CoRR abs/2003.00646 (2020) - [i36]Haoran Ma, Benyamin Ghojogh, Maria N. Samad, Dongyu Zheng, Mark Crowley:
Isolation Mondrian Forest for Batch and Online Anomaly Detection. CoRR abs/2003.03692 (2020) - [i35]Mohammad Hossein Basiri, Benyamin Ghojogh, Nasser L. Azad, Sebastian Fischmeister, Fakhri Karray, Mark Crowley:
Distributed Nonlinear Model Predictive Control and Metric Learning for Heterogeneous Vehicle Platooning with Cut-in/Cut-out Maneuvers. CoRR abs/2004.00417 (2020) - [i34]Benyamin Ghojogh, Milad Sikaroudi, Hamid R. Tizhoosh, Fakhri Karray, Mark Crowley:
Weighted Fisher Discriminant Analysis in the Input and Feature Spaces. CoRR abs/2004.01857 (2020) - [i33]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders. CoRR abs/2004.01864 (2020) - [i32]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Anomaly Detection and Prototype Selection Using Polyhedron Curvature. CoRR abs/2004.02137 (2020) - [i31]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces. CoRR abs/2004.04573 (2020) - [i30]Benyamin Ghojogh, Milad Sikaroudi, Sobhan Shafiei, Hamid R. Tizhoosh, Fakhri Karray, Mark Crowley:
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks. CoRR abs/2004.04674 (2020) - [i29]Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn:
Reinforcement Learning in a Physics-Inspired Semi-Markov Environment. CoRR abs/2004.07333 (2020) - [i28]Milad Sikaroudi, Amir Safarpoor, Benyamin Ghojogh, Sobhan Shafiei, Mark Crowley, Hamid R. Tizhoosh:
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study. CoRR abs/2005.08629 (2020) - [i27]Colin Bellinger, Rory Coles, Mark Crowley, Isaac Tamblyn:
Active Measure Reinforcement Learning for Observation Cost Minimization. CoRR abs/2005.12697 (2020) - [i26]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Quantile-Quantile Embedding for Distribution Transformation, Manifold Embedding, and Image Embedding with Choice of Embedding Distribution. CoRR abs/2006.11385 (2020) - [i25]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Roweisposes, Including Eigenposes, Supervised Eigenposes, and Fisherposes, for 3D Action Recognition. CoRR abs/2006.15736 (2020) - [i24]Milad Sikaroudi, Benyamin Ghojogh, Amir Safarpoor, Fakhri Karray, Mark Crowley, Hamid R. Tizhoosh:
Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches. CoRR abs/2007.02200 (2020) - [i23]Milad Sikaroudi, Benyamin Ghojogh, Fakhri Karray, Mark Crowley, Hamid R. Tizhoosh:
Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem. CoRR abs/2007.05610 (2020) - [i22]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey. CoRR abs/2009.08136 (2020) - [i21]Juan Carrillo, Daniel Garijo, Mark Crowley, Rober Carrillo, Yolanda Gil, Katherine Borda:
Semantic Workflows and Machine Learning for the Assessment of Carbon Storage by Urban Trees. CoRR abs/2009.10263 (2020) - [i20]Juan Carrillo, Mark Crowley, Guangyuan Pan, Liping Fu:
Design of Efficient Deep Learning models for Determining Road Surface Condition from Roadside Camera Images and Weather Data. CoRR abs/2009.10282 (2020) - [i19]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey. CoRR abs/2009.10301 (2020) - [i18]Juan Carrillo, Mark Crowley:
Integration of Roadside Camera Images and Weather Data for Monitoring Winter Road Surface Conditions. CoRR abs/2009.12165 (2020) - [i17]Parisa Abdolrahim Poorheravi, Benyamin Ghojogh, Vincent C. Gaudet, Fakhri Karray, Mark Crowley:
Acceleration of Large Margin Metric Learning for Nearest Neighbor Classification Using Triplet Mining and Stratified Sampling. CoRR abs/2009.14244 (2020) - [i16]Benyamin Ghojogh, Ali Ghodsi, Fakhri Karray, Mark Crowley:
Locally Linear Embedding and its Variants: Tutorial and Survey. CoRR abs/2011.10925 (2020) - [i15]Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart:
Partially Observable Mean Field Reinforcement Learning. CoRR abs/2012.15791 (2020)
2010 – 2019
- 2019
- [c19]Hadi NekoeiQachkanloo, Benyamin Ghojogh, Ali Saheb Pasand, Mark Crowley:
Artificial Counselor System for Stock Investment. AAAI 2019: 9558-9564 - [c18]Benyamin Ghojogh, Mark Crowley:
Instance Ranking and Numerosity Reduction Using Matrix Decomposition and Subspace Learning. Canadian AI 2019: 160-172 - [c17]Sushrut Bhalla, Sriram Ganapathi Subramanian, Mark Crowley:
Training Cooperative Agents for Multi-Agent Reinforcement Learning. AAMAS 2019: 1826-1828 - [c16]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Image Structure Subspace Learning Using Structural Similarity Index. ICIAR (1) 2019: 33-44 - [c15]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Principal Component Analysis Using Structural Similarity Index for Images. ICIAR (1) 2019: 77-88 - [c14]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Locally Linear Image Structural Embedding for Image Structure Manifold Learning. ICIAR (1) 2019: 126-138 - [c13]Juan Manuel Carrillo Garcia, Daniel Garijo, Mark Crowley, Rober Carrillo, Yolanda Gil, Katherine Borda:
Semantic Workflows and Machine Learning for the Assessment of Carbon Storage by Urban Trees. SciKnow@K-CAP 2019: 1-6 - [c12]Sushrut Bhalla, Matthew X. Yao, Jean-Pierre Hickey, Mark Crowley:
Compact Representation of a Multi-dimensional Combustion Manifold Using Deep Neural Networks. ECML/PKDD (3) 2019: 602-617 - [i14]Benyamin Ghojogh, Aydin Ghojogh, Mark Crowley, Fakhri Karray:
Fitting A Mixture Distribution to Data: Tutorial. CoRR abs/1901.06708 (2019) - [i13]Hadi NekoeiQachkanloo, Benyamin Ghojogh, Ali Saheb Pasand, Mark Crowley:
Artificial Counselor System for Stock Investment. CoRR abs/1903.00955 (2019) - [i12]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Eigenvalue and Generalized Eigenvalue Problems: Tutorial. CoRR abs/1903.11240 (2019) - [i11]Benyamin Ghojogh, Maria N. Samad, Sayema Asif Mashhadi, Tania Kapoor, Wahab Ali, Fakhri Karray, Mark Crowley:
Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review. CoRR abs/1905.02845 (2019) - [i10]Benyamin Ghojogh, Mark Crowley:
The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial. CoRR abs/1905.12787 (2019) - [i9]Benyamin Ghojogh, Mark Crowley:
Linear and Quadratic Discriminant Analysis: Tutorial. CoRR abs/1906.02590 (2019) - [i8]Benyamin Ghojogh, Mark Crowley:
Unsupervised and Supervised Principal Component Analysis: Tutorial. CoRR abs/1906.03148 (2019) - [i7]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Fisher and Kernel Fisher Discriminant Analysis: Tutorial. CoRR abs/1906.09436 (2019) - [i6]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Principal Component Analysis Using Structural Similarity Index for Images. CoRR abs/1908.09287 (2019) - [i5]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Locally Linear Image Structural Embedding for Image Structure Manifold Learning. CoRR abs/1908.09288 (2019) - [i4]Benyamin Ghojogh, Ali Saheb Pasand, Fakhri Karray, Mark Crowley:
Quantized Fisher Discriminant Analysis. CoRR abs/1909.03037 (2019) - [i3]Benyamin Ghojogh, Fakhri Karray, Mark Crowley:
Roweis Discriminant Analysis: A Generalized Subspace Learning Method. CoRR abs/1910.05437 (2019) - 2018
- [j4]Eric Eaton, Sven Koenig, Claudia Schulz, Francesco Maurelli, John S. Y. Lee, Joshua Eckroth, Mark Crowley, Richard G. Freedman, Rogelio Enrique Cardona-Rivera, Tiago Machado, Tom Williams:
Blue sky ideas in artificial intelligence education from the EAAI 2017 new and future AI educator program. AI Matters 3(4): 23-31 (2018) - [j3]Sriram Ganapathi Subramanian, Mark Crowley:
Using Spatial Reinforcement Learning to Build Forest Wildfire Dynamics Models From Satellite Images. Frontiers ICT 5: 6 (2018) - [c11]Sriram Ganapathi Subramanian, Mark Crowley:
Combining MCTS and A3C for Prediction of Spatially Spreading Processes in Forest Wildfire Settings. Canadian AI 2018: 285-291 - [c10]Sriram Ganapathi Subramanian, Jaspreet Singh Sambee, Benyamin Ghojogh, Mark Crowley:
Decision Assist for Self-driving Cars. Canadian AI 2018: 381-387 - [c9]Benyamin Ghojogh, Mark Crowley:
Principal Sample Analysis for Data Reduction. ICBK 2018: 350-357 - 2017
- [c8]Syeda Maryam, Laura McCrackin, Mark Crowley, Yogesh Rathi, Oleg V. Michailovich:
Application of probabilistically weighted graphs to image-based diagnosis of Alzheimer's disease using diffusion MRI. Computer-Aided Diagnosis 2017: 101342F - [i2]Eric Eaton, Sven Koenig, Claudia Schulz, Francesco Maurelli, John Lee, Joshua Eckroth, Mark Crowley, Richard G. Freedman, Rogelio Enrique Cardona-Rivera, Tiago Machado, Tom Williams:
Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program. CoRR abs/1702.00137 (2017) - 2016
- [c7]Mahmoud Salem, Mark Crowley, Sebastian Fischmeister:
Anomaly Detection Using Inter-Arrival Curves for Real-Time Systems. ECRTS 2016: 97-106 - 2015
- [j2]Majid Alkaee Taleghan, Thomas G. Dietterich, Mark Crowley, Kim Hall, H. Jo Albers:
PAC optimal MDP planning with application to invasive species management. J. Mach. Learn. Res. 16: 3877-3903 (2015) - 2014
- [j1]Mark Crowley:
Using Equilibrium Policy Gradients for Spatiotemporal Planning in Forest Ecosystem Management. IEEE Trans. Computers 63(1): 142-154 (2014) - 2013
- [c6]Thomas G. Dietterich, Majid Alkaee Taleghan, Mark Crowley:
PAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs. AAAI 2013: 1270-1276 - [c5]David Poole, Mark Crowley:
Cyclic Causal Models with Discrete Variables: Markov Chain Equilibrium Semantics and Sample Ordering. IJCAI 2013: 1060-1068 - 2012
- [i1]Mark Crowley, John Nelson, David Poole:
Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making. CoRR abs/1205.2651 (2012) - 2011
- [c4]Mark Crowley, David Poole:
Policy Gradient Planning for Environmental Decision Making with Existing Simulators. AAAI 2011: 1323-1330 - 2010
- [c3]Elizabeth Patitsas, Kimberly D. Voll, Mark Crowley, Steven A. Wolfman:
Circuits and logic in the lab: toward a coherent picture of computation. WCCCE 2010: 7:1-7:5
2000 – 2009
- 2009
- [c2]Mark Crowley, John Nelson, David Poole:
Seeing the Forest Despite the Trees: Large Scale Spatial-Temporal Decision Making. UAI 2009: 126-134 - 2007
- [c1]Mark Crowley, Brent Boerlage, David Poole:
Adding Local Constraints to Bayesian Networks. Canadian AI 2007: 344-355
Coauthor Index
[b1] [c42] [i59] [i58] [i57] [j5] [c39] [c34] [i55] [i54] [i53] [i52] [i51] [i50] [i49] [i48] [i47] [i46] [i45] [i44] [i41] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c23] [c22] [c21] [c20] [i36] [i35] [i34] [i33] [i32] [i31] [i30] [i28] [i26] [i25] [i24] [i23] [i22] [i19] [i17] [i16] [c19] [c18] [c16] [c15] [c14] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [i4] [i3] [c10] [c9]
[b1] [c42] [i59] [i58] [i57] [j5] [c39] [c34] [i55] [i54] [i53] [i52] [i51] [i50] [i49] [i48] [i47] [i46] [i45] [i44] [i41] [c31] [c30] [c28] [c27] [c26] [c25] [c23] [c22] [c21] [i35] [i34] [i33] [i32] [i31] [i30] [i26] [i25] [i24] [i23] [i22] [i19] [i17] [i16] [c16] [c15] [c14] [i14] [i12] [i11] [i7] [i6] [i5] [i4] [i3]
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of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-28 21:27 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
