Daniel L. Silver

65 papers A* 2B 5C 5Misc 8Journal 12Unranked 30

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	Consolidation using Multiple Task Learning with Context Inputs and Replay of CVAE Generated Pseudo-Examples. Canadian AI Quan Ngo, Daniel L. Silver
2023	J	`jnl`	Forecasting COVID-19 Case Counts Based on 2020 Ontario Data. CoRR Daniel L. Silver, Rinda Digamarthi
2023	—	`ch.`	The Roles of Symbols in Neural-Based AI: They Are Not What You Think! Compendium of Neurosymbolic Artificial Intelligence Daniel L. Silver, Tom M. Mitchell
2023	C	`conf`	The Roles of Symbols in Neural-based AI: They are Not What You Think! NeSy Daniel L. Silver, Tom M. Mitchell
2023	J	`jnl`	The Roles of Symbols in Neural-based AI: They are Not What You Think! CoRR Daniel L. Silver, Tom M. Mitchell
2022	Misc	`conf`	Vehicle Traffic Estimation Using Deep Learning. FLAIRS Meetkumar Patel, Daniel L. Silver
2021	C	`conf`	Learning Arithmetic from Handwritten Images with the Aid of Symbols. NeSy Daniel L. Silver, Ahmed Galila
2021	—	`conf`	The Disadvantage of CNN versus DBN Image Classification Under Adversarial Conditions. Canadian AI Tao Yang, Daniel L. Silver
2020	J	`jnl`	Estimating Grape Yield on the Vine from Multiple Images. CoRR Daniel L. Silver, Jabun Nasa
2020	—	`conf`	Generating Accurate Pseudo Examples for Continual Learning. CVPR Workshops Daniel L. Silver, Sazia Mahfuz
2019	J	`jnl`	AutoML @ NeurIPS 2018 challenge: Design and Results. CoRR Hugo Jair Escalante, Wei-Wei Tu, Isabelle Guyon, Daniel L. Silver, Evelyne Viegas, Yuqiang Chen, Wenyuan Dai, Qiang Yang
2019	—	`conf`	In Vino Veritas: Estimating Vineyard Grape Yield from Images Using Deep Learning. Canadian AI Daniel L. Silver, Tanya Monga
2017	B	`conf`	Improving point-based AIS trajectory classification with partition-wise gated recurrent units. IJCNN Xiang Jiang, Xuan Liu, Erico N. de Souza, Baifan Hu, Daniel L. Silver, Stan Matwin
2017	B	`conf`	Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification. ESANN Xiang Jiang, Erico N. de Souza, Xuan Liu, Behrouz Haji Soleimani, Xiaoguang Wang, Daniel L. Silver, Stan Matwin
2017	J	`jnl`	TrajectoryNet: An Embedded GPS Trajectory Representation for Point-based Classification Using Recurrent Neural Networks. CoRR Xiang Jiang, Erico N. de Souza, Ahmad Pesaranghader, Baifan Hu, Daniel L. Silver, Stan Matwin
2017	—	`conf`	TrajectoryNet: an embedded GPS trajectory representation for point-based classification using recurrent neural networks. CASCON Xiang Jiang, Erico N. de Souza, Ahmad Pesaranghader, Baifan Hu, Daniel L. Silver, Stan Matwin
2016	—	`conf`	A Proposal for Common Dataset in Neural-Symbolic Reasoning Studies. NeSy@HLAI Özgür Yilmaz, Artur S. d'Avila Garcez, Daniel L. Silver
2016	Misc	`conf`	A Scalable Unsupervised Deep Multimodal Learning System. FLAIRS Mohammed Shameer Iqbal, Daniel L. Silver
2016	—	`conf`	Fishing Activity Detection from AIS Data Using Autoencoders. Canadian AI Xiang Jiang, Daniel L. Silver, Baifan Hu, Erico N. de Souza, Stan Matwin
2015	—	`conf`	Consolidation Using Sweep Task Rehearsal: Overcoming the Stability-Plasticity Problem. Canadian AI Daniel L. Silver, Geoffrey Mason, Lubna Eljabu
2015	—	`conf`	Learning Paired-Associate Images with an Unsupervised Deep Learning Architecture. Canadian AI Ti Wang, Daniel L. Silver
2015	—	`conf`	Learning to reason in a Probably Approximately Correct manner. CCECE Jane E. Gomes, Daniel L. Silver
2015	—	`conf`	Neural-Symbolic Learning and Reasoning: Contributions and Challenges. AAAI Spring Symposia Artur S. d'Avila Garcez, Tarek R. Besold, Luc De Raedt, Peter Földiák, Pascal Hitzler, Thomas Icard, Kai-Uwe Kühnberger, Luís C. Lamb, Risto Miikkulainen, Daniel L. Silver
2013	—	`conf`	An Unsupervised Deep-Learning Architecture That Can Reconstruct Paired Images. RSFDGrC Ti Wang, Mohammed Shameer Iqbal, Daniel L. Silver
2013	J	`jnl`	Learning Paired-associate Images with An Unsupervised Deep Learning Architecture. CoRR Ti Wang, Daniel L. Silver
2013	—	`conf`	Lifelong Machine Learning Systems: Beyond Learning Algorithms. AAAI Spring Symposium: Lifelong Machine Learning Daniel L. Silver, Qiang Yang, Lianghao Li
2013	—	`conf`	The Consolidation of Task Knowledge for Lifelong Machine Learning. AAAI Spring Symposium: Lifelong Machine Learning Daniel L. Silver
2012	J	`jnl`	Analysis of the IJCNN 2011 UTL challenge. Neural Networks Isabelle Guyon, Gideon Dror, Vincent Lemaire, Daniel L. Silver, Graham W. Taylor, David W. Aha
2012	—	`conf`	CS/IT outreach from a Canadian perspective. SIGITE Conference Daryl H. Hepting, Gerry Donaldson, Peter R. King, Daniel L. Silver
2012	—	`conf`	ICML2011 Unsupervised and Transfer Learning Workshop. ICML Unsupervised and Transfer Learning Daniel L. Silver, Isabelle Guyon, Graham W. Taylor, Gideon Dror, Vincent Lemaire
2012	—	`conf`	Image Morphing: Transfer Learning between Tasks That Have Multiple Outputs. Canadian AI Daniel L. Silver, Liangliang Tu
2012	—	`ed.`	Unsupervised and Transfer Learning - Workshop held at ICML 2011, Bellevue, Washington, USA, July 2, 2011 ICML Unsupervised and Transfer Learning Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham W. Taylor, Daniel L. Silver
2011	—	`conf`	Consolidation Using Context-Sensitive Multiple Task Learning. Canadian AI Benjamin Fowler, Daniel L. Silver
2011	—	`conf`	Machine Lifelong Learning: Challenges and Benefits for Artificial General Intelligence. AGI Daniel L. Silver
2010	Misc	`conf`	CsMTL MLP For WEKA: Neural Network Learning with Inductive Transfer. FLAIRS Liangliang Tu, Benjamin Fowler, Daniel L. Silver
2010	J	`jnl`	User profile management: reference model and web services implementation. Int. J. Web Grid Serv. Zhongxu Ma, Daniel L. Silver, Elhadi M. Shakshuki
2008	J	`jnl`	A distributed multi-agent meeting scheduler. J. Comput. Syst. Sci. Elhadi M. Shakshuki, Hsiang-Hwa Koo, Darcy G. Benoit, Daniel L. Silver
2008	J	`jnl`	Guest editor's introduction: special issue on inductive transfer learning. Mach. Learn. Daniel L. Silver, Kristin P. Bennett
2008	—	`conf`	Image Transformation: Inductive Transfer between Multiple Tasks Having Multiple Outputs. Canadian AI Daniel L. Silver, Liangliang Tu
2008	J	`jnl`	Inductive transfer with context-sensitive neural networks. Mach. Learn. Daniel L. Silver, Ryan Poirier, Duane Currie
2008	—	`conf`	Using received signal strength variation for surveillance in residential areas. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security Sajid Hussain, Richard Peters, Daniel L. Silver
2007	—	`conf`	A Guide for Establishing and Managing a Computer Science Industrial Advisory Board. FECS André Trudel, Daniel L. Silver
2007	Misc	`conf`	Context-Sensitive MTL Networks for Machine Lifelong Learning. FLAIRS Daniel L. Silver, Ryan Poirier
2007	B	`conf`	Inductive transfer applied to stream discharge modeling. SMC Daniel L. Silver, Lisa Gaudette, Ian Spooner
2007	—	`conf`	Interface Adaptation Based on User Expectation. AINA Workshops (2) Xiaoyan Peng, Daniel L. Silver
2007	—	`conf`	LonelyDog@Home. Web Intelligence/IAT Workshops F. Hu, Daniel L. Silver, André Trudel
2007	—	`conf`	Requirements for Machine Lifelong Learning. IWINAC (1) Daniel L. Silver, Ryan Poirier
2007	B	`conf`	Sequential Inductive Transfer for Coronary Artery Disease Diagnosis. IJCNN Daniel L. Silver, Robert E. Mercer
2006	Misc	`conf`	Keystroke and Eye-Tracking Biometrics for User Identification. IC-AI Daniel L. Silver, Adam Biggs
2006	A*	`conf`	Machine Life-Long Learning with csMTL Networks. AAAI Daniel L. Silver, Ryan Poirier
2005	Misc	`conf`	A Measure of Relatedness for Selecting Consolidated Task Knowledge. FLAIRS Daniel L. Silver, Richard Alisch
2005	B	`conf`	Effect of curriculum on the consolidation of neural network task knowledge. IJCNN Ryan Poirier, Daniel L. Silver
2005	—	`conf`	Establishing and Managing a Computer Science Industrial Advisory Board. FECS André Trudel, Daniel L. Silver
2005	C	`conf`	Information Visualization for Intrusion Detection. PST James Blustein, Daniel L. Silver, Ching-Lung Fu
2005	—	`conf`	Information visualization for an intrusion detection system. Hypertext James Blustein, Ching-Lung Fu, Daniel L. Silver
2005	—	`conf`	User Control over User Adaptation: A Case Study. User Modeling Xiaoyan Peng, Daniel L. Silver
2004	—	`conf`	Sequential Consolidation of Learned Task Knowledge. Canadian AI Daniel L. Silver, Ryan Poirier
2004	—	`conf`	Time-Sensitive Sampling for Spam Filtering. Canadian AI Ching-Lung Fu, Daniel L. Silver
2003	Misc	`conf`	Selective Transfer of Task Knowledge Using Stochastic Noise. AI Daniel L. Silver, Peter McCracken
2003	C	`conf`	The Consolidation of Neural Network Task Knowledge. ICMLA Daniel L. Silver, Peter McCracken
2002	C	`conf`	Life-long Learning through Task Rehersal and Selective Transfer. ICMLA Daniel L. Silver, Robert E. Mercer
2002	Misc	`conf`	The Task Rehearsal Method of Life-Long Learning: Overcoming Impoverished Data. AI Daniel L. Silver, Robert E. Mercer
1998	—	`ch.`	The Parallel Transfer of Task Knowledge Using Dynamic Learning Rates Based on a Measure of Relatedness. Learning to Learn Daniel L. Silver, Robert E. Mercer
1996	J	`jnl`	The Parallel Transfer of Task Knowledge Using Dynamic Learning Rates Based on a Measure of Relatedness. Connect. Sci. Daniel L. Silver
1994	A*	`conf`	X-500 Directory Schema Management. ICDE Daniel L. Silver, James W. Hong, Michael A. Bauer