X-500 Directory Schema Management. - Daniel L. Silver; James W. Hong; Michael A. Bauer 001 (ICDE, 1994)

The Parallel Transfer of Task Knowledge Using Dynamic Learning Rates Based on a Measure of Relatedness. - Daniel L. Silver (Connect. Sci., 1996)

The Parallel Transfer of Task Knowledge Using Dynamic Learning Rates Based on a Measure of Relatedness. - Daniel L. Silver; Robert E. Mercer (Learning to Learn, 1998)

The Task Rehearsal Method of Life-Long Learning: Overcoming Impoverished Data. - Daniel L. Silver; Robert E. Mercer (AI, 2002)

Life-long Learning through Task Rehersal and Selective Transfer. - Daniel L. Silver; Robert E. Mercer (ICMLA, 2002)

Selective Transfer of Task Knowledge Using Stochastic Noise. - Daniel L. Silver; Peter McCracken (AI, 2003)

The Consolidation of Neural Network Task Knowledge. - Daniel L. Silver; Peter McCracken (ICMLA, 2003)

Time-Sensitive Sampling for Spam Filtering. - Ching-Lung Fu; Daniel L. Silver (Canadian AI, 2004)

Sequential Consolidation of Learned Task Knowledge. - Daniel L. Silver; Ryan Poirier (Canadian AI, 2004)

Establishing and Managing a Computer Science Industrial Advisory Board. - André Trudel; Daniel L. Silver (FECS, 2005)

A Measure of Relatedness for Selecting Consolidated Task Knowledge. - Daniel L. Silver; Richard Alisch (FLAIRS, 2005)

Information visualization for an intrusion detection system. - James Blustein; Ching-Lung Fu; Daniel L. Silver (Hypertext, 2005)

Effect of curriculum on the consolidation of neural network task knowledge. - Ryan Poirier; Daniel L. Silver (IJCNN, 2005)

Information Visualization for Intrusion Detection. - James Blustein; Daniel L. Silver; Ching-Lung Fu (PST, 2005)

User Control over User Adaptation: A Case Study. - Xiaoyan Peng; Daniel L. Silver (User Modeling, 2005)

Machine Life-Long Learning with csMTL Networks. - Daniel L. Silver; Ryan Poirier (AAAI, 2006)

Keystroke and Eye-Tracking Biometrics for User Identification. - Daniel L. Silver; Adam Biggs (IC-AI, 2006)

Interface Adaptation Based on User Expectation. - Xiaoyan Peng; Daniel L. Silver (AINA Workshops (2), 2007)

A Guide for Establishing and Managing a Computer Science Industrial Advisory Board. - André Trudel; Daniel L. Silver (FECS, 2007)

Context-Sensitive MTL Networks for Machine Lifelong Learning. - Daniel L. Silver; Ryan Poirier (FLAIRS, 2007)

LonelyDog@Home. - F. Hu; Daniel L. Silver; André Trudel (Web Intelligence/IAT Workshops, 2007)

Sequential Inductive Transfer for Coronary Artery Disease Diagnosis. - Daniel L. Silver; Robert E. Mercer (IJCNN, 2007)

Requirements for Machine Lifelong Learning. - Daniel L. Silver; Ryan Poirier (IWINAC (1), 2007)

Inductive transfer applied to stream discharge modeling. - Daniel L. Silver; Lisa Gaudette; Ian Spooner (SMC, 2007)

Image Transformation: Inductive Transfer between Multiple Tasks Having Multiple Outputs. - Daniel L. Silver; Liangliang Tu (Canadian AI, 2008)

Using received signal strength variation for surveillance in residential areas. - Sajid Hussain; Richard Peters; Daniel L. Silver (Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security, 2008)

A distributed multi-agent meeting scheduler. - Elhadi M. Shakshuki; Hsiang-Hwa Koo; Darcy G. Benoit; Daniel L. Silver (J. Comput. Syst. Sci., 2008)

Guest editor's introduction: special issue on inductive transfer learning. - Daniel L. Silver; Kristin P. Bennett (Mach. Learn., 2008)

Inductive transfer with context-sensitive neural networks. - Daniel L. Silver; Ryan Poirier; Duane Currie (Mach. Learn., 2008)

CsMTL MLP For WEKA: Neural Network Learning with Inductive Transfer. - Liangliang Tu; Benjamin Fowler; Daniel L. Silver (FLAIRS, 2010)

User profile management: reference model and web services implementation. - Zhongxu Ma; Daniel L. Silver; Elhadi M. Shakshuki (Int. J. Web Grid Serv., 2010)

Machine Lifelong Learning: Challenges and Benefits for Artificial General Intelligence. - Daniel L. Silver (AGI, 2011)

Consolidation Using Context-Sensitive Multiple Task Learning. - Benjamin Fowler; Daniel L. Silver (Canadian AI, 2011)

Image Morphing: Transfer Learning between Tasks That Have Multiple Outputs. - Daniel L. Silver; Liangliang Tu (Canadian AI, 2012)

CS/IT outreach from a Canadian perspective. - Daryl H. Hepting; Gerry Donaldson; Peter R. King; Daniel L. Silver (SIGITE Conference, 2012)

ICML2011 Unsupervised and Transfer Learning Workshop. - Daniel L. Silver; Isabelle Guyon; Graham W. Taylor; Gideon Dror; Vincent Lemaire 001 (ICML Unsupervised and Transfer Learning, 2012)

Analysis of the IJCNN 2011 UTL challenge. - Isabelle Guyon; Gideon Dror; Vincent Lemaire 001; Daniel L. Silver; Graham W. Taylor; David W. Aha (Neural Networks, 2012)

The Consolidation of Task Knowledge for Lifelong Machine Learning. - Daniel L. Silver (AAAI Spring Symposium: Lifelong Machine Learning, 2013)

Lifelong Machine Learning Systems: Beyond Learning Algorithms. - Daniel L. Silver; Qiang Yang 001; Lianghao Li (AAAI Spring Symposium: Lifelong Machine Learning, 2013)

An Unsupervised Deep-Learning Architecture That Can Reconstruct Paired Images. - Ti Wang; Mohammed Shameer Iqbal; Daniel L. Silver (RSFDGrC, 2013)

Neural-Symbolic Learning and Reasoning: Contributions and Challenges. - 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 (AAAI Spring Symposia, 2015)

Consolidation Using Sweep Task Rehearsal: Overcoming the Stability-Plasticity Problem. - Daniel L. Silver; Geoffrey Mason; Lubna Eljabu (Canadian AI, 2015)

Learning Paired-Associate Images with an Unsupervised Deep Learning Architecture. - Ti Wang; Daniel L. Silver (Canadian AI, 2015)

Learning to reason in a Probably Approximately Correct manner. - Jane E. Gomes; Daniel L. Silver (CCECE, 2015)

Fishing Activity Detection from AIS Data Using Autoencoders. - Xiang Jiang 001; Daniel L. Silver; Baifan Hu; Erico N. de Souza; Stan Matwin (Canadian AI, 2016)

A Scalable Unsupervised Deep Multimodal Learning System. - Mohammed Shameer Iqbal; Daniel L. Silver (FLAIRS, 2016)

A Proposal for Common Dataset in Neural-Symbolic Reasoning Studies. - Özgür Yilmaz; Artur S. d'Avila Garcez; Daniel L. Silver (NeSy@HLAI, 2016)

TrajectoryNet: an embedded GPS trajectory representation for point-based classification using recurrent neural networks. - Xiang Jiang 001; Erico N. de Souza; Ahmad Pesaranghader; Baifan Hu; Daniel L. Silver; Stan Matwin (CASCON, 2017)

Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification. - Xiang Jiang 001; Erico N. de Souza; Xuan Liu 007; Behrouz Haji Soleimani; Xiaoguang Wang 001; Daniel L. Silver; Stan Matwin (ESANN, 2017)

Improving point-based AIS trajectory classification with partition-wise gated recurrent units. - Xiang Jiang 001; Xuan Liu 007; Erico N. de Souza; Baifan Hu; Daniel L. Silver; Stan Matwin (IJCNN, 2017)

In Vino Veritas: Estimating Vineyard Grape Yield from Images Using Deep Learning. - Daniel L. Silver; Tanya Monga (Canadian AI, 2019)

AutoML @ NeurIPS 2018 challenge: Design and Results. - Hugo Jair Escalante; Wei-Wei Tu; Isabelle Guyon; Daniel L. Silver; Evelyne Viegas; Yuqiang Chen; Wenyuan Dai; Qiang Yang 001 (CoRR, 2019)

Generating Accurate Pseudo Examples for Continual Learning. - Daniel L. Silver; Sazia Mahfuz (CVPR Workshops, 2020)

Estimating Grape Yield on the Vine from Multiple Images. - Daniel L. Silver; Jabun Nasa (CoRR, 2020)

The Disadvantage of CNN versus DBN Image Classification Under Adversarial Conditions. - Tao Yang; Daniel L. Silver (Canadian AI, 2021)

Learning Arithmetic from Handwritten Images with the Aid of Symbols. - Daniel L. Silver; Ahmed Galila (NeSy, 2021)

Vehicle Traffic Estimation Using Deep Learning. - Meetkumar Patel; Daniel L. Silver (FLAIRS, 2022)

The Roles of Symbols in Neural-based AI: They are Not What You Think! - Daniel L. Silver; Tom M. Mitchell (NeSy, 2023)

Forecasting COVID-19 Case Counts Based on 2020 Ontario Data. - Daniel L. Silver; Rinda Digamarthi (CoRR, 2023)

The Roles of Symbols in Neural-Based AI: They Are Not What You Think! - Daniel L. Silver; Tom M. Mitchell (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Consolidation using Multiple Task Learning with Context Inputs and Replay of CVAE Generated Pseudo-Examples. - Quan Ngo; Daniel L. Silver (Canadian AI, 2024)