Articles with public access mandates - Dale SchuurmansLearn more
Available somewhere: 34
Learning with a Strong Adversary
R Huang, B Xu, D Schuurmans, C Szepesvari
https://arxiv.org/abs/1511.03034, 2015
Mandates: Natural Sciences and Engineering Research Council of Canada
On the global convergence rates of softmax policy gradient methods
J Mei, C Xiao, C Szepesvari, D Schuurmans
International conference on machine learning, 6820-6829, 2020
Mandates: Natural Sciences and Engineering Research Council of Canada
Semi-supervised conditional random fields for improved sequence segmentation and labeling
F Jiao, S Wang, CH Lee, R Greiner, D Schuurmans
Mandates: Genome Canada
Coindice: Off-policy confidence interval estimation
B Dai, O Nachum, Y Chow, L Li, C Szepesvári, D Schuurmans
Advances in neural information processing systems 33, 9398-9411, 2020
Mandates: Natural Sciences and Engineering Research Council of Canada
Lego: Latent execution-guided reasoning for multi-hop question answering on knowledge graphs
H Ren, H Dai, B Dai, X Chen, M Yasunaga, H Sun, D Schuurmans, ...
International conference on machine learning, 8959-8970, 2021
Mandates: US National Science Foundation, US Department of Defense, US National …
Domain aggregation networks for multi-source domain adaptation
J Wen, R Greiner, D Schuurmans
International conference on machine learning, 10214-10224, 2020
Mandates: Natural Sciences and Engineering Research Council of Canada
Combiner: Full attention transformer with sparse computation cost
H Ren, H Dai, Z Dai, M Yang, J Leskovec, D Schuurmans, B Dai
Advances in Neural Information Processing Systems 34, 22470-22482, 2021
Mandates: US National Science Foundation, US Department of Defense, US National …
An experimental methodology for response surface optimization methods
DJ Lizotte, R Greiner, D Schuurmans
Journal of Global Optimization 53, 699-736, 2012
Mandates: US National Institutes of Health
Leveraging non-uniformity in first-order non-convex optimization
J Mei, Y Gao, B Dai, C Szepesvari, D Schuurmans
International Conference on Machine Learning, 7555-7564, 2021
Mandates: Natural Sciences and Engineering Research Council of Canada
Escaping the gravitational pull of softmax
J Mei, C Xiao, B Dai, L Li, C Szepesvári, D Schuurmans
Advances in Neural Information Processing Systems 33, 21130-21140, 2020
Mandates: Natural Sciences and Engineering Research Council of Canada
Exponential family estimation via adversarial dynamics embedding
B Dai, Z Liu, H Dai, N He, A Gretton, L Song, D Schuurmans
Advances in Neural Information Processing Systems 32, 2019
Mandates: US National Science Foundation
Generalized conditional gradient for sparse estimation
Y Yu, X Zhang, D Schuurmans
Journal of Machine Learning Research 18 (144), 1-46, 2017
Mandates: Natural Sciences and Engineering Research Council of Canada
Smore: Knowledge graph completion and multi-hop reasoning in massive knowledge graphs
H Ren, H Dai, B Dai, X Chen, D Zhou, J Leskovec, D Schuurmans
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
Mandates: US National Science Foundation, US Department of Defense
Kernel exponential family estimation via doubly dual embedding
B Dai, H Dai, A Gretton, L Song, D Schuurmans, N He
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Mandates: US National Science Foundation
Maximum entropy monte-carlo planning
C Xiao, R Huang, J Mei, D Schuurmans, M Müller
Advances in Neural Information Processing Systems 32, 2019
Mandates: Natural Sciences and Engineering Research Council of Canada
Learning interactive real-world simulators
M Yang, Y Du, K Ghasemipour, J Tompson, D Schuurmans, P Abbeel
arXiv preprint arXiv:2310.06114, 2023
Mandates: US National Science Foundation, Natural Sciences and Engineering Research …
Variational rejection sampling
A Grover, R Gummadi, M Lazaro-Gredilla, D Schuurmans, S Ermon
International Conference on Artificial Intelligence and Statistics, 823-832, 2018
Mandates: US National Science Foundation
On the global convergence rates of decentralized softmax gradient play in markov potential games
R Zhang, J Mei, B Dai, D Schuurmans, N Li
Advances in Neural Information Processing Systems 35, 1923-1935, 2022
Mandates: US National Science Foundation, US Department of Defense
On the optimality of batch policy optimization algorithms
C Xiao, Y Wu, J Mei, B Dai, T Lattimore, L Li, C Szepesvari, ...
International Conference on Machine Learning, 11362-11371, 2021
Mandates: Natural Sciences and Engineering Research Council of Canada
The curse of passive data collection in batch reinforcement learning
C Xiao, I Lee, B Dai, D Schuurmans, C Szepesvari
International Conference on Artificial Intelligence and Statistics, 8413-8438, 2022
Mandates: Natural Sciences and Engineering Research Council of Canada
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