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Items where Author is "Bengio, Yoshua"

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Number of items: 44.

A

Anbil Parthipan, S. C., Sankar, C., Vorontsov, E., Kahou, S. E., & Bengio, Y. (2019). Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. AAAI Conference on Artificial Intelligence, 33(1), 3280-3287. External link

B

Bengio, Y., Lodi, A., & Prouvost, A. (2021). Machine learning for combinatorial optimization: A methodological tour d'horizon. European Journal of Operational Research, 290(2), 405-421. External link

Bengio, Y., Gupta, P., Maharaj, T., Rahaman, N., Weiss, M., Deleu, T., Muller, E., Qu, M., Schmidt, V., St-Charles, P.-L., Alsdurf, H., Bilanuik, O., Buckeridge, D., Caron, G. M., Carrier, P.-L., Ghosn, J., Ortiz-Gagne, S., Pal, C., Rish, I., ... Williams, A. (2021, May). Predicting infectiousness for proactive contact tracing [Paper]. 9th International Conference on Learning Representations (ICLR 2021), Vienne, Austria. Unavailable

Bengio, Y., Frejinger, E., Lodi, A., Patel, R., & Sankaranarayanan, S. (2020, September). A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programs [Paper]. 17th International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research. (CPAIOR 2020), Vienna, Austria. External link

Bengio, Y., Deleu, T., Rahaman, N., Ke, N. R., Lachapelle, S., Bilaniuk, O., Goyal, A., & Pal, C. J. (2020, April). A meta-transfer objective for learning to disentagle causal mechanisms [Paper]. 8th International Conference on Learning Representations (ICLR 2020), Addis Ababa, Ethiopia (27 pages). External link

Beckham, C., Honari, S., Verma, V., Lamb, A., Ghadiri, F., Hjelm, R. D., Bengio, Y., & Pal, C. J. (2019, December). On adversarial mixup resynthesis [Paper]. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. External link

Bengio, Y., Lodi, A., & Prouvost, A. (2018). Machine learning for combinatorial optimization : a methodological tour d'horizon. (Technical Report n° DS4DM-2018-08). External link

Bengio, Y., & Lodi, A. (2017). Les données au service du savoir. Gestion, 42(1), 68-70. External link

C

Courbariaux, M., Bengio, Y., & David, J. P. (2015, December). BinaryConnect: Training deep neural networks with binary weights during propagations [Paper]. 28th Conference on Advances in Neural Information Processing Systems (NIPS 2015), Montréal, Québec. Unavailable

Courbariaux, M., Bengio, Y., & David, J. P. (2015, May). Training deep neural networks with low precision multiplications [Paper]. International Conference on Learning Representations (ICLR 2015), San Diego, Calif. (10 pages). External link

Carreau, J., & Bengio, Y. (2009). A Hybrid Pareto Mixture for Conditional Asymmetric Fat-Tailed Distributions. IEEE Transactions on Neural Networks, 20(7), 1087-1101. External link

Carreau, J., & Bengio, Y. (2009). A hybrid Pareto model for asymmetric fat-tailed data: the univariate case. Extremes, 12(1), 53-76. External link

Carreau, J., & Bengio, Y. (2007, March). A hybrid pareto model for conditional density estimation of asymmetric fat-tail data [Paper]. 11th International Conference on Artificial Intelligence and Statistics, San Pedro, Puerto Rico. Unavailable

D

Drozdzal, M., Chartrand, G., Vorontsov, E., Shakeri, M., Di Jorio, L., Tang, A., Romero, A., Bengio, Y., Pal, C. J., & Kadoury, S. (2018). Learning normalized inputs for iterative estimation in medical image segmentation. Medical Image Analysis, 44, 1-13. External link

G

Gupta, P., Gasse, M., Khalil, E. B., Kumar, M. P., Lodi, A., & Bengio, Y. (2020, December). Hybrid models for learning to branch [Paper]. 34th Conference on neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada (11 pages). External link

Gottipati, S. K., Sattarov, B., Niu, S., Pathak, Y., Wei, H., Liu, S., Thomas, K. M. J., Blackburn, S., Coley, C. W., Tang, J., Anbil Parthipan, S. C., & Bengio, Y. (2020, July). Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. [Paper]. 37th International Conference on Machine Learning (ICML 2020), Vienna, Austria. External link

Gupta, P., Gasse, M., Khalil, E. B., Kumar, M. P., Lodi, A., & Bengio, Y. (2020, December). Supplement: Hybrid models for learning to branch [Paper]. 34th Conference on neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada (8 pages). External link

Gulcehre, C., Anbil Parthipan, S. C., Cho, K., & Bengio, Y. (2018). Dynamic neural turing machine with continuous and discrete addressing schemes. Neural Computation, 30(4), 857-884. External link

Goyal, A., Ke, N. R., Ganguli, S., & Bengio, Y. (2017, December). Variational walkback: Learning a transition operator as a stochastic recurrent net [Paper]. 31st Annual Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA. Unavailable

Goyal, A., Sordoni, A., Cote, M.-A., Ke, N. R., & Bengio, Y. (2017, December). Z-forcing: Training stochastic recurrent networks [Paper]. 31st Annual Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA. Unavailable

H

Havaei, M., Davy, A., Warde-Farley, D., Biard, A., Courville, A., Bengio, Y., Pal, C. J., Jodoin, P.-M., & Larochelle, H. (2017). Brain tumor segmentation with Deep Neural Networks. Medical Image Analysis, 35, 18-31. External link

J

Jegou, S., Drozdzal, M. A., Vazquez, D., Romero, A., & Bengio, Y. (2017, July). The one hundred layers Tiramisu: fully convolutional DenseNets for semantic segmentation [Paper]. IEEE Conference on Computer Vision and Pattern Recognition: Workshops (CVPRW 2017), Honolulu, HI, USA. External link

K

Kerg, G., Goyette, K., Touzel, M. P., Gidel, G., Vorontsov, E., Bengio, Y., & Lajoie, G. (2019, December). Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics [Paper]. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, B.-C.. External link

Krueger, D., Maharaj, T., Kramar, J., Pezeshki, M., Ballas, N., Ke, N. R., Goyal, A., Bengio, Y., Courville, A., & Pal, C. J. (2017, April). Zoneout: Regularizing rNNs by randomly preserving hidden activations [Paper]. 5th International Conference on Learning Representations (ICLR 2017), Toulon, France (11 pages). External link

Ke, N. R., Zoma, K., Sordoni, A., Lin, Z., Trischler, A., Bengio, Y., Pineau, J., Charlin, L., & Pal, C. J. (2018, July). Focused hierarchical RNNs for conditional sequence processing [Paper]. 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden. External link

Ke, N. R., Goyal, A., Bilaniuk, O., Binas, J., Mozer, M. C., Pal, C. J., & Bengio, Y. (2018, December). Sparse attentive backtracking: Temporal credit assignment through reminding [Paper]. 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montréal, Canada (12 pages). External link

Kahou, S. E., Bouthillier, X., Lamblin, P., Gülçehre, Ç., Michalski, V., Konda, K., Jean, S., Froumenty, P., Dauphin, Y., Boulanger-Lewandowski, N., Ferrari, R. C., Mirza, M., Warde-Farley, D., Courville, A., Vincent, P., Memisevic, R., Pal, C. J., & Bengio, Y. (2016). EmoNets: Multimodal deep learning approaches for emotion recognition in video. Journal on Multimodal User Interfaces, 10(2), 99-111. External link

Kahou, S. E., Pal, C. J., Bouthillier, X., Froumenty, P., Gülçehre, Ç., Memisevic, R., Vincent, P., Courville, A., Bengio, Y., Ferrari, R. C., Mirza, M., Jean, S., Carrier, P.-L., Dauphin, Y., Boulanger-Lewandowski, N., Aggarwal, A., Zumer, J., Lamblin, P., Raymond, J.-P., ... Wu, Z. (2013, December). Combining modality specific deep neural networks for emotion recognition in video [Paper]. 15th ACM International Conference on Multimodal Interaction (ICMI 2013), Sydney, NSW, Australia. External link

L

Larsen, E., Lachapelle, S., Bengio, Y., Frejinger, E., Lacoste-Julien, S., & Lodi, A. (2021). Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information. INFORMS Journal on Computing, 34(1), 227-242. External link

Larsen, E., Lachapelle, S., Bengio, Y., Frejinger, E., Lacoste-Julien, S., & Lodi, A. (2019). Predicting tactical solutions to operational planning problems under imperfect information. (Technical Report n° DS4DM-2019-003). External link

L'Heureux, P. J., Carreau, J., Bengio, Y., Delalleau, O., & Yue, S. Y. (2004). Locally Linear Embedding for dimensionality reduction in QSAR. Journal of Computer-Aided Molecular Design, 18(7), 475-482. External link

M

Madan, K., Ke, N. R., Goyal, A., Schölkopf, B., & Bengio, Y. (2021, April). Fast and slow learning of recurrent independent mechanisms [Paper]. 10th International Conference on Learning Representations (ICLR 2021) (18 pages). Unavailable

P

Piche, A., Thomas, V., Ibrahim, C., Bengio, Y., & Pal, C. J. (2019, May). Probabilistic planning with sequential Monte Carlo methods [Poster]. 7th International Conference on Learning Representations, New Orleans, Louisiana (8 pages). External link

R

Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., Luccioni, A. S., Maharaj, T., Sherwin, E. D., Mukkavilli, S. K., Körding, K. P., Gomes, C. P., Ng, A. Y., Hassabis, D., Platt, J. C., ... Bengio, Y. (2023). Tackling climate change with machine learning. ACM Computing Surveys, 55(2), 42 (96 pages). Available

S

Sylvain, T., Luck, M., Cohen, J. P., Cardinal, H., Lodi, A., & Bengio, Y. (2021, March). Exploring the Wasserstein metric for survival analysis [Paper]. AAAI Spring Symposium on Survival Prediction - Algorithms, Challenges and Applications (SPACA 2021), Palo Alto, CA, USA (13 pages). External link

Serban, I. V., Sankar, C., Pieper, M., Pineau, J., & Bengio, Y. (2020). The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach. Journal of Artificial Intelligence Research, 69, 571-612. External link

Sankar, C., Subramanian, S., Pal, C. J., Chandar, S., & Bengio, Y. (2019, July). Do neural dialog systems use the conversation history effectively? An empirical study [Paper]. 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), Florence, Italy. External link

Subramanian, S., Trischler, A., Bengio, Y., & Pal, C. J. (2018, April). Learning general purpose distributed sentence representations via large scale multitask learning [Paper]. 6th International Conference on Learning Representations (ICLR 2018), Vancouver, BC, Canada. External link

Serdyuk, D., Ke, N. R., Sordoni, A., Trischler, A., Pal, C. J., & Bengio, Y. (2018, April). Twin Networks: Matching the future for sequence generation [Paper]. 6th International Conference on Learning Representations (ICLR 2018), Vancouver, BC, Canada (12 pages). External link

Serban, I. V., García-Durán, A., Gülçehre, Ç., Ahn, S., Anbil Parthipan, S. C., Courville, A., & Bengio, Y. (2016, August). Generating Factoid Questions with Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus [Paper]. 54th annual meeting of the Association for Computational Linguistics, Berlin, Germany. External link

T

Trabelsi, C., Bilaniuk, O., Zhang, Y., Serdyuk, D., Subramanian, S., Santos, J. F., Mehri, S., Rostamzadeh, N., Bengio, Y., & Pal, C. J. (2018, April). Deep complex networks [Paper]. 6th International Conference on Learning Representations (ICLR 2018), Vancouver, BC, Canada (19 pages). External link

W

Weiss, M., Rahaman, N., Locatello, F., Pal, C. J., Bengio, Y., Scholkopf, B., Ballas, N., & Li, L. E. (2022, November). Neural Attentive Circuits [Poster]. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA. External link

Y

Yuan, X., Côté, M.-A., Fu, J., Lin, Z., Pal, C. J., Bengio, Y., & Trischler, A. (2019, November). Interactive language learning by question answering [Paper]. Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP 2019), Hong Kong, China. External link

Z

Zarpellon, G., Jo, J., Lodi, A., & Bengio, Y. (2021, February). Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies [Paper]. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence. Published in Proceedings of the ... AAAI Conference on Artificial Intelligence, 35(5). External link

List generated on: Fri Apr 25 07:00:15 2025 EDT