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Maksims Volkovs
Maksims Volkovs
Layer 6
Verified email at cs.toronto.edu - Homepage
Title
Cited by
Cited by
Year
Dropoutnet: Addressing cold start in recommender systems
M Volkovs, G Yu, T Poutanen
Advances in Neural Information Processing Systems 30, 2017
2822017
Continuous data cleaning
M Volkovs, F Chiang, J Szlichta, RJ Miller
2014 IEEE 30th International Conference on Data Engineering, 244-255, 2014
1422014
Boltzrank: learning to maximize expected ranking gain
MN Volkovs, RS Zemel
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
1292009
Improving transformer optimization through better initialization
XS Huang, F Perez, J Ba, M Volkovs
International Conference on Machine Learning, 4475-4483, 2020
1212020
Content-based neighbor models for cold start in recommender systems
M Volkovs, GW Yu, T Poutanen
Proceedings of the Recommender Systems Challenge 2017, 1-6, 2017
1062017
X-pool: Cross-modal language-video attention for text-video retrieval
SK Gorti, N Vouitsis, J Ma, K Golestan, M Volkovs, A Garg, G Yu
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
942022
HGCF: Hyperbolic graph convolution networks for collaborative filtering
J Sun, Z Cheng, S Zuberi, F Pérez, M Volkovs
Proceedings of the Web Conference 2021, 593-601, 2021
942021
Effective latent models for binary feedback in recommender systems
M Volkovs, GW Yu
Proceedings of the 38th international ACM SIGIR conference on research and …, 2015
822015
A flexible generative model for preference aggregation
MN Volkovs, RS Zemel
Proceedings of the 21st International Conference on World Wide Web, 2012
802012
Learning to rank with multiple objective functions
KM Svore, MN Volkovs, CJC Burges
Proceedings of the 20th international conference on World wide web, 367-376, 2011
792011
Context-aware scene graph generation with seq2seq transformers
Y Lu, H Rai, J Chang, B Knyazev, G Yu, S Shekhar, GW Taylor, M Volkovs
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
702021
Collaborative ranking with 17 parameters
M Volkovs, R Zemel
Advances in Neural Information Processing Systems 25, 2012
682012
Predicting adverse outcomes due to diabetes complications with machine learning using administrative health data
M Ravaut, H Sadeghi, KK Leung, M Volkovs, K Kornas, V Harish, ...
NPJ digital medicine 4 (1), 24, 2021
522021
New learning methods for supervised and unsupervised preference aggregation
MN Volkovs, RS Zemel
The Journal of Machine Learning Research 15 (1), 1135-1176, 2014
522014
Weakly supervised action selection learning in video
J Ma, SK Gorti, M Volkovs, G Yu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
512021
Probabilistic simulation of quantum circuits using a deep-learning architecture
J Carrasquilla, D Luo, F Pérez, A Milsted, BK Clark, M Volkovs, L Aolita
Physical Review A 104 (3), 032610, 2021
502021
Two-stage model for automatic playlist continuation at scale
M Volkovs, H Rai, Z Cheng, G Wu, Y Lu, S Sanner
Proceedings of the ACM Recommender Systems Challenge 2018, 1-6, 2018
482018
Noise Contrastive Estimation for One-Class Collaborative Filtering
G Wu, M Volkovs, CL Soon, S Sanner, H Rai
Proceedings of the 41st International ACM SIGIR Conference on Research and …, 2019
432019
Development and validation of a machine learning model using administrative health data to predict onset of type 2 diabetes
M Ravaut, V Harish, H Sadeghi, KK Leung, M Volkovs, K Kornas, ...
JAMA network open 4 (5), e2111315-e2111315, 2021
412021
Guided similarity separation for image retrieval
C Liu, G Yu, M Volkovs, C Chang, H Rai, J Ma, SK Gorti
Advances in Neural Information Processing Systems 32, 2019
412019
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