Ga Wu
Ga Wu
Researcher at Borealis AI
borealisai.com의 이메일 확인됨
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Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming.
B Say, G Wu, YQ Zhou, S Sanner
IJCAI, 750-756, 2017
392017
Two-stage Model for Automatic Playlist Continuation at Scale
M Volkovs, H Rai, Z Cheng, G Wu, Y Lu, S Sanner
RecSys-2018: ACM Conference on Recommender Systems, 2018
222018
Scalable planning with Tensorflow for hybrid nonlinear domains
G Wu, B Say, S Sanner
NIPS, Advances in Neural Information Processing Systems, 6273-6283, 2017
202017
Noise Contrastive Estimation for One-Class Collaborative Filtering
G Wu, M Volkovs, CL Soon, S Sanner, H Rai
In Proceedings of the 42nd International ACM SIGIR Conference on Research …, 2019
102019
Deep Language-based Critiquing for Recommender Systems
G Wu, K Luo, S Sanner, H Soh
In Proceedings of the 13th ACM Conference of Recommender Systems (RecSys-19 …, 2019
92019
Scalable Planning with Deep Neural Network Learned Transition Models
G Wu, B Say, S Sanner
Journal of Artificial Intelligence Research (JAIR) 68, 571-606, 2020
52020
Latent Linear Critiquing for Conversational Recommender Systems
K Luo, S Sanner, G Wu, H Li, H Yang
In Proceedings of the 29th International Conference on the World Wide Web …, 2020
52020
Bayesian model averaging naive bayes (bma-nb): Averaging over an exponential number of feature models in linear time
G Wu, S Sanner, R Oliveira
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
52015
Deep Critiquing for VAE-based Recommender Systems
K Luo, H Yang, G Wu, S Sanner
In Proceedings of the 43nd International ACM SIGIR Conference on Research …, 2020
32020
One-Class Collaborative Filtering with the Queryable Variational Autoencoder
G Wu, MR Bouadjenek, S Sanner
In Proceedings of the 42nd International ACM SIGIR Conference on Research …, 2019
22019
Noise contrastive estimation for scalable linear models for one-class collaborative filtering
G Wu, M Volkovs, CL Soon, S Sanner, H Rai
arXiv preprint arXiv:1811.00697, 2018
22018
Conditional inference in pre-trained variational autoencoders via cross-coding
G Wu, J Domke, S Sanner
arXiv preprint arXiv:1805.07785, 2018
22018
Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering
JP Zhou, W Ga, Z Mai, S Sanner
arXiv preprint arXiv:2008.01246, 2020
12020
Aesthetic Features for Personalized Photo Recommendation
YQ Zhou, G Wu, S Sanner, P Manggala
RecSys-2018: ACM Conference on Recommender Systems, 2018
12018
Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering
Z Mai, G Wu, K Luo, S Sanner
IEEE International Conference on Data Mining Workshop (ICDMW), 2020
2020
A Ranking Optimization Approach to Latent Linear Critiquing for Conversational Recommender Systems
H Li, S Sanner, K Luo, G Wu
Fourteenth ACM Conference on Recommender Systems, 13-22, 2020
2020
Noise contrastive estimation for collaborative filtering
G Wu, M Volkovs, H Rai
US Patent App. 16/546,134, 2020
2020
One-class Collaborative Filtering with Latent Embeddings: Improvements and Interactive Extensions
G Wu
University of Toronto, PhD thesis, 2020
2020
A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification
Y Wang, G Wu, MR Bouadjenek, S Sanner, S Su, Z Zhang
SIAM International Conference On Data Mining (SDM'19.), 2019
2019
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