Matt J. Kusner
Matt J. Kusner
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Cited by
Cited by
From word embeddings to document distances
M Kusner, Y Sun, N Kolkin, K Weinberger
International conference on machine learning, 957-966, 2015
Counterfactual fairness
MJ Kusner, J Loftus, C Russell, R Silva
Advances in neural information processing systems 30, 2017
Grammar variational autoencoder
MJ Kusner, B Paige, JM Hernández-Lobato
International conference on machine learning, 1945-1954, 2017
Bayesian optimization with inequality constraints.
JR Gardner, MJ Kusner, ZE Xu, KQ Weinberger, JP Cunningham
ICML 2014, 937-945, 2014
Gans for sequences of discrete elements with the gumbel-softmax distribution
MJ Kusner, JM Hernández-Lobato
arXiv preprint arXiv:1611.04051, 2016
Supervised Word Mover's Distance
G Huang, C Guo, MJ Kusner, Y Sun, F Sha, KQ Weinberger
Advances in Neural Information Processing Systems, 3270-3278, 2016
QUOTIENT: two-party secure neural network training and prediction
N Agrawal, A Shahin Shamsabadi, MJ Kusner, A Gascón
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications …, 2019
A survey on contextual embeddings
Q Liu, MJ Kusner, P Blunsom
arXiv preprint arXiv:2003.07278, 2020
When worlds collide: integrating different counterfactual assumptions in fairness
C Russell, MJ Kusner, J Loftus, R Silva
Advances in neural information processing systems 30, 2017
Unsupervised point cloud pre-training via occlusion completion
H Wang, Q Liu, X Yue, J Lasenby, MJ Kusner
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
Cost-sensitive tree of classifiers
Z Xu, M Kusner, K Weinberger, M Chen
International conference on machine learning, 133-141, 2013
Blind justice: fairness with encrypted sensitive attributes
N Kilbertus, A Gascón, MJ Kusner, M Veale, KP Gummadi, A Weller
ICML, 2018
Causal reasoning for algorithmic fairness
JR Loftus, C Russell, MJ Kusner, R Silva
arXiv preprint arXiv:1805.05859, 2018
TAPAS: tricks to accelerate (encrypted) prediction as a service
A Sanyal, MJ Kusner, A Gascón, V Kanade
ICML, 2018
Classifier cascades and trees for minimizing feature evaluation cost
Z Xu, MJ Kusner, KQ Weinberger, M Chen, O Chapelle
The Journal of Machine Learning Research 15 (1), 2113-2144, 2014
A model to search for synthesizable molecules
J Bradshaw, B Paige, MJ Kusner, M Segler, JM Hernández-Lobato
Advances in Neural Information Processing Systems 32, 2019
Stochastic neighbor compression
M Kusner, S Tyree, K Weinberger, K Agrawal
International conference on machine learning, 622-630, 2014
Fast distributed k-center clustering with outliers on massive data
G Malkomes, MJ Kusner, W Chen, KQ Weinberger, B Moseley
Advances in Neural Information Processing Systems 28, 2015
Deep manifold traversal: Changing labels with convolutional features
JR Gardner, P Upchurch, MJ Kusner, Y Li, KQ Weinberger, K Bala, ...
arXiv preprint arXiv:1511.06421, 2015
The long road to fairer algorithms
MJ Kusner, JR Loftus
Nature 578 (7793), 34-36, 2020
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