Research Output

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2020

Region-based active learning

Cortes, C., DeSalvo, G., Gentile, C., Mohri, M. & Zhang, N., 2020.

Research output: Contribution to conferencePaper

Static scheduling in clouds

Henzinger, T. A., Singh, A. V., Zufferey, D., Singh, V. & Wies, T., 2020.

Research output: Contribution to conferencePaper

Support and invertibility in domain-invariant representations

Johansson, F. D., Sontag, D. & Ranganath, R., 2020.

Research output: Contribution to conferencePaper

2019

Accelerating eulerian fluid simulation with convolutional networks

Tompson, J., Schlachter, K., Sprechmann, P. & Perlin, K., Jan 1 2019.

Research output: Contribution to conferencePaper

Dialogwae: Multimodal response generation with conditional Wasserstein auto-encoder

Gu, X., Cho, K., Ha, J. W. & Kim, S., 2019.

Research output: Contribution to conferencePaper

Diffusion scattering transforms on graphs

Gama, F., Bruna, J. & Ribeiro, A., Jan 1 2019.

Research output: Contribution to conferencePaper

Entropy-SGD: Biasing gradient descent into wide valleys (International Conference on Learning Representations, ICLR 2017)

Chaudhari, P., Choromanska, A., Soatto, S., LeCun, Y., Baldassi, C., Borgs, C., Chayes, J., Sagun, L. & Zecchina, R., 2019.

Research output: Contribution to conferencePaper

Entropy-SGD: Biasing gradient descent into wide valleys. International Conference on Learning Representations (ICLR) 2017

Chaudhari, P., Choromanska, A., Soatto, S., LeCun, Y., Baldassi, C., Borgs, C., Chayes, J., Sagun, L. & Zecchina, R., Jan 1 2019.

Research output: Contribution to conferencePaper

Hierarchical RL using an ensemble of proprioceptive periodic policies

Marino, K., Gupta, A., Szlam, A. & Fergus, R., Jan 1 2019.

Research output: Contribution to conferencePaper

Model-predictive policy learning with uncertainty regularization for driving in dense traffic

Henaff, M., LeCun, Y. & Canziani, A., Jan 1 2019.

Research output: Contribution to conferencePaper

Practical multi-fidelity Bayesian optimization for hyperparameter tuning

Wu, J., Toscano-Palmerin, S., Frazier, P. I. & Wilson, A. G., 2019.

Research output: Contribution to conferencePaper

Practical multi-fidelity Bayesian optimization for hyperparameter tuning

Wu, J., Toscano-Palmerin, S., Frazier, P. I. & Wilson, A. G., Jan 1 2019.

Research output: Contribution to conferencePaper

Practical multi-fidelity bayesian optimization for hyperparameter tuning supplementary material

Wu, J., Toscano-Palmerin, S., Frazier, P. I. & Wilson, A. G., Jan 1 2019.

Research output: Contribution to conferencePaper

Reproducibility in machine learning for health

McDermott, M. B. A., Wang, S., Marinsek, N., Ranganath, R., Ghassemi, M. & Foschini, L., Jan 1 2019.

Research output: Contribution to conferencePaper

Revisiting auxiliary latent variables in generative models

Lawson, D., Tucker, G., Dai, B. & Ranganath, R., Jan 1 2019.

Research output: Contribution to conferencePaper

Subspace inference for Bayesian deep learning

Izmailov, P., Maddox, W. J., Kirichenko, P., Garipov, T., Vetrov, D. & Wilson, A. G., Jan 1 2019.

Research output: Contribution to conferencePaper

Supervised community detection with line graph neural networks

Chen, Z., Bruna, J. & Li, L., Jan 1 2019.

Research output: Contribution to conferencePaper

The Andoni–Krauthgamer–Razenshteyn characterization of sketchable norms fails for sketchable metrics

Khot, S. & Naor, A., 2019, p. 1814-1824. 11 p.

Research output: Contribution to conferencePaper

Open Access

There are many consistent explanations of unlabeled data: Why you should average

Athiwaratkun, B., Finzi, M., Izmailov, P. & Wilson, A. G., Jan 1 2019.

Research output: Contribution to conferencePaper

The role of over-parametrization in generalization of neural networks

Neyshabur, B., Li, Z., Bhojanapalli, S., LeCun, Y. & Srebro, N., Jan 1 2019.

Research output: Contribution to conferencePaper

Topology and geometry of half-rectified network optimization

Daniel Freeman, C. & Bruna, J., Jan 1 2019.

Research output: Contribution to conferencePaper

Tracking the world state with recurrent entity networks

Henaff, M., Weston, J., Szlam, A., Bordes, A. & LeCun, Y., Jan 1 2019.

Research output: Contribution to conferencePaper

Understanding trainable sparse coding via matrix factorization

Moreau, T. & Bruna, J., Jan 1 2019.

Research output: Contribution to conferencePaper

2018

Boundary-seeking generative adversarial networks

Hjelm, R. D., Jacob, A. P., Che, T., Trischler, A., Cho, K. & Bengio, Y., Jan 1 2018.

Research output: Contribution to conferencePaper

Competing with automata-based expert sequences

Mohri, M. & Yang, S., 2018, p. 1732-1740. 9 p.

Research output: Contribution to conferencePaper

Divide and conquer networks

Nowak, A., Folqué, D. & Bruna, J., Jan 1 2018.

Research output: Contribution to conferencePaper

Emergent communication in a multi-modal, multi-step referential game

Evtimova, K., Drozdov, A., Kiela, D. & Cho, K., Jan 1 2018.

Research output: Contribution to conferencePaper

Emergent translation in multi-agent communication

Lee, J., Cho, K., Weston, J. & Kiela, D., Jan 1 2018.

Research output: Contribution to conferencePaper

Few-shot learning with graph neural networks

Garcia, V. & Bruna, J., Jan 1 2018.

Research output: Contribution to conferencePaper

Gaussian process subset scanning for anomalous pattern detection in non-iid data

Herlands, W., McFowland, E., Wilson, A. G. & Neill, D. B., 2018, p. 425-434. 10 p.

Research output: Contribution to conferencePaper

Hierarchical density order embeddings

Athiwaratkun, B. & Wilson, A. G., Jan 1 2018.

Research output: Contribution to conferencePaper

Intrinsic motivation and automatic curricula via asymmetric self-play

Sukhbaatar, S., Lin, Z., Kostrikov, I., Synnaeve, G., Szlam, A. & Fergus, R., Jan 1 2018.

Research output: Contribution to conferencePaper

MONARCH: Gaining command on geo-distributed graph analytics

Iyer, A. P., Panda, A., Chowdhury, M., Akella, A., Shenker, S. & Stoica, I., 2018.

Research output: Contribution to conferencePaper

Product kernel interpolation for scalable gaussian processes

Gardner, J. R., Pleiss, G., Wu, R., Weinberger, K. Q. & Wilson, A. G., 2018, p. 1407-1416. 10 p.

Research output: Contribution to conferencePaper

Proximity variational inference

Altosaar, J., Ranganath, R. & Blei, D. M., 2018, p. 1961-1969. 9 p.

Research output: Contribution to conferencePaper

Stable and effective trainable greedy decoding for sequence to sequence learning

Chen, Y., Cho, K., Bowman, S. R. & Li, V. O. K., Jan 1 2018.

Research output: Contribution to conferencePaper

Unsupervised neural machine translation

Artetxe, M., Labaka, G., Agirre, E. & Cho, K., 2018.

Research output: Contribution to conferencePaper

Variational sequential Monte Carlo

Naesseth, C. A., Linderman, S. W., Ranganath, R. & Blei, D. M., 2018, p. 968-977. 10 p.

Research output: Contribution to conferencePaper

2017

NON-TWO-PHASE LOCKING PROTOCOLS WITH SHARED AND EXCLUSIVE LOCKS.

Kedem, Z. & Silberschatz, A., Jan 1 2017, p. 309-317. 9 p.

Research output: Contribution to conferencePaper

ON FINDING SEVERAL SHORTEST PATHS IN CERTAIN GRAPHS.

Kedem, Z. M. & Fuchs, H., Jan 1 2017, p. 677-686. 10 p.

Research output: Contribution to conferencePaper

Query-efficient imitation learning for end-to-end simulated driving

Zhang, J. & Cho, K., 2017, p. 2891-2897. 7 p.

Research output: Contribution to conferencePaper

SIMPLIFICATION OF RETRIEVAL REQUESTS GENERATION BY QUESTION-ANSWERING SYSTEMS.

Grishman, R., Jan 1 2017, p. 400-406. 7 p.

Research output: Contribution to conferencePaper

Structured inference networks for nonlinear state space models

Krishnan, R. G., Shalit, U. & Sontag, D., 2017, p. 2101-2109. 9 p.

Research output: Contribution to conferencePaper

Topology and geometry of half-rectified network optimization

Daniel Freeman, C. & Bruna, J., 2017.

Research output: Contribution to conferencePaper

Understanding trainable sparse coding via matrix factorization

Moreau, T. & Bruna, J., 2017.

Research output: Contribution to conferencePaper

Universum prescription: Regularization using unlabeled data

Zhang, X. & LeCun, Y., 2017, p. 2907-2913. 7 p.

Research output: Contribution to conferencePaper

2016

Accelerating online convex optimization via adaptive prediction

Mohri, M. & Yang, S., 2016, p. 848-856. 9 p.

Research output: Contribution to conferencePaper

Bayesian nonparametric kernel-learning

Oliva, J. B., Dubey, A., Wilson, A. G., Póczos, B., Schneider, J. & Xing, E. P., 2016, p. 1078-1086. 9 p.

Research output: Contribution to conferencePaper

Deep kernel learning

Wilson, A. G., Hu, Z., Salakhutdinov, R. & Xing, E. P., 2016, p. 370-378. 9 p.

Research output: Contribution to conferencePaper

Deep multi-scale video prediction beyond mean square error

Mathieu, M., Couprie, C. & LeCun, Y., Jan 1 2016.

Research output: Contribution to conferencePaper