In our output perturbation method, the parties combine local models within a secure computation and then add the required differential privacy noise before revealing the model.

The resulting mean function is used for regression.

Existing machine learning algorithms including deep neural networks achieve good performance in cases where the training and the test data are sampled from the same distribution. While this is a reasonable assumption to make, it might not hold true in practice.

We introduce two novel tree search algorithms that use a policy to guide search.

Neural Information Processing Systems http://nips.cc/

Both the character and word piece models are developed for acoustic modeling, and the corresponding RNN based language models are used for beam search decoding.

We propose a general, theoretically justified mechanism for processing missing data by neural networks. Our idea is to replace typical neuron's response in the

Neural Information Processing Systems http://nips.cc/

We formulate the problem of defogging as state estimation and future state prediction from previous, partial observations in the context of real-time strategy games.

Neural Information Processing Systems http://nips.cc/