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Russ Salakhutdinov

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Very excited about taking on a new role as a director of AI research at Apple in addition to my work at CMU as an associate professor in the Machine Learning Department. Lots of truly amazing AI and Machine Learning projects are taking place all over Apple and I am thrilled to be part of it.

We will be building a team of top-notch Machine Learning and Deep Learning researchers, working on challenging R&D projects as well as conducting fundamental research to advance the state-of-the-art in AI! We are looking for both full-time research scientists as well as postdoctoral fellows to join my team. Apply or ping me if you are interested.*USA&pN=0&openJobId=52662972

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Heading to the Deep Learning Summer School in Montreal.
Will give a focused tutorial on Learning Deep Generative Models,
covering mathematical basics of RBMs, Deep Boltzmann Machines,
Helmholtz Machines, Variational and Importance Weighted Autoencoders (i-ways).
Slides should be up online very soon.

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Gated-Attention Readers for Text Comprehension
with Bhuwan Dhingra, Hanxiao Liu, William W. Cohen

The paper looks at the problem of answering cloze-style questions over short documents. Key point: use multiplicative interactions between the query embedding and intermediate states of a recurrent neural network reader.

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Machine Learning Faculty Retreat at CMU -- about 25 machine learning faculty and we are growing!

If you want to do machine learning, this is the place -- with over 70 ML PhD students, about 10 postdocs, and over 20 MSc in our own Machine Learning Department.

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New paper on Multiplicative Integration with Recurrent Neural Networks with Tony Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio.

The paper introduces a simple structural design called Multiplicative Integration (MI) to improve recurrent neural networks (RNNs). MI changes the way in which information from difference sources flows and is integrated in the computational building block of an RNN, while introducing almost no extra parameters. It can be easily embedded into many popular RNN models, including LSTMs and GRUs.

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Encode, Review, and Decode: Reviewer Module for Caption Generation
Zhilin Yang, Ye Yuan, Yuexin Wu, Ruslan Salakhutdinov, William Cohen

This work develops a generic reviewer module that can be plugged into an existing encoder-decoder model. The reviewer module performs a number of review steps with attention mechanism on the encoder hidden states, and outputs a fact vector after each review step; the fact vectors are then used as the input of the attention mechanism in the decoder.

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New paper on Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations.
with Behnam Neyshabur, Tony Wu, and Nathan Srebro

Here, we investigate the parameter-space geometry of recurrent neural networks, and develop an adaptation of path-SGD optimization method, attuned to this geometry, that can learn plain RNNs with ReLU activations.

Congratulations to my two amazing postdocs +Roger Grosse  and +Yura Burda  -- Yura is joining OpenAI as a research scientist and Roger is joining Department of Computer Science at the University of Toronto as an assistant professor!

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If you are going to ICLR, check out these posters/papers, and more importantly, check out (some of the) associated code -- I am trying to encourage all my students to release their code!

Importance Weighted Autoencoders, Yuri Burda, Roger Grosse, Ruslan Salakhutdinov, ICLR 2016

Generating Images from Captions with Attention, Elman Mansimov, Emilio Parisotto, Jimmy Lei Ba, Ruslan Salakhutdinov, ICLR 2016

Action Recognition using Visual Attention, Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov, ICLR workshop 2016

Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning, Emilio Parisotto, Jimmy Lei Ba, Ruslan Salakhutdinov, ICLR 2016
Code: coming soon.

Data-Dependent Path Normalization in Neural Networks, Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro, ICLR 2016

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Check out code by Elman Mansimov for our paper on Generating Images from Captions with Attention. If you want to learn a model that knows how to "draw" images of "elephants flying in blue skies", here you go:)
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