NIPS 2017

Pruning AI networks without performance loss

In a spotlight paper from the 2017 NIPS Conference, my team and I presented an AI optimization framework we call Net-Trim, which is a layer-wise convex scheme to prune a pre-trained deep neural network. Deep learning has become a method of choice for many AI applications, ranging from image recognition to language translation. Thanks to […]

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Making interaction with AI systems more natural with textual grounding

In an upcoming oral presentation at the 2017 Neural Information Processing Systems (NIPS) Conference, our teams from the University of Illinois at Urbana-Champaign and IBM Research AI have proposed a new supervised learning algorithm to solve a well-known problem in AI called textual grounding. Imagine you wanted to ask someone to hand you an object. […]

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IBM Research showcases AI advances @ NIPS 2017

At the 2017 NIPS conference in Long Beach, CA, IBM will showcase new advances from its AI research team via technical papers as well as results from the company’s ongoing collaboration with academic institutions through the MIT IBM Watson AI Lab and the AI Horizons Network. IBM and MIT scientists will unveil and publish a […]

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