conferences

Beyond Backprop: Online Alternating Minimization with Auxiliary Variables

Since its introduction in the 1970s, the backpropagation algorithm (backprop) has been the workhorse for training neural networks has and contributed to impressive successes in deep learning for a wide range of applications. Backprop plays an important role in enabling neural networks to track the errors they make, learn from those mistakes and improve over […]

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Estimating Information Flow in Deep Neural Networks

Understanding of the macroscopic behavior of deep learning neural networks.

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IBM Research AI Moves Machine Learning Forward at ICML 2019

At the 36th International Conference on Machine Learning (ICML 2019), June 10–15 in Long Beach, CA, IBM Research AI will present recent technical advances in machine learning for AI and data science. We’ve led the exploration and development of machine learning technologies for decades, and now we’re progressing the AI field through our portfolio of […]

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Exploring the Expressive Range of Conversational Laughter with AI

IBM scientists use crowdsourcing and AI techniques to explore what different types of conversational laughter can tell us.

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IBM Sets New Transcription Performance Milestone on Automatic Broadcast News Captioning

IBM sets new performance records for automatic captioning of broadcast news audio, with error rates of 6.5% and 5.9% on two broadcast news benchmarks.

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Ultra-Low-Precision Training of Deep Neural Networks

IBM researchers introduce accumulation bit-width scaling, addressing a critical need in ultra-low-precision hardware for training deep neural networks.

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Leveraging Temporal Dependency to Combat Audio Adversarial Attacks

A new approach to defend against adversarial attacks in non-image tasks, such as audio input and automatic speech recognition.

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Unifying Continual Learning and Meta-Learning with Meta-Experience Replay

Meta-Experience Replay (MER) integrates meta-learning and experience replay to achieve state-of-the-art performance on continual learning benchmarks.

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Will Adam Algorithms Work for Me?

A simple and effective approach to monitor the convergence of Adam algorithms, a generic class of adaptive gradient methods for non-convex optimization.

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IBM Research AI Advancing, Trusting, and Scaling Learning at ICLR

IBM researchers present recent work on advancing, trusting, and scaling learning at the annual International Conference on Learning Representations (ICLR).

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IBM Research AI at CHI 2019

At the ACM CHI Conference on Human Factors in Computing Systems, IBM researchers present recent work in human-computer interaction in the context of AI.

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AI Holds Promise for Glaucoma, a Leading Global Cause of Blindness

IBM Research and New York University are using AI to analyze retina imaging data and help to assess the presence of glaucoma.

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