Michael I. Jordan

Martin J. Wainwright

The core of this paper is a general set of variational principles for the problems of computing marginal probabilities and modes, applicable to multivariate statistical models in the exponential family.

Graphical Models, Exponential Families, and Variational Inference

Thomas Petsche

Michael C. Mozer

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes neural networks and genetic algorithms, cognitive science, neuroscience and biology, computer science, AI, applied mathematics, physics, and many branches of engineering. Only about 30% of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. All of the papers presented appear in these proceedings.

Proceedings of the 1996 Conference

Advances in Neural Information Processing Systems 9

Michael J. Kearns

Sara A. Solla

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.

Michael I. Jordan

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