The stability of resistive ballooning modes in the second ideal stability region is an important issue that has recently received much attention. In this paper it is shown that the ballooning 1s negative, and therefore that the -driven modes are stable, throughout most of the…
This paper gives a reduction theorem for distributed algorithms (see the discussion of [83]). It includes what I believe to be the first reduction result for liveness properties.
Jan van Leeuwen asked me to write a chapter on distributed systems for this handbook. I realized that I wasn't familiar enough with the literature on distributed algorithms to write it by myself, so I asked Nancy Lynch to help. I also observed that there…
I address practical issues concerning the construction of normative expert systems, and examine the influence diagram as a potential framework for representing knowledge in such systems. I introduce an extension of the influence-diagram representation called a similarity network. A similarity network is a tool for…
We present an overview of our 6-year experience in the design of expert systems for anatomic pathology. Our practical goal is to help practicing pathologists with learning, teaching, and the task of diagnosis by providing them with dynamic expert knowledge by means of a personal…
We examine three probabilistic formulations of the sentence a and b are totally unrelated with respect to a given set of variables U. First, two variables a and b are totally independent if they are independent given any value of any subset of the variables…
Cutset conditioning and clique-tree propagation are two popular methods for performing exact probabilistic inference in Bayesian belief networks. Cutset conditioning is based on decomposition of a subset of network nodes, whereas clique-tree propagation depends on aggregation of nodes. We describe a means to combine cutset…
I had long been fascinated with algorithms that, like the bakery algorithm of [12], do not assume atomicity of their individual operations. I devised the formalism first published in [33] for writing behavioral proofs of such algorithms. I had also long been a believer in…
A similarity network is a tool for constructing belief networks for the diagnosis of a single fault. In this paper, we examine modifications to the similarity-network representation that facilitate the construction of belief networks for the diagnosis of multiple coexisting faults.
We examine a probabilistic model for the diagnosis of multiple diseases. In the model, diseases and findings are represented as binary variables. Also, diseases are marginally independent, features are conditionally independent given disease instances, and diseases interact to produce findings via a noisy or-gate. An…
The intelligent reformulation or restructuring of a belief network can greatly increase the efficiency of inference. However, time expended for reformulation is not available for performing inference. Thus, under time pressure, there is a tradeoff between the time dedicated to reformulating the network and the…
The paper reports recent efforts to further improve the performance of the Sphinx system for speaker-independent continuous speech recognition. The recognition error rate is significantly reduced with incorporation of additional dynamic features, semi-continuous hidden Markov models, and speaker clustering. For the June 1990 (RM2) evaluation…
