This technical report addresses how to hide secrets from an operating system. The authors provide a detailed design for the VM blackbox and some microarchitecture level simulation derived performance data. They also describe a compiler directed prefetch scheme that uses both instruction and data prefetches to obfuscate the address traces on the address bus between on-chip L2 cache and memory.

This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the sense from WordNet. SenseLearner participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%.

This presentation accompanies a paper discussing research on a novel scheme to reduce static leakage energy in SRAM arrays.

This paper investigates the application of co-training and self-training to word sense disambiguation. Optimal and empirical parameter selection methods for co-training and self-training are investigated, with various degrees of error reduction. A new method that combines co-training with majority voting is introduced, with the effect of smoothing the bootstrapping learning curves, and improving the average performance.

This paper introduces a new codification scheme for efficient computation of measures in semantic networks. The scheme is particularly useful for fast computation of semantic associations between words and implementation of an informational retrieval operator for efficient search in semantic spaces. Other applications may also be possible.

This paper discusses an impact of interference model on capacity in CDMA cellular networks.

This article discusses open text semantic parsing using FrameNet and WordNet.

This paper discusses an evaluation exercise for Romanian word sense disambiguation.

This paper discusses global versus local call admission control.

This presentation discusses interference model impacts on capacity, global call admission controls, local call admission controls, and the differences in global versus local call admission controls.

Abstract: This paper presents an innovative unsupervised method for automatic sentence extraction using graph-based ranking algorithms. We evaluate the method in the context of a text summarization task, and show that the results obtained compare favorably with previously published results on established benchmarks.

This presentation introduces code division multiple access (CDMA) networks, average and actual interference models, optimized capacity, and the 2D Gaussian user model.

This paper shows results from the application of a novel variant of Random Forests to the shallow semantic parsing problem.

This paper presents the task definition, resources, participating systems, and comparative results for the English lexical sample task, which was organized as part of the SENSEVAL-3 evaluation exercise.

This paper describes the English-Hindi Multilingual lexical sample task in SENSEVAL-3.

In this paper, the authors introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications.

This paper describes an algorithm for open text shallow semantic parsing.

This article discusses PageRank on semantic networks, with application to word sense disambiguation.

This presentation gives an overview of code division multiple access (CDMA), traffic and mobility models, subscriber optimization formulation, and numerical results.

This paper discusses subscriber maximization in CDMA cellular networks.

This paper discusses a logic programming framework for semantic interpretation with WordNet and PageRank.

This presentation discusses wireless networks, access point selections, traffic balancing, multi-cell CDMA, user distribution modeling, and call admission control.

This paper discusses the main lines of research in deriving efficient Word Sense Disambiguation.